In a recent article published on Information Age, Richard Lee said there is much discussion these days about data privacy and security, but precious little about trust. He expressed concern: "Trust is hard to achieve, easy to lose and almost impossible to regain." Richard joined us to discuss how
Seeing is believing. In this short demonstration, you will see the innovations announced in the prior session in action. You will see integration and governance applied to one of the most popular big data use cases: an extended 360 degree view of the customer.
The era of big data is the era of messy data. This is the big data paradox: larger volumes and variety of new sources are inherently complex, and that complexity can actually lower confidence. Organizations have created an entire role to raise confidence in big data: the chief data officer.
Big data has changed the IT landscape. Integration and governance must evolve and become more agile to handle the challenges of big data. IBM's latest innovations in integration and governance deliver context for big data, provide agile governance with automatic protection of big data and ingest
Successful organizations strike a balance between control and speed, moving quickly to explore and analyze big data, but also applying enough controls to avoid missteps with agile integration and governance. Are you confident in the analytic insights that drive your business?
Are you confident in the analytic insights that drive your business? Do you trust big data? Can you protect it? IBM can help with new innovative information integration and governance (IIG) capabilities to build confidence in big data.
Success with big data comes down to confidence. Without confidence in the underlying data, decision makers may not trust and act on analytic insight. Without confidence in your ability to deploy new big data technology and the skills to exploit it, you might defer on big data projects.
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
This week at IBM’s Information On Demand conference, IBM announced a solution for one of the largest concerns in big data today: Data security and privacy. InfoSphere Data Privacy for Hadoop is the first solution in the market to offer a full set of capabilities designed to protect sensitive
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
With 2.5 quintillion bytes of data created every day, organizations cannot wait to establish business-driven protection policies for keeping data safe. The rising volume of data and the growing number of analytics systems storing sensitive data exponentially increases the risk of breaches. IBM®
As organizations begin pursing big data initiatives, they discover how important it is to have an understanding of the underlying data used to generate relevant insight. Organizations - and the people in them - must have confidence in the data or they simply will not use it to its fullest potential
Data security rules have changed in the age of big data. The V-Force (Volume, Velocity and Variety) has changed the landscape for data processing and storage in many organizations. Organizations are collecting, analyzing and making decisions based on analysis of massive amounts of data sets from