Big Data
Making Data Easy for Businesses with Cloud Data Services
February 4, 2016 | Written by: Steve Hamm
Categorized: Big Data | Cloud Computing | Cognitive Commerce | Cognitive Computing | Data Analytics | Open Source Software
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Big Data has been called the most hyped tech trend in the world today. It promises to enable people of all stripes to tap into the world’s ocean of structured and unstructured data and to draw insights that help them make better decisions.
Too bad it’s not delivering fully on that promise.
Or it wasn’t, until now.
That’s because a huge change is coming to the world of Big Data. Think of it as the democratization of data analytics.
The combination of cloud computing with new development platforms and an explosion of open source data tools has given rise to a new approach to computing–cloud data services. These next-generation platforms offer everybody from the most accomplished data scientist and software developer to the “citizen analyst” (basically, you and me) access to data and insights with the ease we have become accustomed to because of the smartphone revolution.
IBM has been gathering and deploying the piece parts for our cloud data services offering for more than a year, and, today, we’re unveiling a one-stop-shop for accessing and exploring data and for building and deploying applications.
Our offering has three main pieces. 1) A set of 25 data and analytics services—a combination of open source software packages, IBM born-on-the-Web tools, and elements of our analytics software portfolio that have been rebuilt from the ground up as cloud services. 2) A repository of more than 150 public and free data sources, everything from census data to government economics statistics. 3) An easy-to-use cloud development platform—Bluemix.
We’re majoring in openness. We exploit open source software, including the popular Apache Spark analytics engine. We offer an open data ecosystem that aggregates proprietary, public and third-party data. And we deploy open architectures that allow data to easily flow among different services—and back and forth between cloud services and on-premises computing systems.
Another key theme is integration: Our data and analytics services are designed to play well together. Developers and analysts can mix-and-match them without having to massage the data or do extensive coding to connect the tools.
In my view, one of the coolest of our new services is IBM Compose Enterprise. It helps clients build modern Web-scale apps faster by enabling them to deploy a wide variety of open source databases and tools in minutes on their own dedicated cloud servers. That way, they can experiment in a secure environment.
One of the key beneficiaries of cloud data services is the business leader or individual within an organization who simply wants to do their job better using data—the citizen analyst. By taping into these new cloud data services, they can explore data sources, meld data of different types, select the most appropriate analytics tools, and produce actionable insights. And they can do it without necessarily having to engage the IT department and, in some cases, waiting weeks for answers. It’s a drag-and-drop experience. Or, if they choose, they can enlist the IT department to design more sophisticated analyses.
At the same time, these new services offer a host of more sophisticated capabilities designed for data scientists and developers—enabling data scientists to analyze complex situations using the most capable analytics tools and providing software programmers and product teams with a dynamic development platform.
For illustration purposes, we’ve developed a scenario for how a regional retail chain manager might use our cloud data services. Her online sales are going gangbusters, but she’s overwhelmed by an overabundance of data from many different sources, so she’s not able to understand what’s going on, how to build her promotional campaigns, and how she can handle all the growth without crashing systems. Tapping into our cloud data services, she can explore diverse data from a wide variety of sources, gather just the pieces he wants into a data warehouse, and pull it into Watson Analytics. There, she can get recommendations on key issues to investigate, ask questions, and see the answers expressed in easy-to-interpret graphics. As a result, she might spot a hidden pattern—a sudden burst demand for a certain athletic shoe among millennials living in cities with large minority populations. Boom! She can craft a promotion laser-focused on that shoe, those locations, and that demographic cohort.
I came into IBM nearly two years ago when Big Blue bought Cloudant, maker of a cloud database service where I was the CEO. Previously, most of my professional experience was in startups, and my passion was helping to deliver disruptive new technologies capable of transforming the way business is done. Now I’m doing pretty much the same thing—only I’m doing it from a seat inside a large tech company that’s transforming itself even as it helps its clients adapt to a rapidly changing business and technology environment.
Like I said before, the quest we’re on here is nothing less than the democratization of data analytics. It’s an exciting time for me, my IBM colleagues, and our clients. We welcome one and all to come share the experience.
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