Evolving from Chaos to Competitiveness: The Emerging Architecture of Next-Generation Data Integration
To compete on Big Data and analytics, today’s always-on enterprise needs a well-designed evolving high-level architecture that continuously provides trusted data originating from a vast and fast-changing range of sources, often with different formats, and within different contexts.
To meet this challenge, the art and science of data integration is evolving, from duplicative, project-based silos that have consumed organizations’ time and resources to an architectural approach, in which data integration is based on sustainable and repeatable data integration practices – delivering data integration automatically anytime the business requires it. (more…)
Last fall, The New York Times resident numbers geek Nate Silver provided a lesson in predictive analytics for the whole world to see – crunching big data to predict, with almost pinpoint accuracy – the winner of the U.S. presidential election.
The success of this high-profile project thrust big data analytics into the limelight, but there are many, somewhat more mundane applications, but with even more unforeseen revelations. (more…)
Data scientist may be the hot job of 2013, but many data professionals report they are already doing much of the work that would be defined as the data scientist role. They just aren’t calling themselves data scientists – at least not yet.
In a new survey of 199 data managers I conducted as part of my work with Unisphere Research and Information Today, Inc., we found that the traits of data scientists – individuals whose backgrounds include IT and programming; math and statistics; and a willingness to look at things differently—are already seen within today’s organizations, in the day to day work performed by database administrators, analysts, managers and consultants. The survey was conducted among members of the Independent Oracle Users Group. (more…)
Finally, there is now evidence of a clear link between financial performance and the broad use of data by employees. Specifically, organizations that take the lead in data analytics are more than three times more likely to be leaders within their industry groups than companies with standard analytics environments.
That’s the finding of a new survey of 530 senior executives, conducted by the Economist Intelligence Unit. There is little disagreement that the ability to make data available across the entire enterprise means greater productivity and performance. More than 80 percent of respondents believe that employees across their organizations “can and should be using data to do their jobs.” (more…)
Many organizations are rushing into big data efforts before it’s clear what business benefits will come from this new paradigm. And this is creating problems for big data analytics proponents. “At one very large financial services firm, we’ve heard that the next executive that uses the word ‘big data’ without a very precise explanation of how it will be used for the organization will be fired,” says Randy Bean, co founder of NewVantage Partners, quoted in MIT Sloan Management Review.
“The point is that there’s been so much overuse and misuse of the term that organizations need and want to understand precisely how big data capabilities and big data initiatives will help them,” he explains. (more…)
From the “it’s-About-Time” Department: More enterprises are embracing – or will soon be embracing – access to data analytics via mobile apps.
Having analytics available in a simple app fashion could be a major boost for efforts to “democratize” analytics in organizations. I once heard Competing on Analytics guru and best-selling author Tom Davenport wonder out loud at a conference why there weren’t more analytics being made available as a “cute little app.” By offering analytics through simple, single-purpose mobile apps, decision-making can be brought into a whole new realm. “I’ve heard of 50 analytical apps for the iPhone so far,” he points out. Examples include a nursing-productivity app, a truck-loading analysis app, and a social sentiment analysis app. (more…)
I ran across an interesting post by Dr. Michael Wu, principal scientist of analytics at Lithium, a social media strategy firm, about the value of Big Data, suggesting that too many people think the data itself is a valuable commodity. However, it is not the same as “information.”
As he describes it, “the promise of Big Data is that one could glean lots of information and gain many valuable insights. However, people often don’t realize that data and information are not the same. Even if you are able to extract information from your Big Data, not all of it will be insightful and valuable.” (more…)
Make no mistake about it, executives are hungry for Big Data and the insights new forms of machine-generated and user-generated data can offer. However, Big Data analytics skills are hard to find, and even when they are available, hard to finance. As a result, the handling of Big Data analysis is defaulting to business users.
That’s one of the conclusions of a recent survey of 241 executives from across the globe, conducted by the Economist Intelligence Unit. The survey confirms that data democracy is a positive force – the vast majority of respondents, 77%, favor enabling more of their employees with better access to Big Data and the ability to analyze it in the context of other relevant data. There may be inertia at the top, but a grassroots movement within organizations is forcing the revolution into a reality. (more…)