Too many years ago, when I was at Verizon, a key problem was lack of consistent customer data – including the basics such as name, address and other customer information. Today’s blog explores some of the key customer data issues that persist in today’s IT systems… a sort of “Back to the Future.” The same

Data quality and data governance just don’t get any love in the big data world. Compared with all of the technology innovations in Business Intelligence (real-time dashboards, mobile BI, advanced visualization), data warehousing (MPP architectures, in-memory computing, data virtualization), and advanced analytics (in-database analytics, Hadoop, NoSQL), poor old data quality just doesn’t seem exciting.  But

Data Quality / Governance The data quality/data governance challenge is how to ensure that the business-critical decisions being made can be accomplished with high enough confidence that you can move from data governance to the realm of decision governance (i.e. all decisions are made with the best available information; we are acting on what and

When you look at the BI/DW landscape, a tremendous amount has changed in a relatively short period of time.  As discussed in previous postings, traditional tools and methods are struggling to keep pace with the needs of big data, and they have become somewhat of a liability for the future.  How much is the landscape

It’s an extremely difficult time for businesses these days.  The economic downturn has forced us all to tighten our belts and control spending applying hyper-focus on only those critical aspects of our business where any investment can produce near-term, measurable return while simultaneously trying to cut costs.  And, across the board, businesses and IT organizations