Data Asset Management
Data is referred to as the new gold. Or named an asset for an organization. That means that data can no longer just be the output of a business process. It needs to be a strategically managed objective for the organization. It needs to be planned, designed, built, maintained & optimized, but also archived/removed to continuously build the value. These are the 6 phases of the lifecycle.
This can be achieved with the Data Asset Management Lifecycle. One half of the journey is the planning and realization/ acquisition of the data asset. The other half is the actual usage and improvement of the data asset.
The organization actually starts gaining benefit from the data value in the use and improve stage of the lifecycle. Therefore we need to shorten the time required to get through the phases of planning and acquisition.
When your organization is at full maturity the deliverables for each phase are as following:
1 Plan & identify
- Data Quality KPI’s
- Enterprise Data Target Architectures
- Roadmap
2 Design & specification
- Roles & Responsibilities
- Data quality dashboard
- Conceptual data models
- Data Flows
3 Development & Acquisition
- Data Management Organization
- Data maintenance proces & workflow
- Data quality analyses
- Business glossary
- Business rules
- Logical data models
- Data definitions
- Data quality rules
- Data lineage
- Data traceability
4 Usage & maintenance
- Data quality maintance
- Business glossary
- Data Lineage (following data, horizontal view)
- Data traceability (finding data, top down view)
- Data protection
- Data compliance
5 Improvement & optimization
- Data workflows
- Data quality analyses
- Data models
- Data flows
- Data lineage
- Business glossary
6 Archiving & removing
- Data Management Organisation
- Data quality analyses
- Data repositories
- Business glossary
- Data flows
- Data lineage
When you are interested in identifying and developing your data assets en the relation to you information assets, please don’t hesitate to contact LeanData!