Published: 27 August 2019
Summary
Data governance has become more challenging as data straddles edge, on-premises and multiple cloud environments. Also, new regulations are driving demand for effective data governance. This research provides a framework for data and analytics technical professionals to implement data governance.
Included in Full Research
- Prework
- Step 1: Data Discovery and Policy Setting
- Part 1: Identify Data Sources
- Part 2: Profile Data
- Part 3: Create Policies
- Part 4: Onboard Data
- Part 5: Apply Policies
- Step 2: Transform the Data
- Step 3: Curate and Remediate Enterprise Data
- Part 1: Curate Data (Data Catalog)
- Part 2: Remediate Data Quality
- Part 3: Search Metadata
- Part 4: Workflow
- Step 4: Master Data Management
- Step 5: Harmonize Departmental Data
- Part 1: Prepare Data
- Part 2: Analytics
- Part 3: Train Models
- Step 6: Operationalize Data Governance
- Part 1: Operationalize Analytical Reports and Models
- Part 2: Lineage, Audit and Impact Analysis
- Part 3: Check for Drift
- Follow-Up
- How to Mitigate the Risks
- Related Guidance