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Around the World With Windows Store Apps

REDMOND, Wash. – Feb. 26, 2013 – This week, thousands have descended upon Barcelona, Spain, for Mobile World Congress, the world’s premier mobile industry event. In honor of this international gathering, we’re celebrating Windows Store apps from around the world, along with stories of the people working behind the scenes to bring those apps to life on Windows 8.

‘Most Verbose’: Meet Microsoft's Original MVP

REDMOND, Wash. – Feb. 21, 2013 – It's 1993, and you need technical support. Who you gonna call?

Most techies at the time would plug in their modems and dial up CompuServe. In the days before Twitter, Facebook and broadband, CompuServe's forums were a gathering place for geeks to talk shop and get answers to burning questions.

Calvin Hsia
Calvin Hsia
February 21, 2013
Calvin Hsia, pictured here with his son Tyler, started Microsoft’s MVP program 20 years ago as a simple list of “most verbose” people on a forum.
Web | Print

Calvin Hsia, a developer who lived in Hawaii, thought it might be fun to figure out who posted the most. So he wrote a program that could download, organize and tabulate hundreds of daily forum messages. He then published a list of hundreds of the forum's "Most Verbose People," as he liked to call them.

Microsoft saw value in that verbosity, so much so that the members of "Calvin's List," along with its creator, became Microsoft's first Most Valuable Professionals (MVPs).

As part of the launch of the program, the MVP Award was created in 1993 to thank exceptional, independent community leaders who — often verbosely — share their passion, technical expertise and real-world knowledge of Microsoft products with others. This week, as Microsoft celebrates the 20th anniversary of the MVP Award, the original group of 34 award winners has swelled a hundredfold. Hsia was among the attendees who honored the milestone at this week's MVP Global Summit, not as an award recipient — he became a Microsoft employee 19 years ago — but as a supporter.

"Our MVPs are incredibly important to the company," said Hsia, a senior software development engineer (SDE) on Microsoft’s Visual Studio team. "They help our customers, they act as beta testers and they give us honest feedback. They're huge for us."

He isn't the only fan. Microsoft CEO Steve Ballmer also expressed his gratitude for the community's longstanding passion.

"For 20 years, the insight and feedback from the MVP community has helped drive and shape Microsoft's product advancements," Ballmer says. "The contributions that MVPs make to technical communities is invaluable, and I deeply appreciate their passion as well as all that they do for our customers."

This year Microsoft honored 3,800 MVPs across 90 Microsoft technologies. Every day, MVPs reach 1 million customers through social media, in forums, at user group gatherings and as presenters at technology conferences around the world.

That reach makes them the company's "best buddies," says S. Somasegar, corporate vice president of Microsoft’s Developer Division.

"These are our best and most passionate customers, those who take it upon themselves to learn about everything we're doing, to provide invaluable feedback and to then help the rest of the world discover and make the most of our technologies,” he says. “I view our MVPs as ambassadors to the technologies and work that we do at Microsoft."

A Dev in Paradise

Hsia didn't need much to create his original MVP list — just a little code and a dial-up connection via his blisteringly fast (and much bigger than a bread box) US$549 2400 baud modem.

That code helped Hsia stay on top of the 700-plus daily messages posted on the forum for FoxPro, the database program at the heart of his consulting business. At the time, Hsia mostly stayed away from Microsoft products. But after the company began publishing FoxPro, he changed his tune. The company was pouring a lot of resources into improving the database, and Hsia took notice.

Meanwhile, the MVP Award helped him gain a reputation as a FoxPro whiz. If someone posted a question on CompuServe's forums, Hsia usually had an answer.

That technical expertise attracted attention in Redmond. One day Hsia got a question from a senior Microsoft executive: did he want a job at Microsoft? He handed the phone to "the boss" — aka his wife — who listened for 30 seconds, said "No thanks," and hung up.

"We live in Hawaii!" she said.

The young couple eventually changed their minds and made the move to the Seattle area. Hsia became an SDE working on FoxPro. He continued to maintain “Calvin's List,” but the conversation soon drifted from CompuServe to other forums and websites. Today, he ranks the top MSDN and TechNet blogs.

Hsia also stayed in touch with the MVP community, listening to their feedback about the various products he worked on throughout his career. They really are Microsoft's most valuable — and verbose — external community, he says, and over the years they have played a big part in changing public perception of "big, bad Microsoft" among customers.

"Our MVPs — they're out there trying to help our customers every day,” Hsia says. “And in doing that, they really help us."

Hsia himself perhaps best articulated the value and spirit of MVPs 20 years ago, when CompuServe Magazine profiled him shortly after winning his award: "I know how difficult it is for an independent developer to see all angles to a problem, and I know how nice it is to receive a reply with a solution. It's extremely gratifying to know that I've helped solve somebody's problem."

A ‘Golden Era’ of Insight: Big Data’s Bright Future

REDMOND, Wash. – Feb. 15, 2013 – At Microsoft Research labs around the world, some very deep thinkers are contemplating big data.

Eric Horvitz
Eric Horvitz
February 14, 2013
Eric Horvitz, distinguished scientist at Microsoft and co-director of Microsoft Research’s Redmond lab.

This includes Eric Horvitz, distinguished scientist at Microsoft and co-director of Microsoft Research’s Redmond lab, who was recently elected to the National Academy of Engineering for his work in “computational mechanisms for decision making under uncertainty and with bounded resources.”

He sees a future where machines, fueled by large amounts of data, can become “empowering, lifelong digital companions” who know what you want or need (be it pizza or medicine), where you want to go (be it Hawaii or the most traffic-free route to the ball game) and generally work with a passion on your behalf.

Capturing data, storing it, interpreting it, and leveraging it can provide insights on small and large scales, and in high-tech and mainstream fields alike, Horvitz said.

“In today’s world, effective large-scale data analytics for predictive modeling, visualization, and discovery are becoming central for success in many areas.”

Microsoft News Center recently spoke to Horvitz about how Microsoft Research (MSR) is investing time and talent in the area of big data and machine intelligence, what breakthroughs MSR has made, and his vision for the future of these fields.

MNC: Why do you think there is such a buzz around big data right now?

Horvitz: Buzzwords arise for variety of reasons. In this case, I believe a confluence of several factors led to the popular use of that catchy phrase. One is the data that’s being collected in unprecedented quantities now on a variety of fronts, and advances in computer science – in sensing, storage and networking. Large amounts of data are being collected in part because of the shift of many human activities to the Web – and that has made it easy to collect transactions and events of various kinds in stream with activities. This includes everything from e-commerce to cars driving over sensors in roads to smartphone services leveraging location data, to healthcare. In healthcare, the explosion of genomics and the increasing capture of clinical data in hospitals has brought gigabytes and terabytes of patient data into databases – and we are in the early days of biomedical informatics. Storage also has become very inexpensive compared to what it used to be. We used to talk about maybe one day having terabytes of data. Now terabytes are something your kids can carry on a small drive in their pocket as they go to middle school. On the computational side, there have been advances with computational procedures we use to harness data for multiple interesting uses – such as building predictive models from data. As examples, we can leverage data to make real-time predictions about a computer user’s changing intentions or interests and learn to recognize someone’s gestures. We can learn from patient data to predict the likelihood that a patient will be readmitted after their discharge from a hospital.

MNC: What makes Microsoft Research’s machine learning research unique from others in the field?

Horvitz: Microsoft Research is well known as an open research lab where we promote research freedom to publish on our results and advances. That has attracted the best and the brightest people. Folks at MSR are energized by a stream of interesting real-world challenges. They also have access to large data resources – and the tantalizing opportunity to get one’s best ideas into into the hands of hundreds of millions of people. Our researchers investigating machine learning are very much part of the larger community of researchers worldwide pursuing studies in machine intelligence. Beyond machine learning, this reseach includes machine perception, automated reasoning and decision making. Machine learning runs deep in the DNA of Microsoft Research; the area of work was one of a few early critical priority areas that we invested in.

Today, people doing machine learning research across our labs are a substantial intellectual force. This includes teams of deep thinkers working on core principles as well as applications. We have teams of folks doing machine learning in Redmond, Cambridge, Beijing, Bangalore, Silicon Valley, New England and New York City. Together, these groups form one of the largest machine learning efforts in the world.

MNC: What are some ways that MSR machine learning research has found its way into Microsoft products?

Horvitz: Numerous effort s have found their way into Microsoft products and services. Many of these successes stem from very close collaborations between people at MSR and folks on the product teams. As one example, Microsoft Research did the core work on learning how to rank items. This work led to Bing’s core methods for ranking search results in response to user queries. MSR is also well-known for is its work in vision systems – machines that can see and recognize what they’re seeing – as well as speech recognition and translation. When you use Bing voice search or Bing translator, you’re leveraging core MSR machine learning efforts.

Our Cambridge team is well known for methods that learn to understand how to take an image and to segment and categorize it; this valuable and innovative work was a critical enabler for the Kinect, which can identify people and their gestures in a room.

MSR is also known for applying machine learning research in the field of biomedical informatics and other aspects of clinical healthcare. In the Redmond lab, we’ve had major efforts in harnessing and utilizing the large quantities of clinical data coming out of hospitals now to build predictive models for guiding decision-making in hospitals. These systems are at work as I speak, in hospitals around enhancing healthcare. Another application is Bing Maps and Bing Directions, which provides traffic-sensitive directions for 72 cities in North America. Bing Directions uses methods from MSR that showed how we can learn from histories of traffic data how to predict real-time flows on all streets in a greater city region. Machine learning even occurs deep in the Windows operating system. MSR teamed with Windows to develop a real-time prefetching system that runs in Windows 7 and Windows 8. Windows continues to learn from users about their patterns of activity and then makes predictions about next actions – making the operating system even faster.

MNC: What are some goals of this extensive machine intelligence research?

Horvitz: The directions and goals are broad, from explorations of the basic science of machine learning to understanding how to best solve particular classes of data and perform specific tasks. We also explore the development of more efficient and powerful tools to support the engineering practice of machine learning. On this front, we’ve been exploring the development of tools and methods that let non-experts or or semi-experts do a great job with their own predictive modeling and data analytics. This is a very, very interesting challenge – to put the power in the hands of end users – typically, this kind of analytical power has only been in the hands of machine learning experts and statisticians .

MNC: That sounds like an immense challenge. Where do you start in trying to make machine intelligence available to the masses?

Horvitz: In machine learning, numerous algorithmic procedures have been developed; each typically comes with levers and knobs for tuning the methods to the data and task at hand. Questions arise about which method is best to use for a particular dataset and learning task. There are also challenges with cleaning, preparing and anonymizing raw data so it can be easily processed and analyzed. There are multiple danger zones in machine learning, and new kinds of tools can help people to specify what it is they want to learn and how to validate the accuracy of the predictions made by the models that they build. Then there’s decision making. This centers on how to guide actions and policies in the world based on predictions. We’re working to create new kinds of tools that guide data collection, analysis and testing – and that also provide end users with insights about visualization and decision making.

MNC: What are some of the other hurdles in the world of machine learning?

Horvitz: One challenge that we’ve been taking on is machines that can understand and even translate conversational speech. Sometimes small gains in accuracy have big implications for the competency of a system. Recently, (MSR Chief Research Officer) Rick Rashid demonstrated in front of a large audience in Tianjin, China, the ability to do real-time translation from English to Mandarin Chinese. He was talking freely and having his speech translated and then re-rendered in his own voice – he was speaking Mandarin in real time. That translation pipeline was enabled by several technologies, but in some ways the most salient and surprising innovation was a surprising increase in the accuracy of speech recognition for conversational speech. That’s just happened in the last couple of years, and was the result of research and experimentation at MSR on new directions in machine learning.

MNC: So what aspects of big data will Microsoft Research focus on?

Horvitz: There are so many fun and promising directions. I have to say, it’s really an exciting opportunity area – and we’re at an exciting time. Looking out at the longer-term future, I expect that machine learning, and machine intelligence more broadly, is going to provide us with foundational new tools for doing scientific research, and that many breakthroughs over the next few decades will come as a collaboration between people and the machine learning and reasoning tools. There are opportunities to learn new things from large amounts of data, including getting to the bottom of healthcare mysteries by going through data with automated learning tools – some of which can recognize causality, that A actually causes B.

Another direction is working to weave together a set of technologies – machine learning, speech recognition, natural language understanding, machine vision and decision making – to create systems that act like bright collaborators and that complement human intellect in new kinds of ways.

On another front, there’s a great deal of opportunity to do new kinds of search and retrieval on the Web. We’re also applying machine learning in new ways to pick out signals in large amounts of population data. For example, in recent work, we’ve developed a way to discover clues about medication side effects in anonymized search logs. I believe that data-centric methods will change the world in so many ways, with influences on health, education, science and commerce.

MNC: If you were to get a bit Jules Verne, what could all of this research mean for the future?

Horvitz: Looking out to the future, I believe that there’s an opportunity to build systems that really become empowering, lifelong digital companions that deeply understand what it is you want to do, where you want to go, what you want to learn, what you need to do to stay healthy, what your good and less good at, and that continue to work on your behalf to assist and to complement you. Work on several fronts is already providing some foreshadowing wisps of wider possibilities.

MNC: Why did you get into this field?

Horvitz: I have long been interested in understanding the human mind and my curiosity led me from biology to physics to the world of information and computation. Beyond that core pursuit, I’ve come to be excited over the years with applying principles of learning and decision making in real-world applications that provide value – while somehow being related to the big questions about thinking systems. I’ve had a blast working with and alongside fabulous colleagues on principles and applications. And at a place like Microsoft Research, we all have this tantalizing “lever” in mind – with a fulcrum at the horizon. Our next innovation or idea could really move the planet, via having an influence on Microsoft’s products and services.

MNC: All in a day’s work, huh?

Horvitz: [Laughing] Exactly. But I’m serious about this, we’re not kidding around.

MNC: The Harvard Business Review has declared the data scientist the new sexiest job.

Horvitz: That’s great. You might say that, in some ways, computer science and other engineering fields have suffered over the years in that people making career choices had been looking for “noble endeavors” – in fields like healthcare and law. I believe that the computational sciences are becoming the noble endeavors of our time, because computing enables so many other things from aerospace to healthcare to science to law to government.

Editor’s note – Feb. 15, 2013 – Several updates were made post publication.

Big Data + Great Western Bank = Triumph in a Time of Austerity

REDMOND, Wash. Feb. 14, 2013 Remember 2008? It was the year the Great Recession descended, bringing the global economy to a near-standstill. The financial meltdown on Wall Street flowed through main streets around the globe, destroying many community banks in its path. In fact, according to the IMF, through 2010 the recession had already drained a whopping $3.4 trillion from financial institutions around the world.

Ron Van Zanten
Ron Van Zanten
February 13, 2013
Ron Van Zanten, vice president of Data Quality at Great Western Bank.

Which makes Great Western Bank’s story truly amazing. As some institutions shuttered and shrank, Great Western reinvested – in its people, customers and in how it uses technology to make its business better.

And it grew. Great Western Bank is now one of the largest banks in the United States, with 200 branches and over 400,000 customers. The bank has expanded by more than 300 percent since 2008 and continues to have ambitious growth plans.

To support these plans, Great Western Bank needed a technology solution that would enable increased profitability and better insight into customer relationships.

MNC: How will big data enable Great Western Bank to achieve your growth plans in the coming years?

Van Zanten : Big data gives us a 360 degree view of our customers. It allows us to understand customer activity, such as clicks through our webpages or ads. We can also compare that activity with the products those customers use – such checking or savings accounts or loans – and whether they are happy with, if they want a new product offered what it could be. So we can start to predict what types of engagements or services they are looking for. It also allows us to understand the behaviors of potential customers: what are they looking for when they go to our website, which products do they examine.

We are able to analyze employee actions and customer interactions and measure against results, to see which activities increase the bottom line. And we can see which activities are not adding value. For example, a customer that just opened a checking may get a call within a couple days asking how her experience was, and to talk about additional products or services. This is a legacy process that provided an opportunity for the bank to offer whatever products were currently being sold (such as credit cards and a new promotion). But that might not be the best product for everybody. So now, we can build these relationships more effectively - bringing opportunities forward that our customers want to hear about.

MNC: How are executives at your banks embracing big data?

Van Zanten : Our executives are under the same pressure to perform and do more with less. This data is the best way to move the dial and prove the dial is moved. If they don’t have the analytics to defend what they spent money on, they can be in a tough spot. So out of necessity, our executives are in.  Some people are interested in it because of their background – the risk department has seen how trends and analytics really changed the financial industry. Business bankers are the guys who shake customers’ hands; they can come back and prove a customer is profitable, and that the return on equity is where the bank wants to be – because that’s what they’re measured on.  

Having data that can quickly and easily be analyzed by our bankers turns out to be a corporate asset.  It becomes a way for bankers to pilot programs they were unable to justify before.

MNC: What tools are you using to manage all of this data?

Van Zanten : We use the Microsoft stack – SQL Server 2012 and Windows Server 2008 R2 – as the core engine to bring all our internal and external data sources together to classifying it and get it standardized. We are able to relate all systems together through the concept of time, which is really linear. Then we can build a cause and effect diagram and relate data back customer. This is where we start to see some important trends, because we can link to customer accounts, their demographic data, biographical data, and activities related to that customer or like customers.

As for reporting, PowerPivot allows us to get information in front of users that is consistently valuable. In my previous life we had a huge data warehouse and thousands of reports. There were 7,000 reports in and 1,500 weren’t being used anymore. With PowerView, people can interact with the data, and either get to the quick answer or manipulate the data to a point where it is a useful, productive report. – Then they have the option of publishing via Microsoft SharePoint in order to share with their teams, or request an analyst to make a formal report that is a supported production item.

MNC: Why did you choose Microsoft?

Van Zanten : I had used the Microsoft stack before and I knew it would scale well beyond our size. I previously had a 30 terabyte database and it served thousands of people and about 20,000 report executions a day. I knew we could scale, and I knew it would be flexible enough to connect with all of our different data sources. SQL Server always allows us to build a schema and model that fit our bank, with our naming convention, and present it in a manner that our bankers are comfortable with (via pivot tables in Microsoft Excel).

Bankers have been living in the Microsoft Office environment for 20 years, so I didn’t have to retrain people on the tool. They felt comfortable with the data, and the tools they were using were familiar to them. It’s a lot easier to get them to trust what’s going on and get them to interact with the data warehouse.

MNC: What is the bottom line impact on your business?

Van Zanten : We get cost savings from eliminating activities that are not adding value to the bank. With a data warehouse, we can look at the effectiveness of mailing or calling campaigns or follow-up visits, and relate back to the performance of that customer after the fact. We can even figure out if the activity in a branch is justifying enough value for the branch’s existence. 

This is the billion dollar question in banking. Does a bank need 4,000 branches? All banks are afraid to give them up, because this was their homestead. Traditionally a branch location allowed a bank to own that neighborhood, and they would have coverage to interact with customers. But now, people are doing banking on mobile phones, on the internet, on the phone, etc.

At Great Western Bank, less and less of our customers go into a branch each year. What is the new value proposition for that? What kind of infrastructure do we need to ensure we can support those customers, to ensure we still have that connection, that our customers feel engaged? Connections are so lightweight, there is no sense of loyalty. So, we can now understand if there is a lift from TV commercials or mailers. Those measurements were historically done by feel (from branch managers, etc.), but banks no longer have the margins to make these decisions ad hoc. There has to be a justifiable return on investment, and the data warehouse can make that happen. 

It’s almost a necessity for banks to measure their customers and measure their activities. Banks that take this step will talk to customers in increasingly effective ways and customers will eventually feel a bond with this bank. For examples, mailers aren’t the best way to engage a 20-year-old kid that only wants to interact via mobile phones. But if you can build these touch points these people will be customers for 50 years. If you can establish a strong product suite with a customer (such as bill pay, online banking, checking accounts or loans), you’re in a much better spot than trying to talk them into coming in their 40s.

Microsoft’s Hottest Gear for the New Year

Editor’s note – Feb. 13, 2013 – Zumba Fitness Core was removed from the slideshow below post-production .

REDMOND, Wash. — Feb. 13, 2012 — Whether you’re working to keep new year’s resolutions or getting ready for spring, Microsoft has tech to help you get fit, keep you connected with friends and family, and stay motivated to achieve your goals. Explore our top tech tips and product picks this season, including Surface, Windows 8 PCs, Windows Phones, Xbox 360 and Kinect, Office 365 Home Premium, Bing and Skype. 

Head to your local Microsoft retail store or for more information.

Up Next: The Weather Channel Forecasts the Business Value of Big Data

REDMOND, Wash. — Feb. 12, 2012 — Weather is money. It can be a fickle profit maker or shaker. Weather can propel an upstart skydiving outfit in Argentina, while freezing up national economies in Asia. And the more precisely businesses, nations and people can understand, predict and plan for weather, the more money they can make. So it’s no wonder organizations big and small, across industries and continents, seek the very best weather information to help create their own fortunes.

Bryson Koehler
Bryson Koehler
February 11, 2013
Bryson Koehler, chief information officer at The Weather Company (TWC).
Web | Print

Here’s where The Weather Company (TWC), the parent company of The Weather Channel, comes in. TWC understands that weather forecasts are much more than a reason to stay up for the 11 o’clock news; weather provides a healthy business opportunity that extends far beyond a segment on a TV news broadcast. And, according to The Weather Company Chief Information Officer Bryson Koehler, the recent rise in data volume, velocity and variety only means TWC can improve their forecasts at perpetually faster rates.

MNC: So what does big data mean for The Weather Company?

Koehler: We are big data. Weather is probably the biggest big data platform. Weather plays a massive role in how you work, how you live, how you play and how you shop. It impacts a significant portion of the world’s activity, and big data is about understanding how consumer behavior intersects with and is influenced by weather.

MNC: What led The Weather Company to implement a big data solution?

Koehler: The most intriguing part of this story is that weather is all around us and it impacts decisions we make on a daily basis; it’s the largest influencer in your life that you don’t always pay attention to. However weather is also entrenched in the business world, providing us with an opportunity to help companies make intelligent decisions as it relates to weather. And as you know, weather is dynamic. Figuring out the weather once doesn’t matter. What does matter is that once you understand how people have reacted to weather in the past, you can extrapolate to predict how people will act in the future. This is fascinating to us, and maintaining our position as the world’s best weather forecasting organization is really an exercise of big data.

MNC: What are your business goals in terms of big data capabilities with forecasting?

Koehler: We provide services to industries including aviation, energy and many local broadcast television networks in the United States. With big data, we are helping our customers understand the data, so that they can take action. For example, sometimes the weather impacts travel at the last minute. The reality behind the scenes is that we knew very well—six hours or three days in advance—exactly what was going to happen. If we take weather as a big data exercise, we can help our customers act on that data to forecast the impact that it would have on aviation flight paths and systems, as one example.

MNC: Has anything surprised you since you started to implement big data solutions?

Koehler: The most surprising thing is how large the impact of big data is on day-to-day business and how little everyone has known about the specifics of those impacts.

MNC: Does leveraging big data tools make it easier for The Weather Company to give people better information on how weather can impact them?

Koehler: Advertisers can make real-time decisions around the ads they buy or run based on the weather—for a better return on their investment. We know that when it’s cold, people buy soup. But how cold does it need to be? We can define the trigger conditions for increased soup sales—X degrees, X wind chill, and X cloud cover. The ability to personalize data to target consumers who are in the right place and have the right conditions is a really big deal.

MNC: How much data does The Weather Company manage?

Koehler: The implementation we’re working on now combines data and moves it to a non-relational data store when it makes sense. We call this the SUN Platform, our storage utility network. With this deployment, we will centralize our multiple petabytes of data and the 10 or 20 terabytes of weather data that we ingest every day. We manage both a high velocity of data and a large long-term cache of historical weather information.

MNC: Is big data changing the way your company delivers content and people consume it?

Koehler: Regardless of how it’s delivered –on television networks, mobile applications or websites—weather information drives behavior. You don’t need a lot of data to describe a sunny day. You need a lot of data when you have a complex storm system moving through a city. Instead of delivering the same weather forecasts to everyone, we can personalize and enhance the consumer experience. You’ll see a lot of changes to our product as we continue to learn how weather drives consumer behavior.

MNC: Is there anything you’re doing to empower your employees to manage big data?

Koehler: The first thing is getting the right systems and architecture in place. The speed at which people want to store new data continues to increase, so we need to be flexible and responsive to requests for any type of data. If somebody says she needs pollen data for the weather in Scotland, we need to ensure that we can categorize, store and synthesize that data through our products very quickly.

MNC: What is Microsoft doing to support The Weather Company in getting insights from big data?

Koehler: Microsoft is doing a great job of helping people understand why big data is valuable and how companies can use it to improve their business. Microsoft also provides an incredible set of tools and technologies that make it possible to glean insights from big data. But it is more important right now to educate executive teams and decision makers about why big data is important to them.

MNC: Why did you choose Microsoft for your big data solutions?

Koehler: The question I would ask is: why do we continue to choose Microsoft? I view Microsoft as a strategic business partner in terms of the overall technology foundation that we’re putting in place. Microsoft products are uniquely positioned to solve big data problems.

MNC: Do you have information or anecdotes you’d like to add?

Koehler: Weather influences more than a third of the world’s GDP on a daily basis. It’s a foundational arm of any big data strategy. The Weather Company is excited about partnering with Microsoft and organizations around the world to leverage data that helps everybody make better business decisions.

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