As IBM's big data evangelist, James Kobielus is IBM Senior Program Director, Product Marketing, Big Data Analytics solutions. He is an industry veteran, a popular speaker and social media participant and a thought leader in big data, Hadoop, enterprise data warehousing, advanced analytics, business intelligence, data management and next best action technologies.
October 23, 2014
Data science by itself is an ineffectual civic-governance tool if it lacks strong champions who can wield it to get things done in the legislative, executive and judicial branches. Big data analytics can influence public policy if it helps frame a compelling case in the minds of decision makers for taking this or that action. And if data scientists can show that a counterintuitive scenario is more valid than "common sense" or "gut feel" on a particular decision, they just may change the terms of debate in public policy discussions.
October 16, 2014
I'm impressed with initiatives in the U.S. data scientist community to volunteer their time to worthy causes at home and abroad. Clearly, most of the data scientists who participate in communities such as New York-based DataKind have day jobs to pay the bills. But they see larger humanitarian causes (reuniting refugees, curing infectious diseases, feeding hungry populations and guaranteeing civil rights to the disenfranchised for example) that can benefit from the smartest data scientists applying their best efforts and most sophisticated tools to the task. To sustain the engagement of the data science community in these common causes, what's needed is for people and institutions to open source all of their decision-support assets: data, analytics, tools, platforms and, of course, expertise.
October 9, 2014
Data scientists, like anybody else, tend to gravitate to where the jobs are, especially those that fetch higher salaries, offer the resources needed to achieve their dreams and promise more rewarding career paths. For that reason, larger employers with well-established, amply funded big data initiatives tend to have an advantage over smaller organizations when it comes to recruiting the best and brightest data scientists. In order to more equitably distribute data scientist expertise among the haves and have-nots, the requisite skills, tools and platforms need to become more widely available at low or no cost.
October 2, 2014
The invisible spread of infections in healthcare facilities has continued to run rampant. Healthcare associated infections (HAIs) remain a serious threat everywhere in the world. Nevertheless, pathogen-caused infections, though they spread invisibly in healthcare environments, can be illuminated through judicious deployment of advanced analytics. Indeed, advanced analytics, which involves applying statistical methods to trustworthy data, has long been used to reveal invisible patterns of all sorts. Consequently, their potential role in HAI identification and risk mitigation should be obvious.
September 25, 2014
Global climate data is massive, diverse and often internally inconsistent. Researchers who attempt to use data science to understand, predict and control global warming find themselves challenged by methodological limitations that frustrate their attempts to fathom this sprawling mosaic. Chief issues include historically thin sources, rampant auto-correlations and heterogeneous data provenance. Tackling global warming requires a harmonious balance between theory-driven domain science and data-driven statistical analysis.
September 11, 2014
The customer is always right, even when some of them are totally unreasonable and, perhaps, a bit off their rocker.
September 4, 2014
The success of big data projects often depends on having access to robust, scalable data integration. You would be hopelessly naive if you didn't acknowledge the fact that integrating huge amounts of data into "data lakes" can be quite burdensome, costly, complex, time-consuming, labor-intensive and so on. Rest assured that big data integration doesn't need to be burdensome, especially if you're wielding the right platforms, tools, personnel and best practices. If you're suitably empowered, there's no need to fear the big data wolf at the door.
September 2, 2014
Transactions make the world go round, but fast analytics help the planet rotate even faster.
August 27, 2014
The consolidated memory cloud will be the dominant architecture of the big data future. For enterprises and service providers trying to get closer to that vision, however, the migration path will not always be straightforward.