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
Companies whose investments focus on growing talent in data sciences help not only their processes, but also the company as a whole. In our most recent global study on big data analytics, we concluded that the gap between the demand for analytics talent globally and the supply of analytics talent
Big Data promises to intelligently join and mine hundreds of millions, and even billions, of records for various applications that require trusted data about customers, products, locations and other entities. Without quantifiable and verifiable confidence in data, the information originated from
This datagram quickly explains the nine levers that enable organizations to create value from an ever-growing volume of data from a variety of sources -- value that results from insights derived and actions taken at every level of the organization.
Twice recently, in two different large companies, people whom I have otherwise respected as being quite sensible have said to me that their organisations had appointed people who, within their own function, were ‘responsible for data quality’.
Well, when I went to Data Governance School back at the
One natural consequence of the influx of big data is that organizations are modernizing their infrastructures to do a better job of ingesting data from new sources, identifying data that has value, and leveraging that data. As they address those challenges and tap into the opportunity that lies
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?
One of the biggest problems posed by big data is separating the signal from the noise, or cutting through all the data to find insight and value. The 2013 IBM Institute for Business Value study surveyed 900 business and IT executives from 70 countries to assess how they’re converting data into
Whether you need to deliver trusted information to a data warehouse, get a 360 degree view of your customers, or put big data to work for your organization through any other project, IBM InfoSphere Information Integration and Governance capabilities provide a foundation of trust and protection for
Protecting and security sensitive big data is necessary to ensure data is shared for new forms of analysis. Before the owners of that data will share it (yes, political silos still exist, and yes individuals still feel they own data and can say no to sharing it), they want to ensure it is