In part four of this series we introduced three key stages within the analytics lifecycle to outline how leading organizations are outpacing the competition. In this post, part five, we will explore the first of those stages (Acquire) which provides the ability to acquire and integrate data quickly
This is part four in a series presenting, in small easily consumable bites, findings and insights from the IBM Institute for Business Value’s latest study and paper - “Analytics: The speed advantage - Why data-driven organizations are winning the race in today’s marketplace." In part three we
Computational modeling has revolutionized all branches of the physical sciences, engineering and design. Leading-edge work in these fields is pushing new computational frontiers at nano scales. Computation-centric methods allow researchers to model, simulate and assess a much wider array of options
Let's explore in more detail the final two shifts highlighted in the new IBM Analytics study, “Analytics: The speed advantage - Why data-driven organizations are winning the race in today’s marketplace," including the transformation of business processes with digital capabilities.
This past summer we witnessed an incredible phenomenon seemingly capturing the world by storm: The ALS Ice Bucket Challenge. Facebook estimates 28 million people posted about ALS between June 1 and August 28, including comments and tags. 2.4 million videos also were created on YouTube, spreading
“As you dig deeper into unstructured data where feelings, emotions and other often messy information reside, you have to embrace qualitative metrics which don’t fit neatly into traditional quantitative analysis,” says David M. Lawson, co-founder & CEO of NewSci, LLC and this week’s Big Data
IBM developer challenges foster collaboration that can have a worldwide impact. Developers bringing together the power of open data, Hadoop and analytics can solve huge world problems, like the current Ebola crisis.
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To fulfill the promise of analytics, we must put a lot more effort into delivering these projects right, the first time. We must think through each of the traditional success criteria and ask ourselves the burning question: how is delivering analytics different? This starts from gaining executive
Chris Clark, COO of Fiberlink (an IBM company), reminds us that “mobile never stops. It runs like water, finds every crevice.” As such organizations (and CIOs) must be fully aware of potential exposures and their risks so that they can adequately protect client data and their organization as a
Jake Porway, founder and executive director of DataKind and this week’s Big Data & Analytics Hero, shares that they’ve found that "cross-sector collaborations between data scientists, managers, designers, foundations, nonprofits and more are critical for really making lasting change.” When we
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What are the opportunities of data refinement from the IT point of view? Does self-service data refinement devalue IT? Does it simply create more work for IT, cleaning up after business users who have run amuck?
Andy Hayler, CEO of The Information Difference, tells us that “the average large company has six different competing sources of customer data and nine different competing sources of product data.” For companies to succeed data quality is imperative.
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