Do you have Data on your Data?

Since most organizations do not have unlimited budgets for data and analytics, prioritization often comes up. In many cases work gets focused to the "squeaky wheel" and from each business line there are always a series of priorities that are the "most important" for the company.
How is your analytics team handling these competing requests? Are they using data on the data that is produced? Using data to measure the effectiveness of the data assets that are created often gets lost as teams need to move on to the next high priority request. I classify data assets as tables, reports, data models, etc. Here are some suggestions to track and measure your data assets and the time spent to build those data assets.
- How many data assets does each business line have?
- What is the coverage of data assets for each business line?
- Does each business line have enough data assets aligned with their business priorities?
- Which data assets are used over time?
- How many data assets are not used?
- Are data assets used immediately when they are rolled out and then die off?
- What caused this drop off of usage?
- What data assets are used & re-used?
- What core data assets can solve multiple questions?
- Are these critical to the business line?
- What data assets that are special or small use cases?
- Who is using the data assets?
- Is the data asset used by a broad audience or focused group?
- How many users are Daily Active Users (DAU), Weekly Active Users (WAU), Monthly Active Users (MAU)?
Utilizing data on your data helps teams to make smart decisions around planning and prioritization. This builds awareness of not only the data assets themselves but also the teams the request work as well as the adoption rate of them. Having data & metrics for the questions above will help you and your teams to drive conversations with data and truly become a data driven organization.
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