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Metadata may not be something IT professionals think about that much. Yet, in the world of big data, metadata becomes much more important, especially as more organizations adopt and expand their analytics work.
In IBM’s 2011 survey of 3,018 CIOs, 83% of respondents in the poll “have visionary plans that include business intelligence and analytics”. However, according to industry consultant Claudia Imhoff, president of Intelligent Solutions, 59% of BI analysts “say that they miss information that might be of value to their jobs because they cannot find it.”
If users can’t find the data they need, they won’t be able to run the analytics the business needs. The most effective way to assure that users can locate the data they want is to scrupulously apply metadata in your analytics environment.
No less a luminary than William H. Inmon (“the father of the data warehouse”) has called upon IT departments to apply metadata to their business intelligence repositories. A dozen years ago in a paper on the importance of metadata for business intelligence analysts, Inmon wrote :
In the data warehouse environment, the first thing the … analyst needs to know in order to do his/her job is what data is available, and where it is in the data warehouse. In other words, when the … analyst receives an assignment, the first thing [he or she] needs to know is what data there is that might be useful in fulfilling the assignment. To this end the metadata for the warehouse is vital to the preparatory work done by the…analyst.
If it was “vital” then, it’s even more critical in our contemporary world of big data.
Metadata organizes information, helping to make it discoverable and accessible. You can apply a variety of attributes about the data that can reveal its relevance to users. For example, keyword, temporal, and geospatial information can be included as well as use constraints, pricing, contacts, and anything else that improves the quality of the information about the information being sought.
Metadata saves organizations time. It also makes the data more valuable, which, in turn, often makes it more useful to analysts. IT leaders should make it a priority in their organizations.