What is Data Maturity?
The extent of an organizations’ capability in leveraging their data, defines their data maturity level. The stages in which an organization’s data maturity is assessed can be laid out with a data maturity model. The model indicates how effectively the organizations can leverage their data in a methodical manner. It further allows them to set the base for strategies and actions to achieve the desired level of data maturity.
Why Data Maturity Assessment is Necessary
It is necessary that organizations measure and manage the extent of data being leveraged. As organizations strengthen their efforts toward reducing time-to-market, leveraging data as an asset to improve business agility and market readiness is imperative. Data maturity assessments (DMA) are crucial to business strategies, enabling quicker insights and market predictions even as helping organizations in being future ready.
Data maturity assessments uncover where an organization stands in terms of maturity level, providing quantitative measures for assessing existing data strategies. It further helps in strengthening the confidence and trust of customers and stakeholders. A robust DMA framework facilitates organizations in identifying and evaluating their present level while taking steps for moving to the next level.
Key Domains of Data Maturity Assessment
It is important that organizations focus on assessing the existing data platform, strategy, and architecture based on the defined domains. The assessment is done based on three functions, namely, process, people, and technology.
- Data Quality: