5 Ways to Achieve Data Maturity

Mature your data practices to achieve true data operationalization.
5 Ways to Achieve Data Maturity
Survey Methodology

Survey methodology

“Putting the 'Ops' in DataOps: Success factors for operationalizing data,” outlines how organizations can assess and progress their data maturity.

  • Objectives

    Organizations continue seeking new ways to capitalize on their ever-growing data to increase revenue, delight customers, and scale operations while meeting increased demands for security and operational resilience and regulatory requirements.

  • Priorities

    These rising demands require increased investment in technology, practices, and skills. IT decision makers need insight about their unique data requirements to help guide when and where to invest.

  • Respondents

    This report is based on a global survey of 1,100 professionals and executives in data, business, and IT roles across 11 countries, conducted by 451 Research, part of S&P Global Market Intelligence in Fall 2023 and commissioned by BMC. As part of a phased, multiyear analysis related to data management, DataOps, and data-driven business outcomes, the survey and report uncover insights into how organizations can assess and enhance their data maturity to help overcome challenges in how to use data for competitive advantage.

Data maturity

Respondents fit into one of four data management maturity levels

Developing Maturity

Functional Maturity

Proficient Maturity

Exceptional Maturity

Organizations with more mature data management and DataOps practices report greater success in data-driven activities.

Variables like leadership buy-in, internal skills availability, and regulatory history can influence where an organization sits on the data management or DataOps maturity curves, and shape how effectively it pursues improvement and optimization of its practices.

75% of organizations with more mature DataOps practices have a Chief Data Officer (CDO), compared to 54% with less mature practices.