The different components of a data intelligence strategy can have a bigger business impact depending on maturity

Fully implemented

Work in progress

Data profiling and data quality scoring

36%

20%

Data quality remediation

31%

34%

Impact analysis

27%

28%

Data mapping

27%

25%

Self-service data literacy and asset discovery

27%

20%

Data policies and controls

19%

24%

Data stewardship and governance workflows

19%

22%

Metadata harvesting, classification and curation

across the data landscape

18%

19%

Self-service capabilities to shop for enterprise data

16%

19%

Stakeholder collaboration surrounding data assets

12%

13%

Data lineage

11%

17%

Association of technical assets with your

governance framework

10%

8%

Fully implemented

Work in progress

Data profiling and data quality scoring

36%

20%

Data quality remediation

31%

34%

Impact analysis

27%

28%

Data mapping

27%

25%

Self-service data literacy and asset discovery

27%

20%

Data policies and controls

19%

24%

Data stewardship and governance workflows

19%

22%

Metadata harvesting, classification and curation across

the data landscape

18%

19%

Self-service capabilities to shop for enterprise data

16%

19%

Stakeholder collaboration surrounding data assets

12%

13%

Data lineage

11%

17%

Association of technical assets with your

governance framework

10%

8%

Fully implemented

Work in progress

Data profiling and data quality scoring

36%

20%

Data quality remediation

31%

34%

Impact analysis

27%

28%

Data mapping

27%

25%

Self-service data literacy and asset discovery

27%

20%

Data policies and controls

19%

24%

Data stewardship and governance workflows

19%

22%

Metadata harvesting, classification and curation across the data landscape

18%

19%

Self-service capabilities to shop for enterprise data

16%

19%

Stakeholder collaboration surrounding data assets

12%

13%

Data lineage

11%

17%

Association of technical assets with your governance framework

10%

8%

Fully implemented

Work in progress

Data profiling and data quality scoring

36%

20%

Data quality remediation

31%

34%

Impact analysis

27%

28%

Data mapping

27%

25%

Self-service data literacy and asset discovery

27%

20%

Data policies and controls

19%

24%

Data stewardship and governance workflows

19%

22%

Metadata harvesting, classification and curation across the data landscape

18%

19%

Self-service capabilities to shop for enterprise data

16%

19%

Stakeholder collaboration surrounding data assets

12%

13%

Data lineage

11%

17%

Association of technical assets with your governance framework

10%

8%