Webinar Summary: Assessing Your Data Management Maturity

On 17 June, the webinar «ASSESSING YOUR DATA MANAGEMENT MATURITY» was held, in which Irina Steenbeek, founder of Data Crossroads, spoke about the maturity of data management/governance.

In this webinar on «The DATA-DRIVEN webinar series»We cover a brief overview of existing data management and governance maturity models, describe a methodology for conducting a brief exploration of maturity in your organisation, and demonstrate the results of a review of data management assessment worldwide.

Here are some of the main points:

Maturity is a measure of an organisation's ability to undertake continuous improvement in a particular discipline.

• Three questions about data management maturity
  • • Why: Key reasons for conducting a data management maturity assessment
    • What: Definitions of data maturity and data management/governance
    • How: Challenges with existing models

• There are two fundamental reasons for conducting a data management maturity assessment.
  • • Define the steps to improve data management performance in your company.
    • Compare the results with those of your peers in the industry.

• There are two key perspectives on data management and its scope.
  • • DAMA-DMBOK2 – «broad» meaning: from the company's point of view on the life cycle of data circulating within a company.
    • DCAM v2.0 – narrow sense: from the perspective of the tasks to be performed by data management professionals.

• There are several challenges with well-known data management models and data management/governance maturity models.
  • • Fundamental conceptual differences.
    • Differences in definitions of data management terminology and the content of data management capabilities/functions.
    • Data management maturity models are difficult to map.
    • The results of the different maturity models can hardly be compared.
    • The metamodels of DM models and DM maturity models are not aligned.
    • Comparative assessment of the maturity of MDs is hardly possible.

• Regardless of the approach chosen, it is necessary to conduct an assessment of data management maturity.
  • • Specify the DM metamodel used in your company: definition, scope, and key components replaced.
    • Align and map the DM metamodel with the maturity model metamodel.
    • Specify maturity levels and define corresponding indicators (KPIs) to measure maturity.
    • Conduct the maturity assessment and specify the follow-up steps.

If you would like to know more about how Anjana Data can help you with your data strategy by changing the governance of data in your organisation. Request a live demonstration.

You can watch the full webinar video ASSESSING YOUR DATA MANAGEMENT MATURITY on our YouTube channel, where you will also find more videos related to data governance. You can subscribe to receive notifications of new videos.

>>>> Register for the following webinar: MAMDV3.0 as a reference framework for creating an operational environment for data governance, data quality management, and data management.