How old is your data warehouse? It’s a simple question and probably one you don’t think about much. The majority of production data warehouses are now 15-20 years old and probably very transactional centric. Over the years, you’ve probably remodeled “the house” more than a few times—adding some “rooms” and “upgrades” here and there. It’s starting to feel its age as more Business Intelligence requirements have been added, including Mobile applications and specialized analytics. And more and more ideas seem to show up in your inbox every day, especially Big Data questions.

Maintaining a database of postal mail addresses requires them to be maintained over time and validated. Conventional wisdom is usually that an address database should be largely static and never change after data entry unless someone physically moves. However, as in many cases, conventional wisdom is not correct in this case. Both the United States Geological Survey (USGS) and the United States Postal Service (USPS) recommend that physical street addresses be maintained at least once a quarter via a process named geocoding, which includes street name, city, state and zip code validation.

The success of any company is becoming more and more dependent on unlocking the value of data and turning it into trusted information for critical decision making. The ability to deliver the right information at the right time and in the right context is crucial. Today, organizations are bursting with data, yet most executives would agree they need to improve how they leverage information to prevent multiple versions of the truth, improve trust and control and respond quickly to change.

If you are an IBM customer, it is very likely you have received some level of education about IBM’s Information Management solutions platform, which includes IBM’s Big Data strategy.

IBM released Hadoop-based InfoSphere BigInsights in May 2013. There are already Hadoop-based commercial distributions from other vendors such as Cloudera, HortonWorks and MapR. So it was interesting to learn how IBM stacks up against other vendors in the Big Data landscape. I learned more about this because I had the opportunity to get hands-on with the InfoSphere BigInsights Big Data ecosystem the week of October 7, at an IBM boot camp.