Organizations have made investments in “small data” for years and many are achieving data governance, or at least understand the gap they need to fill. They know how to work with the relatively small number of technologies in play—including databases (standardized on SQL), ETL, DQ and BI—ideally all linked with modeling tools and/or a business glossary.

These organizations are now embracing the promise of big data—a new frontier akin to the Wild West or the gold rush. Sometimes this produces genuinely impressive-looking results and insights—especially those supporting marketing. But making decisions based on marketing insights can be low consequence compared to other potential analytical results, such as risk analysis and pricing information.

Learn how adding a context/governance layer can provide the following benefits and answer critical questions:

• Catalog - What information is out there and what can I use?
• Governance - Who owns/supports what? How up to date is the information and who is using it?
• Context/impact - Does the data have consistent meaning (name matches are not sufficient)? What are the technology dependencies and risks?