The promise of big data and analytics is revolutionary and exciting. But, to truly make big data a big deal requires confidence in your data. Learn how two teams tried to use analytics to fund a an enterprise project with dramatically different results. Discover how one went wrong and how the other
The concern about consumer data privacy has never been higher. For example, 86% of Americans are concerned with data collection from Internet browsing and how it is used, and 70% of Europeans are concerned about the reuse of their personal data. With data breaches and issues such as the NSA’s
I’ve encountered many customers who are keen to ditch their data warehouse and use Hadoop to store the organization’s data as a cost-saving measure and to provide more flexibility to the business. However, an oft-overlooked consequence of eliminating the data warehouse is that analysts are now
Security concerns have never been more top of mind for business leaders, consumers and governments. The proliferation of the digital age impacts all aspects of life and is radically changing the way we think about security, in both the cyber and the physical world.
The traditional approach to security is to build and stand on a wall protecting the most valuable enterprise assets. In a big data world, however, threats are rapidly multiiplying, originating across enterprise walls and taking new forms - making them harder to identify and defend against.
This is Part 1 in a 14 part series that is my attempt to present, in small easily consumable bites, findings and text from IBM Institute for Business Value’s latest study and paper - “Analytics: A blueprint for value - Converting big data and analytics insights into results”.
In the paper, my
This week, IBM’s Institute for Business Value (IBV) released its 2013 Study entitled “Analytics: A blueprint for value.”Stylized as an Executive Report, it is really a manifesto on the challenges that face every analytics-driven organization in their quest for success (and tangible value). The
Big data means more data – from more sources, in more formats. It also involves data that is created at a more rapid pace. All of those factors make it harder to establish context. Where did this data come from? How much do you trust it? What steps were taken to correct, or massage, the data?