Hopefully yesterday you were able to review and fill in the sample maturity model template I provided you for. If you did, it should all be coming together for you. You likely have 5-7 Maturity Levels that are a tailor fit for your organization, and specifically your data. Remember, we crafted the model around what was already occurring within your data today. Thus, we didn’t really create a model; we actually just applied labels to your existing data tendencies. It is best to do it this way because your data will naturally follow the model going forward. Today we are going to look at the task of making sure your model works by reviewing it against your data. If you make it out of these simple tests, your maturity model is golden.
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The Data Governance Imperative
This book takes a refreshing look at Data Governance and offers an approach that provides value to the business. Highly recommended! Check it out here.
5 Steps to a Data Governance Maturity Model
Do you know the maturity levels of the data across your organization? It is important to score your data so that you can prioritize your work. Read our series on Maturity Model's here.
Ten Steps to Quality Data and Trusted Information
It is imperative that you have a Data Quality plan or program in place if you are doing Data Governance. This provides a very straightforward approach to getting Data Quality off the ground. A must read.
We’re almost through building a maturity model that is just right for your organization. I hope yours is coming along nicely. Today I’m going to provide you with a template that you can use that nicely sums up your maturity model. Did I mention that your maturity model document need not be longer than one page? Its true. A well organized maturity model should be clear and concise; lots of documentation will just cloud its real value. This template will help you to be clear about how your data stacks up. Once you’ve reviewed the template, we’ll talk about how to put the levels you’ve already discovered on your own (the highest and lowest) into the template, and then work to fill in the middle using the natural maturity you’ve already found in your data. Continue on for the template…
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