Comm100 Forums & FAQ

Does Comm100 offer discounts to military families and veterans?

Does Comm100 give discounts to veterans? What special promotions or coupons are available to military veterans and military families at Comm100? Does Comm100 have a military discounts webpage or website?
Knoji Staff asked this on May 26, 2017 Posted in Comm1000 answers

Does Comm100 offer free returns? What's their exchange policy?

What's Comm100 returns and exchanges policy? Can you return in-store? How many days do you have to return items to Comm100 for a full refund? Do I need a receipt to return my item to Comm100? Do items need to be in new condition?
Knoji Staff asked this on May 26, 2017 Posted in Comm1000 answers

Does Comm100 offer free shipping?

How much does Comm100 charge for shipping? Do they offer free shipping all the time? Where does Comm100 ship from? Do they ship on weekends?
Knoji Staff asked this on May 26, 2017 Posted in Comm1000 answers

Related Customer Support Software Discussions

Which one is better Live chat tool & conventional phone and Email support

Nowadays there are numerous of methods for providing a great customer support like live chat tool, phone support, email and text support etc. While Live chat services provided by trained live chat agents are taking this tool to a new height in the field of customer service. Although Live chat has its own advantages but is it right to say that "live chat will overcome another customer service methods in a very short span of time"?

aryan asked this on Nov 9, 2017 Posted in LiveChat0 answers

How the Insurance Industry can use Artificial Intelligence to Boost Trust

How the insurance industry can use artificial intelligence to boost trust

Insurance  is no place for transactional relationships. At its core, it's about  developing trust and demonstrating you understand your customers. Artificial intelligence (AI) is helping insurers do just that, at a scale that’s never been possible before.

We  all know the cost of acquiring a customer versus the cost of retaining a  customer – no one wants to lose customers and have to replace them. For  the insurance industry, retention comes down to trust. Historically, a  trusted customer-insurer relationship is generated from a great claim  experience, but this paradigm is changing.

The customer has the power


There  is a groundswell of disruption happening across the business world.  Thanks to the increasingly digital, instant and personalised world we  live in, customers now expect a different experience than they once did.  They expect their insurer to demonstrate how well you know them, in  every single interaction – whether it be via the call centre, email or  in person. The customer experience has to be personalised and  journey-based. It’s no longer viable to treat every customer the same or  even in broad segments.

Those insurers who fail to act and take  measures to meet the expectations of this new breed of customer, risk  losing them to a competitor who does. Unwavering loyalty is a thing of  the past. Customers are now only one bad experience away from taking  their business elsewhere. Two-thirds of customers say they’re likely to  switch brands if they’re treated like a number instead of an individual,  and 50% feel the same if the company doesn’t anticipate their needs.

Artificial intelligence is the answer


Artificial  intelligence is the key to supercharging human ability, and providing  these bespoke experiences that our customers are demanding. Positively,  insurance is especially likely to benefit from AI, due to the wealth of customer data at your fingertips.  This data feeds the AI engine, and the more quality data it can get its  hands on, the more intelligent the technology becomes and the better  the outcome.

While AI has been around for decades, it hasn’t been  until now that the technology has advanced to a point that can benefit  businesses of all sizes and budgets – one of our main goals with the AI  that’s embedded across our platforms, Einstein, is to democratise AI.  Improvements in computing power, the advent of big data and advances in  machine learning have all contributed to the rise of AI.

The benefits of artificial intelligence are many and varied


Artificial  intelligence such as Einstein works by analysing customer data, finding  patterns and developing deep insights into individual customers – at a  rate not humanly possible. This insight can then be used to engage  clients, help shape new products, and predict what offers or solutions  are going to resonate best with an individual. All of this has the  potential to deepen client relationships and improve loyalty.

Another  benefit is using artificial intelligence to eliminate mundane admin  tasks. We’re already seeing, in the US, AI being employed in the first  stage of the motor vehicle claims assessment process, analysing photos  of vehicle damage to determine whether it’s a write-off or not.

The  benefits of automating this step are two-fold. Not only does the  technology improve productivity, enabling employees to add value to the  customer relationship instead, but it also allows the payout or repair  to happen much faster, improving the overall customer experience.

Artificial intelligence: where to start


The  first step in unlocking the benefits of artificial intelligence is  getting your customer data into one layer within your organisation. AI  can only become intelligent, accurate and useful if it’s given a  complete and extensive set of data to generate learnings from. It can’t  work its magic if data is siloed between departments and in disparate IT  systems.

Secondly, it's important to have a clear, strategic  view on what you want artificial intelligence to achieve for your  organisation – to determine what part of the customer experience could  most benefit from that level of insight or automation.

In a  recent Gartner report, AI and advanced machine learning is listed as the  number one strategic technology trend for 2017. Artificial intelligence  is here, and it has the potential to completely redefine the insurance  function. Savvy insurers are on-board, quietly implementing AI and  building a competitive advantage in the process – it’s important others  don’t fall behind.

This Article Source is From : https://www.salesforce.com/au/blog/2017/10/how-the-insurance-industry-can-use-artificial-intelligence-to-bo.html

hulda echave asked this on Oct 18, 2017 Posted in Salesforce.com0 answers

How the Insurance Industry can use Artificial Intelligence to Boost Trust

How the insurance industry can use artificial intelligence to boost trust

Insurance  is no place for transactional relationships. At its core, it's about  developing trust and demonstrating you understand your customers. Artificial intelligence (AI) is helping insurers do just that, at a scale that’s never been possible before.

We  all know the cost of acquiring a customer versus the cost of retaining a  customer – no one wants to lose customers and have to replace them. For  the insurance industry, retention comes down to trust. Historically, a  trusted customer-insurer relationship is generated from a great claim  experience, but this paradigm is changing.

The customer has the power


There  is a groundswell of disruption happening across the business world.  Thanks to the increasingly digital, instant and personalised world we  live in, customers now expect a different experience than they once did.  They expect their insurer to demonstrate how well you know them, in  every single interaction – whether it be via the call centre, email or  in person. The customer experience has to be personalised and  journey-based. It’s no longer viable to treat every customer the same or  even in broad segments.

Those insurers who fail to act and take  measures to meet the expectations of this new breed of customer, risk  losing them to a competitor who does. Unwavering loyalty is a thing of  the past. Customers are now only one bad experience away from taking  their business elsewhere. Two-thirds of customers say they’re likely to  switch brands if they’re treated like a number instead of an individual,  and 50% feel the same if the company doesn’t anticipate their needs.

Artificial intelligence is the answer


Artificial  intelligence is the key to supercharging human ability, and providing  these bespoke experiences that our customers are demanding. Positively,  insurance is especially likely to benefit from AI, due to the wealth of customer data at your fingertips.  This data feeds the AI engine, and the more quality data it can get its  hands on, the more intelligent the technology becomes and the better  the outcome.

While AI has been around for decades, it hasn’t been  until now that the technology has advanced to a point that can benefit  businesses of all sizes and budgets – one of our main goals with the AI  that’s embedded across our platforms, Einstein, is to democratise AI.  Improvements in computing power, the advent of big data and advances in  machine learning have all contributed to the rise of AI.

The benefits of artificial intelligence are many and varied


Artificial  intelligence such as Einstein works by analysing customer data, finding  patterns and developing deep insights into individual customers – at a  rate not humanly possible. This insight can then be used to engage  clients, help shape new products, and predict what offers or solutions  are going to resonate best with an individual. All of this has the  potential to deepen client relationships and improve loyalty.

Another  benefit is using artificial intelligence to eliminate mundane admin  tasks. We’re already seeing, in the US, AI being employed in the first  stage of the motor vehicle claims assessment process, analysing photos  of vehicle damage to determine whether it’s a write-off or not.

The  benefits of automating this step are two-fold. Not only does the  technology improve productivity, enabling employees to add value to the  customer relationship instead, but it also allows the payout or repair  to happen much faster, improving the overall customer experience.

Artificial intelligence: where to start


The  first step in unlocking the benefits of artificial intelligence is  getting your customer data into one layer within your organisation. AI  can only become intelligent, accurate and useful if it’s given a  complete and extensive set of data to generate learnings from. It can’t  work its magic if data is siloed between departments and in disparate IT  systems.

Secondly, it's important to have a clear, strategic  view on what you want artificial intelligence to achieve for your  organisation – to determine what part of the customer experience could  most benefit from that level of insight or automation.

In a  recent Gartner report, AI and advanced machine learning is listed as the  number one strategic technology trend for 2017. Artificial intelligence  is here, and it has the potential to completely redefine the insurance  function. Savvy insurers are on-board, quietly implementing AI and  building a competitive advantage in the process – it’s important others  don’t fall behind.

This Article Source is From : https://www.salesforce.com/au/blog/2017/10/how-the-insurance-industry-can-use-artificial-intelligence-to-bo.html

hulda echave asked this on Oct 18, 2017 Posted in Salesforce.com0 answers

Salesforce takes another shot at IoT

Everyone wants a piece of the Internet of Things, and why not? If predictions come to fruition, there are going to be billions and billions of devices and sensors broadcasting information at us by 2020, and someone has to make sense of it and point us to the data that matters. Salesforce wants to be that company (or at least one of them).

Salesforce has never been shy about jumping on the latest tech bandwagon, whether it’s big data, artificial intelligence or the Internet of Things. In fact, Salesforce was talking about IoT long before most companies with an announcement of a Salesforce IoT Cloud way back in 2015 at the company’s mega Dreamforce Conference.

Today, Salesforce announced a new IoT initiative called IoT Explorer Edition designed to help customers make sense of IoT data and put it to work. In 2015 when CEO Marc Benioff launched that IoT Cloud with a bang, it was really about getting a head start on a technology the company sensed could be significant moving forward.

The IoT Explorer Edition is designed to put that vision into reach of more businesses. For starters, it offers what Salesforce is calling a “low code” way of generating IoT business workflows. Non-technical personnel can supposedly pick and choose processes and connect to different devices and sensors to create some type of automated workflow.

For instance, suppose you owned a wind turbine company (it could happen) and you wanted to get a service notice when the turbine was going to require service. You could create a workflow that triggers that notice when capacity falls below a certain level.

Being Salesforce, it doesn’t just want to deliver this information in a vacuum. It wants to tie that information to other Salesforce products like Salesforce Service Cloud. If the workflow triggers a service call, it would be useful for the service person to have access to the service history and the fact you called earlier in the week about a problem with your wind turbines.

Finally, Salesforce wants to help you get proactive about your service calls. Why wait for your customer to call you when you can predict the future with this tool and know with some degree of certainty when a device is going to need service. You could contact the owner and let them know their doohickey is in danger of breaking and you can sell them a new one. How great would that be?

The new IoT Explorer Edition will be generally available starting on October 17th as an add-on to Salesforce’s various clouds.

This Article Source is From: https://techcrunch.com/2017/10/10/salesforce-takes-another-shot-at-iot/

hulda echave asked this on Oct 11, 2017 Posted in Salesforce.com0 answers

Enterprise AI Needs High Data Quality to Succeed

There’s no doubt that AI has usurped big data as the enterprise technology industry’s favorite new buzzword. After all, it’s on Gartner’s 2017 Hype Cycle for emerging technologies, for a reason.

While  progress was slow during the first few decades, AI advancement has  rapidly accelerated during the last decade. Some people say AI will  augment humans and maybe even make us immortal; other pessimistic  individuals say AI will lead to conflict and may even automate our  society out of jobs. Despite the differences in opinion, the fact is,  only a few people can identify what AI really is. Today, we are  surrounded by minute forms of AI, like the voice assistants that we all  hold in our smart phones, without us knowing or perceiving the  efficiency of the service. From Siri to self-driving cars, a lot of  promise has already been shown by AI and the benefits it can bring to  our economy, personal lives and society at large.

The question  now turns to how enterprises will benefit from AI. But, before companies  or people can obtain the numerous improvements AI promises to deliver,  they must first start with good quality, clean data. The success of AI  relies on accurate, cleansed and verified data.

Data Quality and Intelligence Must Go Hand-in-Hand


Organizations  currently use data to extract numerous informational assets that assist  with strategic planning. The strategic plans dictate the future of the  organization and how it fairs within the rising competition. Considering  the importance of data, the potential impact caused by low quality  information is indeed intimidating to think of. In fact, bad data costs  the US about 3 trillion per year.

Recently, I had the opportunity to interview Nicholas Piette and Jean-Michel Francofrom Talend, which is one of the leading big data and cloud integration company.  Nicholas Piette, who is the Chief Evangelist at Talend, has been  working with integration companies for nine years now and has been part  of Talend for over a year.

When asked about the link between both  Data Quality and Artificial Intelligence, Nick Piette responded with  authority that you cannot do one without the other. Both data quality  and AI walk hand-in-hand, and it’s imperative for data quality to be  present for AI to be not only accurate, but impactful.

The Five R’s


To  better understand the concept of data quality and how impacts AI, Nick  used the five R’s method. He mentioned he learned this method from David  Shrier, his professor in MIT. The five R’s mentioned by Nicholas  include:

  1. Relevancy
  2. Recency
  3. Range
  4. Robustness
  5. Reliability


If  the data you are using to fuel your AI driven initiatives ticks off  each one of these R’s, then you are off to the right start. All five of  these hold a particular importance, but relevancy rises above the rest.  Whatever data you have should be relevant to what you do, and should  serve as a guide and not as a deterrent.

We might reach a point  where the large influx of data we have at our fingertips is too  overwhelming for us to realize what elements of it are really useful vs  what is disposable. This is where the concept of data readiness enters  the fold. Having mountains of historical data can be helpful for  extracting patterns and forecasting cyclical behavior or re-engineering  processes that lead to undesirable outcomes. However, as businesses  continue to advance toward the increase use of real-time engines and  applications, the importance of data readiness—or information that is  the most readily or recently made available—takes on greater importance.  The data that you apply should be recent and should have figures that  replicate reality.

AI Use Cases: A look at Healthcare


When asked for the best examples of the use of AI at work today, Nick said he considered the use of AI in healthcare as a shining example of both what has be achieved using AI to-date and  what more companies can do with this technology. More specifically, Nick  said:

“Today, healthcare professionals are using AI technology  to determine the chances of a heart attack in an individual, or predict  cardiac diseases. AI is now ready to assist doctors and help them  diagnose patients in ways they were unable to do before.”

Our  understanding or interpretation of what the AI algorithms produce  dictates the use of AI in healthcare. This is true regardless of its  current accolades. Thus, if an AI system comes up with new insights that  seem ‘foreign’ to our current understanding, it’s often difficult for  the end-user to ‘trust’ that analysis. According to Nick, the only way  society can truly trust and comprehend the results delivered by AI  algorithms is if we know that at the very core of those analyses is  quality data.

Quality-Driven Data


Nicholas  Piette added that ensure data quality is an absolutely necessary  prerequisite for all companies looking to implement AI. He said the  following words in this regard:

“100% of AI projects are subject  to fail if there are no solid efforts beforehand to improve the quality  of the data being used to fuel the applications. Making no effort to  ensure the data you are using, is absolutely accurate and trusted—in my  opinion—is indicative of unclear objectives regarding what AI is  expected to answer or do. I understand it can be difficult to  acknowledge, but if data quality mandates aren’t addressed up front, by  the time the mistake is realized, a lot of damage has already been done.  So make sure it’s forefront.”

Nick also pointed out that hearing  they have a data problem is not easy for organizations to digest.  Adding a light touch of humor, he said “Telling a company it has a data  problem is like telling someone they have an ugly child.” But the only  way to solve a problem is to first realize you have one and be willing  to put in the time needed to fix it.

First Step is Recognition


Referring  to the inability of the companies to realize that they have a problem,  Nicholas pointed out that more than half of the companies that he has  worked with did not believe that they have a data problem until the  problem was pointed out. Once pointed out, they had the AHA! Moment.

Nick  Piette further voiced his opinion that it would be great if AI could,  in the future, exactly tell how it reached an answer and the  computations that went into reaching that conclusion. Until that  happens, data quality and AI run parallel. Success in AI will only come  from the accuracy of data inputted.

 “If you want to be successful, you have to spend more time working on the data and less time working on the AI.”

This Article Source is From : https://readwrite.com/2017/10/09/data-quality-fuels-business-ai/

kishan cv asked this on Oct 11, 2017 Posted in Salesforce.com0 answers

Salesforce Rolls out Data Sharing Platform on Marketing Cloud

Salesforce on Wednesday is rolling out Salesforce Data Studio, a self-service platform on the Marketing Cloud that allows data owners like publishers to directly connect with data buyers.

With a collection of tools to facilitate direct sales of consumer data, Data Studio aims to resolve the problems typically associated with third-party data brokers.

Buyers, typically brands seeking more information about their customer base, "want peer-to-peer relationships with data owners to acquire data that's trustworthy and high fidelity that they can use for things like activation and to grow their insights," Raji Beni, VP of product marketing for Salesforce Marketing Cloud, told ZDNet.

While buyers can get a better understanding of where the data is coming from, sellers can also take more control of where it goes. The platform, Beni said, "provides the ability for data owners to provision data with controls and terms they are comfortable with to ensure it's used in a way that doesn't create concerns for them and also creates opportunities for markets."

Relying on third-party data brokers can leave unanswered questions about the fidelity of the data, Beni said -- "how clean it is and where it was captured" -- as well as questions about the origins of the data or when exactly it was collected.

"The seasonality of markets change frequently," Beni noted, and marketers "don't want to be making decisions based on information that's 24 months old."

Ultimately, he said, it all comes down to the relevance of the data for marketers.

Data Studio includes audience discovery and search tools that should help marketers learn about the data available and how it relates to their brand's own, firsthand data.

It also includes data governance tools for the data owners, allowing them to set certain access parameters, such as what attributes are shared, to whom and for how long. Because the data governance controls are software enabled, there's no contract needed.

Some of the brands using Data Studio, Salesforce said, include large businesses like Anheuser-Busch, Conagra, Essence, Heineken and Keurig. Meanwhile, data owners using it include Bazaarvoice, Gatehouse Media, Kayak, Leaf Group, Penske Media Corporation, Publishers Clearing House, Ranker, Salary.com, and Univision.

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Salesforce steps up developer efforts for Einstein

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This Article Source is From : http://www.zdnet.com/article/salesforce-rolls-out-data-sharing-platform-on-marketing-cloud/

katherine daisy asked this on Oct 9, 2017 Posted in Salesforce.com0 answers

As Data And Cloud Rise, Lines Are Blurring Between Developers And Data Scientists

With the rise of the cloud comes an explosion in the value of data. Because of the increasing prevalence of cloud infrastructure in nearly every industry, data is easier to collect, and the tools  needed to glean intelligence from it are growing in accessibility. The  potential that data offers has catapulted it to the forefront of an  organization’s priorities. In fact, the demand for both data scientists  and data engineers is projected to grow by 39% by 2020, according to a  recent IBM report.

Aside from the spiking demand for data  professionals, what’s interesting is how the rise of data is reshaping  countless roles within companies, from marketers to operations  management. Almost any job critical to a business can be improved with data.  Content can be strategically marketed to consumers based on their  preferences and location; doctors can diagnose patients more accurately  with real-time disease studies; even sports stadiums can tap user data  to bring fans an interactive experience from the second they set foot in  the arena.

To create data-intensive apps, organizations are  looking to their developers and, in turn, their data scientists. As we  shift toward a data-first approach, these two teams -- which have  historically operated in close but separate silos -- are finding  themselves thrown together as they identify, design and create  technologies that harness data.


When joined together with the  right cloud tools and open technologies, developers and data scientists  can help each other to analyze and pick out key data trends and  patterns, build new AI and machine learning models, and make sure that  the right data gets to the right business stakeholders at the right time  -- whether they are customers, employees or decision makers.


Bridging The Gap

The  distinctions between data scientists and developers have always been  somewhat ambiguous, and it seems they continue to become more unclear  every day. For example, if you examine almost any programming model,  what you will find is that core analytics functions that data scientists  have traditionally managed (data handling, statistical analyses and  calculations) have always been at the heart of app development.

Data  scientists have always played a role in building these models by  creating the tools developers need to power their apps. However, this  has historically been done in a process akin to a relay handoff, with  data scientists translating incoming raw data into analytics-friendly  languages such as Python, analyzing it, building models with the  resulting insights and then handing it back over to the development  team, which then typically translates the data again into the best  programming language for its app. After building in these data models,  developers then provide feedback to the data science team on what needs  improvement and the process starts again.

In today’s world of  constant innovation, this pace is not fast enough. To build with data at  a competitive pace, it’s imperative for these two roles to take  advantage of new tools and approaches that allow them to work together. A  few ways include:

Turning to the cloud: Data  platforms and notebooks, powered by the cloud, allow teams such as data  scientists, developers and business analysts to work together across  different languages and data models.

Implementing a collaborative, trusted environment to share data:  Data owners are often hesitant to share intelligence across teams, as  they can be unsure of how to share data as well as what is safe to share  broadly. Creating a data governance strategy, as well as implementing  tools that simplify the cleansing and sharing of data with trusted  parties, helps break down barriers and facilitate collaboration.

Eliminating data analysis silos:  Data analysis has typically been done in a conveyor belt-style  approach, with each data scientist performing a separate step. While  organized, this means a single mistake has the power to ruin an entire  workload. Automation tools can help to eliminate these silos by  simplifying and accelerating data discovery, cleansing and training,  thus giving data scientists the capacity to focus on analysis and  collaboration with others.

As an example, let’s take an airline  that wants to decrease the amount of turbulence each flight experiences.  Working together on a unified cloud platform geared toward both data science and app development,  the airline’s developer and data science teams can work in a  centralized environment to explore data patterns and identify ideas for a  solution. Previously, these teams would have had to spend a tremendous  amount of time passing data back and forth and iterating potential ideas  and machine learning models to build out instead of collaborating on  them together in one space.

This new level of communication and  iteration would yield a product ready to be put into production much  more rapidly. For example, imagine a mobile app for pilots that would  place the most relevant weather data, previous flight reports and  recommended route changes into their hands, helping them to achieve the  smoothest flight possible. In this case, the combined team could bring  in multiple data streams from flight routes, weather patterns and  previous flights.


Working side by side with developers, data  scientists can analyze trends across these sources, communicating with  developers to identify and visualize the most relevant findings. As data  scientists create machine learning models, developers can  simultaneously build out features around these models, giving immediate  feedback about what’s working and what’s not.

The Power Of Collaboration

Technology  is enabling developers and data scientists to do more and share more  while using fewer resources. To streamline processes and effectively  share knowledge, both teams need to be equipped with a cloud platform  and embrace a collaborative environment instead of being restricted to  working in separate silos with different tools and programming  languages.

But this shift is not just about adopting new  technologies -- a culture shift is also required. Business leaders must  also open a line of direct communication with their data science and  development teams to be sure a collaborative mindset is implemented and  adopted.

So, what can your organization do to best serve the people who handle such a valuable asset? More on that to come.

This Article Source is from :  https://www.forbes.com/sites/forbestechcouncil/2017/09/14/as-data-and-cloud-rise-lines-are-blurring-between-developers-and-data-scientists/#1dfaecc75036

hulda echave asked this on Sep 18, 2017 Posted in Salesforce.com0 answers

Atlassian Rolls out Several Cloud-Focused Product Updates

Atlassian on Wednesday is rolling out a number of product enhancements to improve collaboration and visibility across different corporate teams, with many of the updates geared towards customers operating on the cloud.

Already, more than 70 percent of Atlassian's existing customers are using cloud products, while more than 75 percent of new Atlassian customers start with a cloud deployment.

To solve some of the pain points that exist for Atlassian Cloud customers, the company is rolling out Identity Manager, a product with four features: SAML single sign-on for identity management, enforced two-step verification, advanced password policies, and priority cloud support. The cloud support feature promises a one-hour response time for customers facing critical issues on the weekend.

The product is primarily designed for customers that are large enough that they need identity management but may not be ready to adopt a third party identity manager.

"When we look at our customers who are growing and continue to grow on Atlassian Cloud, user management gets to be less convenient than it was when you knew everyone," Rahul Chhabria, product manager for Enterprise Cloud at Atlassian, told ZDNet. "We want customers to trust their data is secure and that our products will be up all the time."

Next, Atlassian is adding Trello boards to Bitbucket Cloud, which brings the project planning capabilities of Trello to Bitbucket, the software collaboration tool. Combining the collaboration tools bridges a gap that existed between software developers and non-technical teams such as designers or marketers.

"We find this experience makes Bitbucket a one-stop shop for software development teams and brings in everyone else that participates in shipping great software," Chhabria said.

In another move focused on hybrid customers, Atlassian is collaborating with Microsoft Azure to let customers deploy Jira Software Data Center on Azure, through a jointly developed customized template. Atlassian introduced AWS support last year.

"We're trying to provide deployment flexibility for them, for whatever environment they're comfortable with," said Junie Dinda, product marketing lead for server products at Atlassian.

Meanwhile, Atlassian is making it easier for support teams to offer help to customers with the new Embedded Portal in Jira Service Desk Cloud. Instead of having to navigate to a different page or send an email to raise a Jira Service Desk request, customers can use an embedded help button that lives anywhere.

Lastly, Atlassian is updating Portfolio for Jira, a project management tool, with two new features. With the new programs feature, business leaders can get an aggregated view of multiple projects -- this gives them visibility into projects that all tie into broader business objectives.

"This is extremely important for executives and managers to understand what's actually going on in their agile software development and how it ties to their business priorities, Dinda said.

Similarly, the dependencies reporting feature gives a visualization of factors on which a project may be dependent. The feature helps managers spot project bottlenecks and find any risks to the project.

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Article Source is From : http://www.zdnet.com/article/atlassian-rolls-out-several-cloud-focused-product-updates/

hulda echave asked this on Sep 15, 2017 Posted in Salesforce.com0 answers

It's Time To Think Beyond Cloud Computing


Fasten your harnesses, because the era of cloud computing’s giant data centers is about to be rear-ended by the age of self-driving cars. Here’s the problem: When a self-driving car has to make snap decisions, it needs answers fast. Even slight delays in updating road and weather conditions could mean longer travel times or dangerous errors. But those smart vehicles of the near-future don’t quite have the huge computing power to process the data necessary to avoid collisions, chat with nearby vehicles about optimizing traffic flow, and find the best routes that avoid gridlocked or washed-out roads. The logical source of that power lies in the massive server farms where hundreds of thousands of processors can churn out solutions. But that won’t work if the vehicles have to wait the 100 milliseconds or so it usually takes for information to travel each way to and from distant data centers. Cars, after all, move fast.

That problem from the frontier of technology is why many tech leaders foresee the need for a new “edge computing” network—one that turns the logic of today’s cloud inside out. Today the $247 billion cloud computing industry funnels everything through massive centralized data centers operated by giants like Amazon, Microsoft, and Google. That’s been a smart model for scaling up web search and social networks, as well as streaming media to billions of users. But it’s not so smart for latency-intolerant applications like autonomous cars or mobile mixed reality.


“It’s a foregone conclusion that giant, centralized server farms that take up 19 city blocks of power are just not going to work everywhere,” says Zachary Smith, a double-bass player and Juilliard School graduate who is the CEO and cofounder of a New York City startup called Packet. Smith is among those who believe that the solution lies in seeding the landscape with smaller server outposts—those edge networks—that would widely distribute processing power in order to speed its results to client devices, like those cars, that can’t tolerate delay.

Packet’s scattered micro datacenters are nothing like the sprawling facilities operated by Amazon and Google, which can contain tens of thousands of servers and squat outside major cities in suburbs, small towns, or rural areas, thanks to their huge physical footprints and energy appetites. Packet’s centers often contain just a few server racks—but the company promises customers in major cities speedy access to raw computing power, with average delays of just 10 to 15 milliseconds (an improvement of roughly a factor of ten). That kind of speed is on the “must have” lists of companies and developers hoping to stream virtual reality and augmented reality experiences to smartphones, for example. Such experiences rely upon a neurological process—the vestibulo-ocular reflex—that coordinates eye and head movements. It occurs within seven milliseconds, and if your device takes 10 times that long to hear back from a server, forget about suspension of disbelief.

Immersive experiences are just the start of this new kind of need for speed. Everywhere you look, our autonomously driving, drone-clogged, robot-operated future needs to shave more milliseconds off its network-roundtrip clock. For smart vehicles alone, Toyota noted that the amount of data flowing between vehicles and cloud computing services is estimated to reach 10 exabytes per month by 2025.
Cloud computing giants haven’t ignored the lag problem. In May, Microsoft announced the testing of its new Azure IoT Edge service, intended to push some cloud computing functions onto developers’ own devices. Barely a month later, Amazon Web Services opened up general access to AWS Greengrass software that similarly extends some cloud-style services to devices running on local networks. Still, these services require customers to operate hardware on their own. Customers who are used to handing that whole business off to a cloud provider may view that as a backwards step.


US telecom companies are also seeing their build-out of new 5G networks—which should eventually support faster mobile data speeds—as a chance to cut down on lag time. As the service providers expand their networks of cell towers and base stations, they could seize the opportunity to add server power to the new locations. In July, AT&T announced plans to build a mobile edge computing network based on 5G, with the goal of reaching “single-digit millisecond latency.” Theoretically, data would only need to travel a few miles between customers and the nearest cell tower or central office, instead of hundreds of miles to reach a cloud data center.


“Our network consists of over 5,000 central offices, over 65,000 cell towers, and even several hundred thousand distribution points beyond that, reaching into all the neighborhoods we serve,” says Andre Fuetsch, CTO at AT&T. “All of a sudden, all those physical locations become candidates for compute.”


AT&T claims it has a head start on rival telecoms because of its “network virtualization initiative,” which includes the software capability to automatically juggle workloads and make good use of idle resources in the mobile network, according to Fuetsch. It’s similar to how big data centers use virtualization to spread out a customer’s data processing workload across multiple computer servers.


Meanwhile, companies such as Packet might be able to piggyback their own machines onto the new facilities, too. ”I think we’re at this time where a huge amount of investment is going into mobile networks over the next two to three years,” Packet’s Smith says. “So it’s a good time to say ‘Why not tack on some compute?’” (Packet’s own funding comes in part from the giant Japanese telecom and internet conglomerate Softbank, which invested $9.4 million in 2016.) In July 2017, Packet announced its expansion to Ashburn, Atlanta, Chicago, Dallas, Los Angeles, and Seattle, along with new international locations in Frankfurt, Toronto, Hong Kong, Singapore, and Sydney.


Packet is far from the only startup making claims on the edge. Austin-based Vapor IO has already begun building its own micro data centers alongside existing cell towers. In June, the startup announced its “Project Volutus” initiative, which includes a partnership with Crown Castle, the largest US provider of shared wireless infrastructure (and a Vapor IO investor). That enables Vapor IO to take advantage of Crown Castle’s existing network of 40,000 cell towers and 60,000 miles of fiber optic lines in metropolitan areas. The startup has been developing automated software to remotely operate and monitor micro data centers to ensure that customers don’t experience interruptions in service if some computer servers go down, says Cole Crawford, Vapor IO’s founder and CEO.

Don’t look for the edge to shut down all those data centers in Oregon, North Carolina, and other rural outposts: Our era’s digital cathedrals are not vanishing anytime soon. Edge computing’s vision of having “thousands of small, regional and micro-regional data centers that are integrated into the last mile networks” is actually a “natural extension of today’s centralized cloud,” Crawford says. In fact, the cloud computing industry has extended its tentacles toward the edge with content delivery networks such as Akamai, Cloudflare, and Amazon CloudFront that already use “edge locations” to speed up delivery of music and video streaming.


Nonetheless, the remote computing industry stands on the cusp of a “back to the future” moment, according to Peter Levine, general partner at the venture capital firm Andreessen Horowitz. In a 2016 video presentation, Levine highlighted how the pre-2000 internet once relied upon a decentralized network of PCs and client servers. Next, the centralized network of the modern cloud computing industry really took off, starting around 2005. Now, demand for edge computing is pushing development of decentralized networks once again (even as the public cloud computing industry’s growth is expected to peak at 18 percent this year, before starting to taper off).


That kind of abstract shift is already showing up, unlocking experiences that could only exist with help from the edge. Hatch, a spinoff company from Angry Birds developer Rovio, has begun rolling out a subscription game streaming service that allows smartphone customers to instantly begin playing without waiting on downloads. The service offers low-latency multiplayer and social gaming features such as sharing gameplay via Twitch-style live-streaming. Hatch has been cagey about the technology it developed to slash the number of data-processing steps in streaming games, other than saying it eliminates the need for video compression and can do mobile game streaming at 60 frames per second. But when it came to figuring out how to transmit and receive all that data without latency wrecking the experience, Hatch teamed up with—guess who—Packet.


“We are one of the first consumer-facing use cases for edge computing,” says Juhani Honkala, founder and CEO of Hatch. “But I believe there will be other use cases that can benefit from low latency, such as AR/VR, self-driving cars, and robotics.”


Of course, most Hatch customers will not know or care about how those micro datacenters allow them to instantly play games with friends. The same blissful ignorance will likely surround most people who stream augmented-reality experiences on their smartphones while riding in self-driving cars 10 years from now. All of us will gradually come to expect new computer-driven experiences to be made available anywhere instantly—as if by magic. But in this case, magic is just another name for putting the right computer in the right place at the right time.


“There is so much more that people can do,” says Packet’s Smith, “than stare at their smartphones and wait for downloads to happen.” We want our computation now. And the edge is the way we’ll get it.

Article Source is From : https://www.wired.com/story/its-time-to-think-beyond-cloud-computing/

hulda echave asked this on Sep 14, 2017 Posted in Salesforce.com0 answers

AI for Customer Service: 4 Ways to Get Ahead of the Curve

AI for Customer Service: 4 Ways to Get Ahead of the Curve

Customer expectations have changed massively thanks to the internet. Instant gratification is simply expected as normal and it’s harder than ever for service to stand out. Meanwhile, significant growth in customer contact is also putting serious pressure on organisations to offer a prompt response.

It’s great that customers feel more connected to brands, but as we’ve come to expect instantaneous replies to queries, organisations are reaching their physical limits in terms of how much their human workforce can handle.

To deal with the demand for tailored 1-to-1 customer/company conversations, businesses are using AI. In fact, by 2020, Gartner predicts that 85% of customer interactions will be handled this way.

But when we talk about AI for customer service, we don’t just mean customer service bots replacing human agents. AI technology is also easing admin workloads – allowing representatives to focus on providing the human touch.

Here are four important ways AI is transforming how organisations communicate with their customers and manage increasing workloads.

1. Using AI for customer service helps solve small problems – before they grow 

Remember the last time you demanded to speak to a call handler’s supervisor? If only that escalated complaint could have been nipped in the bud early. That’s why AI is now helping organisations to deal with small issues early, before they become big ones.

If customers are provided with the means to contact a company with minimal effort, such as through a messenger window while they work instead of a phone call, they’re more likely to report minor concerns, rather than waiting until the problem can no longer be avoided. This can prevent issues from escalating beyond what’s necessary – improving brand satisfaction.

In turn, reducing the number of escalated complaints means human agents are under less pressure when it comes to getting to grips with more complicated cases. That’s good for brand satisfaction too: according to the Ombudsman Service, 75% of shoppers in the UK feel encouraged to make a repeat purchase if their complaint is well dealt with.

 
2. AI for customer service can improve your multichannel offering

Customers spend a lot of time on their smartphones, communicating through messaging apps. So if this is how your customers prefer to communicate, why wouldn’t you give them this option?

Messaging means talking to your customers on their terms, through their choice of application. But the Harvard Business Review says the biggest benefit is the ability for a brand to immediately understand the customer’s query in context – helping to provide quick, no-nonsense responses.

More organisations than ever are now allowing their customers to contact them this way, to good effect – research by Aberdeen Group suggests that companies with a strong omnichannel presence have on average an 89% customer retention rate.

The challenge is handling the resulting increase in customer contact. Automation can help, but only for basic enquiries – and that’s where AI for customer service can help. By using intelligent deep learning capabilities, AI can make decisions on whether to reply to a customer automatically – giving an instant response – or transfer them to a human agent if the enquiry is more involved.

 
3. Making self-service smarter – the rise of AI customer service bots 

AI customer service bots – whether on a website or a messaging app – allow customers to address their own issues instantaneously – without putting unnecessary pressure on contact centre teams.  

But it’s important that AI complements the human aspect of customer service.

A recent report from Accenture suggests that AI will dominate the way the big 3 banks in the UK interact with their customers – but it also notes that, even though customers are willing to embrace AI, they still want to be safe in the knowledge they can speak to a human.

And the great news is, bots are getting better at making that happen. Organisations gather more data from their customers, AI becomes more competent at diagnosing customer issues and offering first point resolution – allowing physical agents to optimise those human-to-human interactions.

 
4. AI can predict what your customer’s going to do next 

Good predictions about customers’ likely behaviour are among the most prized assets an organisation can get its hands on – because it means you’re ready to respond.

Whether it’s being able to predict stock demand based on the weather, or identifying problems before they affect customers, AI has the ability to make real-time decisions on a scale we’ve never seen before.

Customer issues are generally not unique. And if one customer is contacting customer service with a problem, it’s safe to assume there are more to follow. But it’s this repetition of issue cases that helps AI to learn and understand the common – but sometimes complex – reasons why customers interact with a brand, and the solutions that go with them.

This is where AI deep learning comes into its own. By linking up data silos across the organisation, companies can pinpoint customer issues and resolve them quickly.

And this will only get better with time. As organisations accrue more data on customers, their predictive accuracy will increase.

 
Introducing Service Cloud Einstein – Salesforce’s AI for customer service

There’s no doubt, great customer service still leaves a lasting impression – and AI has an increasing role to play in providing what your customers demand.  That’s why we’re excited to introduce Service Cloud Einstein:

Einstein Supervisor – empowering contact centre supervisors with real-time, omni-channel insights and AI-powered analytics to increase productivity and customer satisfaction Einstein Case Management – using machine learning for automatic case escalation and intelligent information gathering to save valuable time for agents
Intelligent Mobile Service – keeping your team in the field connected, providing personalised and exceptional service wherever they go.

To discover more about how AI can revolutionise your customer interactions, Follow Us & Like our Page @Solunusinc

This Article Source is From : https://www.salesforce.com/uk/blog/2017/08/ai-for-customer-service-4-ways-to-get-ahead-of-the-curve

hulda echave asked this on Sep 12, 2017 Posted in Salesforce.com0 answers

Stronger Security and Disaster Planning Fuel Healthcare's Migration to the Cloud

cloud computing platforms for healthcare

Stronger Security and Disaster Planning Fuel Healthcare's Migration to the Cloud


New  cost reductions make cloud options more compelling than ever but, in a  twist, experts say cloud platforms can be more secure than managed data  centers.


Healthcare did not lead the charge into the cloud.  But it has been making up for lost time. The use of cloud platforms has  grown substantially within healthcare provider organizations.


A recent HIMSS Analytics survey of provider C-suite executives found that more than half are using Infrastructure-as-a-Service (Iaas) cloud platforms to provide an environment for a wide range of uses ranging from hosting  internally developed programs to a running fully functional EHR.

HIPAA  privacy and security concerns were one reason for the slow start. But  once HHS provided clear guidance on how to address PHI issues and work  through Business Associate (BA) relationships, everything changed.

Today,  very few healthcare CIO’s consider security a reason to avoid the  cloud. Quite the opposite. The HIMSS Analytics survey found that  disaster preparedness is now one of the leading reasons why healthcare  CIO’s are making the decision to shift resources onto cloud platforms.  The savings are compelling. Why rent storage in a redundant data center  to maintain a fully functioning backup when you can pay for only what  you need in the cloud?

“You don't have to worry about your infrastructure and data center,”  said Jason Bickford, Applications Director of Health Information  Management Systems at Banner Health and president of the HIMSS Arizona  Chapter. “Cloud-based is the right way to go.”

Disaster recovery  in the cloud also has value as a stepping stone on the way to moving  production-level clinical applications into a cloud environment. The  logic is compelling. Once the backup clinical application has been  confirmed to be running smoothly in parallel, the cloud option has  proved itself reliable, so why not take advantage of the potential  savings?

That is not to say that security isn’t a priority. After  budget limitations, HIMSS Analytics survey respondents cited security  concerns as a reason to move slowly toward the cloud.

“Regardless  of whether a solution is hosted in your own data center or in the  cloud, security should be a critical factor in your review,” advises  Susan Snedaker, Director, IT Infrastructure & Operations at Tucson  Medical Center and author of the book IT Security Management. “There’s  nothing inherently more or less secure about a cloud option, but some  cloud-based solutions may not meet today’s stringent security  requirements.”

In selecting a cloud platform vendor, Snedaker  advises a careful review of the vendor’s documentation and contracts.  Pay attention to the provider’s security program and make sure that  audits take place on a regular basis.

“If your database is going  to be hosted on the same server as another database from another  company, what happens if the other database is attacked? Can the  attacker then gain access to your data?” Snedaker says. “Be sure to  understand the specifics of the hosting solution so you are clear about  your vulnerabilities. Then take steps to mitigate them – select a  different solution, select a different hosting model, ask the vendor to  modify policies, processes, procedures, access methods, etc. or accept  the risk if it cannot be overcome and there are no better options.”

Security  consultant Tod Ferran of Halock Security Labs has performed audits of  the large cloud platforms, Microsoft, Amazon and Google, and found the  services are maintaining a very high level of security. “In many ways,”  Ferran said, “the cloud is a better choice because many hospitals can’t  afford the staff to make their systems secure enough.”

As the  nature of risk has changed, so has the value equation. Strong security  means constant maintenance of operating systems and applications with  the healthcare enterprise. HIT managers can gain peace of mind from  knowing the updates are being performed by a vendor that is guaranteeing  round-the-clock support, rather than by a hospital staff already  stretched with aggressive internal project loads.

Many healthcare  providers use multiple cloud vendors, cherry picking among the  different options to align with specific demands of each application.

“Organizations  are not putting all their eggs in one basket,” said Sandra Yu, cloud  client executive at CDW. “It’s a multi-cloud world.” CDW partners with a  wide number of cloud hosts in providing managed cloud services ,  so Yu has experience with many vendors.

“If  you have needs for hyper computing, we would recommend a public  hyper-scalar for that,” she said. For PHI she would recommend a private  cloud.

When it comes to applications that have a heavy  computational workload, you need to be sensitive to the cloud’s latency  and so she would recommend a cloud data center that is geographically  closer. But for something that is not PHI-sensitive, she would recommend  a public cloud where the costs should be lower.

“The clinical  apps that can work well in the cloud are typically those that are not  transferring large files or data streams,” Snedaker says. “If you’re  going to host a data intensive clinical application in the cloud, you  should be sure you have the right connectivity solution in place.”

When  factoring in all of the reasons to move to the cloud, in the end, cost  is still a prime motivation. The savings are derived not only from  reducing the cost of maintaining data centers. The pricing for IaaS  continues to go down.

“It’s like a race to the bottom,” Yu said,  noting that when one of the major vendors lowers its price, the others  are quick to match it. Pricing among the leading public cloud vendors is  generally on par now, so decisions should be made after shopping for  the services and support that you’ll need. Pay as you go options are  readily available, so trials are simple to setup.
This Article Source  is From :  http://www.healthcareitnews.com/news/stronger-security-and-disaster-planning-fuel-healthcares-migration-cloud

katherine daisy asked this on Sep 6, 2017 Posted in Salesforce.com0 answers

7 things startups need to know about cybersecurity

Cyber security breach attack on monitor with binary code

It’s hard to imagine any business that doesn’t use any form of technology these days. The problem is, any computing infrastructure or equipment can be exposed to various methods of cyberattacks. Just last May, the WannaCry ransomware affected more than 10,000 organizations of all sizes in more than 150 countries. The attack caused stoppages in critical services and operations such as the UK’s National Health Service and several of Renault’s automotive manufacturing plants. Last year, one billion Yahoo users saw their accounts hacked, costing the company dearly.

While these reported ones were about large organizations, there were many anecdotal accounts of SMEs getting hit by the attack. Many of these smaller organizations are running on older systems and have little to no protection. Startups often get tied up with the more pressing parts of the business such as sales and operations that most often overlook security as part of your agenda. Here are 7 things entrepreneurs need to know about cybersecurity.

1. No such thing as too small

You may think that cybercriminals only target high profile organizations like the incidences we often hear and read about on the news. However, a Ponemon Institute study reports that 55 percent of SMEs experienced some form of cyberattack. If your business uses any computing device or the internet or has a digital presence such as a website or cloud accounts, then you are at risk of cyberattacks. Most attacks are now carried out by automated malicious software and scripts that seek out vulnerable computers and networks regardless of the size and nature of the organization.


According to cloud security provider Indusface, SMEs, which are more at-risk due to their limited experience with cybersecurity measures, are required to deal with today’s complex threats. Most small businesses have no dedicated IT staff that focuses on such things. This is why it’s important for startups to make security a shared responsibility across all members.

2. Threat 1: Data breaches

There are several common cyberattacks that you should be aware of. The first one is data breach. This is when cyber criminals seek to steal your company’s data by gaining access to your databases. Personal and financial information are sold on the black market for use in identity theft and fraud. Startups who have websites or apps that gather customer information such as ecommerce, online support, or CRM are prime targets for such attacks.

You may think that large organizations that have experienced data breaches such as Sony, Dropbox and LinkedIn survived the data breach fallout so you shouldn’t worry too much about such attacks. However, these major companies have resources and longstanding relationships to weather such issues. Startups don’t fare too well dealing with loss of customer trust and stained reputations. According to the U.S. National Cyber Security Alliance, 60 percent of small businesses fail within six months after suffering from such attacks.

3. Threat 2: Ransomware and malware

Security company Kaspersky identifies ransomware among the top cybersecurity threats to businesses today. Ransomware are a specific type of malware (malicious software) that infect computers (including mobile devices) over a vulnerable network. The ransomware encrypts files on the compromised computer. Users won’t be able to access the files unless they get a decryption key by paying ransom to the attackers. Even with paying the ransom, there’s no assurance that attackers will actually honor your payment.

Most ransomware attackers demand between $500 to $1,000 in exchange for your files. Some ransomware such as Jaff demand as much as $4,000. Ransom payments are often in cryptocurrencies like Bitcoin due to the anonymity these methods offer. The major impact to businesses isn’t exactly the ransom but the disruption to the business. Getting locked out of all your work files can halt your operations indefinitely.
4. Threat 3: DDoS attacks

Distributed denial-of-service attacks (DDoS) render your website or server inaccessible by overwhelming your network with traffic. An hour of downtime from a DDoS attack can cost up to $20,000 for a third of companies. For high transaction websites such as ecommerce services, this figure can be upwards $100,000 for every hour.

Small businesses are often left to weather the downtime and absorb lost sales and productivity. Even if not directly targeted, SMEs could still be affected by DDoS attacks on larger infrastructure providers. Last year, thousands of sites and services went down after a massive DDoS attack hit DNS provider Dyn.

5. People are often the weakest link

People are often the weakest link in a security chain. A BakerHostetler report found that most security breaches are caused by human lapses. Many systems are left vulnerable to data breaches and ransomware attacks through phishing where people are tricked into clicking on links and installing malware.

Some can even bring these threats into your infrastructure by carelessly plugging in their own phones, notebooks, and storage devices to your network and computers. Educating yourself and your staff on the best day-to-day security practices would be a worthwhile investment to prevent attacks caused by human error. Have security policies in place that would govern how you and your staff should be using your IT resources.

6. Access control counts

Know to whom you’re giving infrastructure access. As a startup, you may be unnecessarily handing out critical infrastructure access to just about anyone like that freelancer you hired to build and maintain your page may still have access to your servers or the guy you let go last week may still have the passcode to void transactions on your POS system.

Today, most administration tools and services allow you to set user roles with corresponding levels of access so that you can control who gets to do what on your infrastructure. Encourage people to use strong passwords and protect them at all times. Revoke access of anyone not working for your company as soon as they go. Cover yourself legally as well by putting in nondisclosure clauses to prevent them from leaking passwords on agreements with people you involve in the business.

7. Invest on security

As a startup, you may be averse to take on added expenses. However, cybersecurity is just one of the IT investments you have to make. Besides, there are cost-effective anti-malware and security software that you can use for your office computers.

In addition, security-as-a-service is now a thing which means you don’t have to make heavy upfront investments on security applications and appliances to protect your network. Instead, you can subscribe to scalable security services such as web application firewalls and DDoS mitigation services for your online infrastructure and applications. Startup cyber security is just among the many realities IT professionals must focus on. Know the risks and put up programs in place that would help you avoid getting hit by cyberattacks down the line.


This Article Source is From : http://www.cio.com/article/3201744/data-protection/7-things-startups-need-to-know-about-cybersecurity.html

kishan cv asked this on Aug 23, 2017 Posted in Salesforce.com0 answers

Salesforce Service Cloud Update Provides New Tools for Service Agents

The latest update to Salesforce Service Cloud is designed to help service agents offer better, mobile customer service and is more customizable.


Salesforce.com has announced the “next generation” of its Service Cloud platform that has been redesigned with new features as well as improvements for easier application setup and management.


Service agents can manage and resolve customer issues regardless of whether they are on the road, at the home office or at a customer's site using the new native Service Cloud mobile app for iOS and Android that are due for release later this year.


Salesforce customers can also extend Services Cloud functionality with additional apps available from the Salesforce AppExchange or they can customize the platform with Lightning Builder.


Lightning Components can be added simply by dragging and dropping them to Service Cloud. Currently-available Service Cloud apps include several with telephony and call center management features from Dialpad, NewVoiceMedia and Talkdesk; internet of things asset tracking and mapping from MapAnythingLive, and patient and healthcare provider communications from Healthwise.


On the management front, Salesforce has added new capabilities to the Lightning Service Console including the “Case Kanban” visual dashboard that shows cases in the queue to help service agents prioritize their time.


Another component, Community Agent 360 shows a customer’s community history giving the agent some context about recent customer activities, such as a recent support article the customer may have read so the agent doesn’t repeat information or suggest a fix the customer has already tried.
A Federated Search feature lets agents find relevant information across Salesforce and external data sources such as Confluence, YouTube, Dropbox and Box.


There is also a Macro Builder capability that helps agents quickly create reusable macros for specific customer service scenarios. Agents can then easily deploy that macro if the issue comes up again.
As a measure of how easy it is to set up, Salesforce asserts that companies of any size can use Service Cloud to build a feature rich customer service center in a day or less.


“Any company, large, medium and small, can be empowered to deliver personalized service experiences in less than a day with clicks, not code,” Keith Pearce, vice president of marketing for Service Cloud at Salesforce, told eWEEK.


Features such as case management are now built-in to Service Cloud. In as little as five steps, service administrators can add a customer community and knowledge base, as well as connect to email, Facebook and Twitter feeds, according to Pearce.


“We’ve set up service flows for Twitter and Facebook and it takes all the learnings from similar cases the agent can get to" in just a few clicks, said Pearce.


For additional features and customization, Salesforce offers Trailhead, its online, gamified training platform, with more than twenty free, guided modules to learn how to deploy, configure and customize Service Cloud.


“The new cloud-based deployment and management features Salesforce has added to its Service Cloud are designed to address core issues of concern to its business clients,” Charles King, principal analyst at Pund-IT, told eWEEK in an email.


“Central to that is the evolution of digitally-enabled, proactive customers with access to powerful communications technologies and platforms to highlight unusual experiences and share their feelings," King said.


Proactive customers with access to social media and other web communications will often freely vent their frustration with service providers that perform poorly, King noted.


"Anyone who doubts that their business or brand might suffer from this often unconstrained venting hasn't been paying attention to the news. The new Salesforce offerings aim to help clients address these issues with next gen service cloud solutions that are quick to deploy, simple to learn and easily managed,” he said.


The Salesforce Service Out-of-the-Box, Lightning App Builder for Service, Lightning Service Console, Federated Search and Case Kanban view are available today at no additional cost with any edition of Service Cloud.


A pilot edition of Community Agent 360 is available today at no additional cost with a Customer Community Cloud license. A beta version of Macro Builder is available now at no additional cost with any edition of Service Cloud. Salesforce said it plans to make a pilot version of the Service Cloud Mobile app for iOS and Android available in the second half of 2017 with any edition of Service Cloud.

This Article Source is From : http://www.eweek.com/cloud/salesforce-service-cloud-update-provides-new-tools-for-service-agents

hulda echave asked this on Aug 14, 2017 Posted in Salesforce.com0 answers

Fix Your Databases now as You Migrate to the Cloud

If you have lame databases in your on-premises systems, don’t move them to the cloud. They’ll still be lame databases.

As thousands of enterprises move their application workloads and data to the cloud, too many move whatever they have, include their lame databases. It’s easy to just lift and shift them you’ll find the popular on-premises databases also available in the cloud. So you end up with the same limitations, just running somewhere new.

Don’t do that. Instead, reevaluate the type, and the brand of databases you’re using as part of your cloud migration.

[ The RDBMS is scaling out: Review: Google Cloud Spanner takes SQL to NoSQL scale. | MySQL face-off: Amazon Aurora outscales Google Cloud SQL. | Review: ClustrixDB scales out — way out | Review: DeepSQL outruns Amazon Aurora | Keep up with hot topics in programming with InfoWorld's App Dev Report newsletter. ]


Use the cloud migration effort to vastly improve your data management and data use capabilities. For example, consider moving from SQL or relational databases to NoSQL or object-based databases, which maybe a better fit for your patterns of data use.

Yes, that means the database must be redesigned, reformatted, and transformed. Fortunately, there are many tools for the job, and most can make short work of it.

Too many enterprises treat their data like a graveyard, sacred and never to be disturbed.   I’ve found that trying to get the people charged with the data to think about changing anything is an all but impossible task. I get it: The public cloud is scary enough. Changing the database engine too is unthinkable.

But, let me make my case. If you’re moving the data anyway, it’s much cheaper to make the changes now, including changes to the applications that produce and consume the data, than it is to put the data on the cloud and change it later.

Remember: You only need to go though a single test and acceptance process, versus two, if you do it as part of your cloud migration effort. And did I mention that there are already best practices and tools to make the transformation easy?

I understand that it takes money, time, risk, and all that translates into fear. I’ve been told that smart enterprise IT employees learn to keep their heads down for survival. But that’s not smart.

Data is still king. Limitations that many enterprises have accepted over the years have lead to limitations in the business itself. Why limit your business when you can fix it now?

So, fix your databases now as you migrate them to the cloud.


This Article Source is from : http://www.infoworld.com/article/3213171/database/fix-your-databases-now-as-you-migrate-to-the-cloud.html

hulda echave asked this on Aug 11, 2017 Posted in Salesforce.com0 answers

From Public Cloud to Hybrid IT – Straight From the Horse’s Mouth

cloud horses mouth image

People who bet on horse races know that the most reliable information about a horse will come from those who are closest to that horse -- a trainer or someone working in the stable. The idiom, straight from the horse’s mouth, implies that someone has gotten even better information – a tip from the horse itself!


Over the past two months, I’ve been writing articles about common public cloud concerns and why hybrid IT gives you the right mix of public cloud, private cloud, and on-premises solutions. Of course, I don’t expect you to take my word for it. But maybe you will take advice from those who tried public cloud and have since moved to hybrid IT.


In this article, I’ve complied a few quotes from a variety of organizations of all sizes and industries. Each has experienced public cloud and now has moved to hybrid IT. So here you go – advice that is straight from the horse’s mouth:


Public cloud performance issues

“We’re moving some of our web infrastructure workloads back to our own data center. Performance was the big issue. Lack of communication from our public cloud provider led to a customer-facing outage we could not have prevented. Now we’re seriously rethinking our entire cloud strategy and are moving more workloads back on-prem.” – Social media company


“We’re bringing back apps that we had put on the public cloud and didn’t go as planned because of reduced performance when compared to … when they were on-prem. That said, there are other apps we feel are truly more cloud-ready, and we’re trying those out in the cloud so we can have what we deem to be a truly hybrid solution.” – Financial Services company


Public cloud cost concerns

“We opted to be bleeding-edge and move to cloud when storage and hypervisor license costs were on the climb. It seemed to be a better way to keep costs in an opex mode and know what they were. That worked slightly at first. … We used a lot of IaaS and SaaS within AWS. … As we grew, the usage did too … and the bills grew far faster. … We honestly reached a tipping point when billing started to approach $100,000 per month. … We had good financial outcomes moving on-prem with a hybrid solution so we can access cloud when we choose. … We now have two times the horsepower on-prem for half the cost.” – Social Media company


“One of the biggest issues driving declouding for us is that, to be honest, the initial move to the public cloud was done willy-nilly. We moved the workloads and then we moved the apps to run off those workloads. But we didn’t really think about how to stage properly, how to control usage costs, and how to design an exit strategy. We quickly learned that cloud costs were far higher than we expected.” – Retail company


Public cloud control concerns


“Flexibility is important. With a private cloud, we get the control and flexibility of a dedicated environment that’s tailor-made to address our specific IT needs. For fast-growing companies like ours with constantly changing requirements, a private cloud offers more flexibility to adapt and evolve as the company changes.” – Social Media company


“The data we hosted on AWS was growing exponentially, as all data does, and that increased costs. Public cloud hosting served its purpose when we entered the all-cloud (for the most part) approach, but then you hit this point where it doesn’t make financial or operational sense any longer, when the same thing can be accomplished on-prem for less money and less hassle. … Having the workloads back on-site gave us better control over usage, and we could better see spikes in activity.” – Public Sector company

The benefits of Hybrid IT

Many businesses have already started to move beyond the public cloud – into a new era of hybrid IT that combines public cloud, private cloud and traditional IT. New offerings such as hyperconverged and composable infrastructure offer cloud-like capabilities on-premises – solutions that can provide businesses more control, greater performance, less cost, and less risk than many public cloud options. A combination of on-premises, software-defined options within a private cloud seamlessly combined with public cloud lets businesses build the best possible infrastructure for their individual workloads.

“The lower cost of storage, servers, and even better servers that require less hypervisor licenses made it less costly than it once was to scale out a data center or private cloud on-site.” – Energy company
Organizations all over the world are taking a closer look at their applications and deciding which ones should be in the public cloud and which ones should remain on traditional IT or a private cloud. Although performance, cost and control issues are all relevant, you should also consider the business model of each workload in your decision.

HPE has assembled an array of resources to help you transition to a brand-new hybrid IT world. You can learn more about HPE composable infrastructure powered by Intel® by reading the e-book, HPE Synergy for Dummies, or learn about HPE’s approach to hybrid cloud by checking out the HPE website, Project New Hybrid IT Stack. And to find out how HPE can help you determine a workload placement strategy that meets your service level agreements, visit HPE Pointnext.


This Article Source is From : http://www.infoworld.com/article/3212833/data-center/from-public-cloud-to-hybrid-it-straight-from-the-horse-s-mouth.html

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How the Internet of Things Can Be Good for Small Businesses

Every business and technologically-oriented person has heard of the Internet of Things (IoT) by now, and how small devices will do things we never thought were possible. The Internet of Things has been closely linked with the rise of the smart home, where someone could ideally jumpstart their coffee maker and lights from their smartphone.

The real growth of the Internet of Things will occur with businesses, where it can work together with big data to make things more efficient. A basic example of the Internet of Things comes from British Petroleum, which for years has distributed thousands of wearables as part of its corporate wellness program to have a better idea of their employees' health and thus reduce health insurance costs. Small businesses stand to be the biggest beneficiary of the IoT, as it will let them catch up with many of the advantages which a large corporation have dominated until now.

Here are some of the advantages which the Internet of Things can offer any business, as well as how to prepare your business for this technological revolution.

The Power of Data

Analysts have been talking about big data even more than the IoT, but so many businesses seem to think that big data is for big businesses who can afford huge amounts of servers. The Internet of Things will change that.

IoT is fundamentally about the idea that all sorts of objects which you would have never thought of connecting to the Internet 10 or 20 years ago like watches or refrigerators or lights can now be connected. But the most important thing about this is that through these connections, each and every one of these devices will emit data which can be used to improve a business's efficiency.

Take those aforementioned smart lights for example. Many businesses and reporters have pointed out how the Internet of Things could use smart lights and data to improve energy efficiency by gathering data on how much heating, cooling, and lights are needed at any particular moment. Data about energy usage once had to be done by a maintenance worker checking the amount of power consumed once a month. Now it can be done in real time. And most importantly for small business, it requires sensors and devices which anyone can get their hands on.

Of course, small businesses will have to confront the challenge of storing mountains of data produced by the Internet of Things, which some experts predict will reach 600 zettabytes or 600 trillion gigabytes by 2020. Fortunately, small businesses can adjust to this explosion of data by migrating away from traditional data servers and embracing the cloud.

Read more about cloud storage and remote workers at TechCo

Innovation and Creative Thinking

Data in and of itself is useless if a small business leader cannot come up with creative solutions to leverage the information.

As an example Inc. talks about the Aquaco fish farm as to how a small business can use the IoT to improve their business. Aquaco uses the data gathered by sensors placed in tiny recording devices to regulate feeding, monitor oxygen levels and other environmental factors to alert them in advance of when things might be going on, and continually looks for new, efficient means to use the data gathered by their sensors.

Another example of IoT benefits include customer service. As noted above, some businesses like Aquaco use IoT sensors to detect when a device is about to fail or reaching dangerous parameters. But if a business put their sensors in a device they sell to customers, they could tell the customers when said device is about to fail and offer a replacement. While customer service in the past looks to fix a customer's problems, customer service with the IoT could head off those problems before they become serious. By rewarding innovation and creativity, the IoT will thus reward small businesses who can more quickly and efficiently carry out new ideas and concepts.

The IoT for many has been an esoteric concept where a lot of technology is hyped out but nothing actually changes in our normal lives. But as engines of innovation and practically, small businesses are the vehicle that can truly bring the IoT to its full potential, as they use the data gathered to come up with far more solutions and changes than larger corporations can.

The Internet of Things is a continual process where additional data leads to solutions which encourages the spread of data which leads to further solutions. Small businesses will find the solutions to problems which we do not even know are problems today.

Source is From : https://tech.co/iot-small-business-big-data-2017-07#.WWUhkJVDqD4.twitter

hulda echave asked this on Jul 18, 2017 Posted in Salesforce.com0 answers

Why Serverless Cloud Solutions Will Reduce IT Costs


The public cloud computing sector is in a constant state of evolution, as vendors design new IT infrastructure architectures and service providers deploy them in their own unique hyperscale data centre facilities.

According to the latest analysis of cloud pricing by 451 Research, for the majority of new applications, a serverless solution offers a lower total cost of ownership (TCO) than both virtual machines (VMs) or containers.

Severless cloud market development

When analyzing serverless offerings from the leading public cloud service providers, 451 Research determined that IBM generally offers the least expensive service, with Microsoft leading for certain other configurations.

According to the 451 Research assessment, the TCO of serverless tends to be lower than VMs, even when the VM is hosting containers, because there is no need for developers to provision, configure and manage the infrastructure.

As an example, when a serverless function is active for just three quarters of the month, it only takes a 10-minute saving in operational overhead for serverless to beat virtual machines on TCO.

451 Research analysts believe that even without the savings in developer time, the ability of serverless to increase utilisation means it is cheaper than using VMs when the code is executed fewer than 500,000 times each month.

451 Research finds that IBM is least expensive for 0.1 second duration scripts, and Azure is cheapest for 10-second scripts - assuming memory requirements match predetermined size allocations.

Besides, IBM offers a distinct cost advantage by allowing users to choose exact memory requirements, whereas other cloud service providers round up the figures, resulting in users typically paying for unused capacity.

That being said, and considering the similarities in pricing methods and offerings between cloud service providers, 451 Research believes serverless is poised to undergo a round of price cutting this year.

"Serverless is more than just hype; it has the potential to transform the way we develop, build and run applications in the cloud. Understanding the economics of serverless technology is vital to understanding its potential to disrupt the industry," said Owen Rogers, research director at 451 Research.

Outlook for serverless cloud services

Freemium serverless offerings are already fueling the growth of new services by stimulating experimentation and helping enterprises gain skills. In the analyst's opinion, this could result in serverless solutions becoming the next cloud 'price war' battleground.

451 Research expects adoption of serverless - or FaaS (functions as a service) - to continue growing over the next few years. In its 2016 market study, 37 percent of the IT decision-makers surveyed were already using serverless technology.

The term 'serverless' implies that no servers are used to run an application or service. But in reality, this model means that developers and cloud service providers do not encounter the typical complexity and maintenance management of VMs or containers.

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Article Source is From : https://www.cloudcomputing-news.net/news/2017/jul/10/why-serverless-cloud-solutions-will-reduce-it-costs/

katherine daisy asked this on Jul 13, 2017 Posted in Salesforce.com0 answers

The Changing Face of Security in the Age of The Cloud

The computing world just keeps on progressing but as we all know with  progress comes additional challenges. This is especially true of  challenges around security. Every advance in computing has given rise to  the same question: “how do we secure this new toy?”

When client/server architecture was all the rage in the late 1990s  there was great excitement about the advantages it brought about but  also a concern for the security implications of distributed clients and  centralised servers. When server consolidation came of age in the early  2000s the concern was how to keep applications secure when running on  the same server.

In the age of cloud computing,  we seem to have introduced more security impacts than ever before.  Cloud computing has been the basis for many tremendous benefits in the  computing industry and has positively impacted many businesses around  the world. While we can celebrate all the advances we need to be very  aware of all the new threats that have come with the steps forward. The  following are some of the areas that concern security professionals in  the 2017:

Cloud

As I have stated in a past article, security concerns are still the number one impediment to cloud adoption in the computing world today. With that said, more and more  organisations are moving production workloads to the cloud every day and  how to secure those workloads is a question with no single answer.  Whether cloud workloads are treated as if they are in one's own data  centre or secured through as-a-service tools, placing workloads into the  cloud comes with some measure of uncertainty that requires research,  planning, and execution to mitigate.

Edge/fog networks

The concept behind fog computing isn’t really all that new. I  remember moving web servers to the outer edge of the network, outside  the firewall, so that they can be closer to the users. The difference  now is that fog computing supports larger numbers of devices either at  the edge of the managed network or, in the case of IoT, placed  physically very far from the control plane.

The somewhat obvious threat vector is the vulnerability of these  fog/edge to attack and the continuation of that attack to the control  plane, aggregation layer or even all the way to the virtual private  network or data centre. This needs to be dealt with in much the same way  as this type of problem was handled in past. The fog/edge devices need  to be hardened and the communications path between those devices and the  aggregation layer and the data centre (cloud or other) need to be  secured.

Mobile users

It was so much easier to secure an environment when we knew who our  user base was. Well, not anymore. The preponderance of mobile devices  that the service developers can have no control over, leaves the service  network open to attack via those devices. A user who utilises your  provided tested and secured app could easily have installed another app  which is just a front for malware of some kind. Beyond just writing apps  that are secure the systems as the front end of the data centre or  cloud environment that support these apps have to be strongly secured.  Additionally, communications between app and service layer need to be  secured and monitored.  

Malware

On June 26 the largest container shipping company in the world Maersk  Lines, Russian oil producer Rosneft, and pharmaceutical giant Merck,  along with hundreds of other institutions around the world, were all but  shut down by a global malware/ransomware attack.

That the perpetrators used various public cloud-based resources to launch the attack is a very real possibility. Security professionals  around the globe are concerned about the form the next big malware,  virus, or ransomware attack will take. Practical and logical steps,  including planning for recovery, training, and maintenance, need to be  taken to prevent organisations from falling prey to these attacks.

Global data expansion

Many years ago, I wrote an article on how server consolidation can  positively impact data centre security by reducing the number of  operating system instance to maintain and by reducing the number of  possible targets for hackers. In today's ever expanding global data  environment we have to ask ourselves: have we provided too many targets  for the bad guys?

The answer is maybe. Each individual and organisation have to be  engaged in preventing data loss and data theft by utilising the many  means of securing data that exist today. Data at rest encryption,  automated and versioned replication or version backup, are just some of  the ways an enterprise can protect themselves. These security concepts  apply equally to preventing and/or recovering from malware attacks.

The only way to survive the many security threats that exist is  to: recognise the threats, learn about them and how to fight them; build  a comprehensive plan for protecting your organisation and for reaction  to and recovery from an attack; whether it is basic security maintenance  or implementation of major security efforts, take action. Don’t just  sit back and wait for an attack to happen.

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Article Source is From : https://www.cloudcomputing-news.net/news/2017/jul/10/changing-face-security-age-cloud/

Kishan Chakravarthy asked this on Jul 12, 2017 Posted in Salesforce.com0 answers