Webinar Summary: Assessing Your Data Management Maturity

On 17 June, 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 a brief overview of existing data management and governance maturity models, described a methodology for conducting a brief scan of maturity in your company, and demonstrated the results of the global data management assessment review.

Here are some of the main points:

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

• Tres preguntas sobre la madurez de la gestión de datos
  • • 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
    • Compare the results against peers in the industry.

• Existen dos perspectivas clave sobre la gestión de datos y su alcance.
  • • 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-known 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.
    • The 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.
    • Carry out a maturity assessment and specify follow-up steps.

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

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