There is great value in metadata. However it can be a big and confusing topic. Get started with this overview providing structure to different uses of metadata.
All data starts with business metadata. This is the information we need to actually build a dataset. There is someone in the business who approved the collection and processing of data in the first place. He/she also provides requirements an descriptions on what he needs. The challenge is that this information is often not maintained throughout time which leads business metadata quality to decrease.
Become aware of the necessity and value of business metadata to enable support on data requests, make it findable and also understandable!
When we actually know what the business wants, we can design and implement this into physical form through technical metadata. We can now build the actual application or buy it of the shelf and map it to the business metadata.
Now that we know what data we need, what it means and have a place to store and process data; we can start doing business. This will generate operational metadata. This type of metadata is very valuable in monitoring our data processes. We get insights in what data is processed, how often, the speed and frequency. This is great input in analysing the performance of our IT landscape and see where improvements can be made. Further we monitor the access to systems and data. When we take it a step further we can even start analysing patterns and possibly spot odd behaviour as signals of threats to our data.
Step into the driving seat capturing and analysing your operational metadata and become pro-active in controlling your IT landscape!
Finally we can also take the social metadata as an inspiration. And this is where the actual value of your data becomes tangible. If value is determined as the benefit the user thinks he gains, the way that he uses the data is an indicator of value. Thus if we start measuring what data is used often by many users, this data must be important and valuable. So let’s invest in improving the quality of this data to improve the value created. Behaviour is also a good indicator to measure. How much time is spent on content and which content is skipped quickly. Apparently that content doesn’t match up with what the user is looking for.
Measure social metadata to analyse what data is used often by many. It is likely to be more valuable than other data.