“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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In 2014, there were several important shifts that occurred in the world of big data that business executives around the globe cannot afford to ignore. In part one we introduced four transformative shifts affecting the fast-paced digital marketplace; now in part two we will take a closer look at the
For insurance companies, the integration of big data and analytics solutions with telematics technologies offers important opportunities to extend the use of telematics data beyond usage-based insurance (UBI) and improve competitive differentiation.
Big Data & Analytics Heroes
Ben SnymanVP Underground Mining and Smart Services, Joy Global
“Roof stability and effective support is quite a challenge,” declares Ben Snyman, VP of Underground Mining and Smart Services at Joy Global and this week’s Big Data Hero. “If the roof has a problem, production halts. We cannot afford to wait around for a report telling us there is a problem. We
Data refinement is one of the most important revelations in the big data market. The idea is simple: you want to take advantage of and use all sources of big data. But when each individual user needs only information relevant to them, what’s needed is a data refinery. It automatically cleans,
The mobile market is continually growing with “mobile-based payments in the United States expected to reach $142 billion in volume in 2019.” With mobile comes mobile data and the grave need for security. Vijay Dheap, global product manager for IBM MobileFirst, declares that “mobile security
The case is clear: the faster you can turn raw data into intelligent insight, the quicker you can get ahead of your competitors.
This theme comes through loud and clear in the latest analytics study from IBM’s Institute for Business Value. Nonetheless, only 10 percent of organizations fit into the
When people say that "data is the new oil," they're usually making a general statement on how deeply modern organizations depend on data to drive transactions, analytics and processes in general. It's in that context that many organizations decide to appoint something called a chief data officer (