Picture the amount of data that a large company has acquired. Simply maintaining this magnitude of data could be a BI team’s full time job. Now, imagine that the BI team needs to find a certain data set among thousands or hundreds of thousands. Just searching through the data is like finding a needle in a haystack; a process that can take hours, weeks, or months. With insights being time-sensitive, this leaves the company in a difficult spot. The data landscape is constantly changing and without a system in place, the BI team is always a step behind. In order to close this gap, metadata management should be integrated into the business’s strategy.
What is metadata management?
If we separate the words and look just at metadata, this is the information that describes the data. By utilizing metadata, BI teams can understand the data’s journey, story, and content. The proper management of the metadata is extremely important and can make or break a company. Metadata management should answer five main questions when it comes to data: who, what, where, when, and how. If BI professionals can provide a concrete answer to each question, they will be completely aware of the data’s current status, history, and any changes it may have undergone.
Metadata management is especially important when it comes to investigating the root cause of an error. In order to pinpoint where an error originated, BI teams will need a clear view of the data’s journey and flow. They can then understand the error, reconcile it, and see which reports it may have impacted. This will help maintain the accuracy of future reports and solidify insights.
Another excellent use of correct metadata management is when a company wants to make a change to an ETL process and runs an impact analysis. If the metadata is organized and data lineage accessible, BI teams can understand which data sets that type of modification will affect. They can then decide how to best move forward with the change and adjust accordingly.