The DATA-DRIVEN webinar series, 23 June 2020 |


On June 17, the webinar “ASSESSING YOUR DATA MANAGEMENT MATURITY” was held where Irina Steenbeek, Founder of Data Crossroads, spoke about the data management/governance maturity.

In this webinar of “The DATA-DRIVEN webinar series” we covered the brief overview of the existing data management & governance maturity models, the description of a methodology to make a brief scan of the maturity in your company, and demonstrate the results of the global data management assessment review.

Here are some of the main points:

Maturity is a measurement of the ability of an organization to undertake continuous improvement in a particular discipline

  • Three questions about data management maturity
      • Why: Key reasons to perform  a data management maturity assessment
      • What: The definitions of maturity and data management/ governance
      • How: Challenges with existing models
  • There are two key reasons to perform a data management maturity assessment.
      • Define the steps to improve the performance of data management in your company
      • Benchmark the results against the peers in the industry.
  • There are two key perspectives on data management and its scope
      • DAMA-DMBOK2 – “broad” sense: from the enterprise point of view on the lifecycle of data circulating in a company.
      • DCAM v2.0 –  “narrow” sense: from the viewpoint of tasks to be done by data management professionals.
  • There are several challenges with well-know data management and data management /governance maturity models.
      • Fundamental conceptual differences.
      • Differences in the definitions of DM terminology and the content of DM capabilities / functions.
      • DM maturity models can hardly be mapped.
      • Results of different maturity models can hardly be compared.
      • The metamodels of DM models and DM maturity models are not aligned.
      • DM maturity benchmarking is hardly possible.
  • Regardless of the chosen approach, you need to perform a data management maturity assessment
      • Specify the metamodel of DM used in your company: definition, scope, and key substituted components.
      • Align and map the DM metamodel with the metamodel of the maturity model.
      • Specify maturity levels and define corresponding indicators (KPIs) to measure the maturity.
      • Perform maturity assessment and specify follow-up steps.

If you want to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organization, request a demo.

You can watch the complete webinar ASSESSING YOUR DATA MANAGEMENT MATURITY video in our Youtube channel, where you will also find more videos related to Data Governance. You can subscribe to receive notifications of new videos.

About the Author: Angela Miñana Francés