DATA GOVERNANCEGOVERNANCEGOVERNANCE
Discover
- Obtaining a snapshot of the present state of the organization’s data lifecycle.
- Business processes that are reliant on supporting capabilities and data
- Data discovery, data profiling, and the present status of data and processes are all things to consider.
Apply
- All data governance rules, business rules, stewardship procedures, processes, and cross-functional duties captured should be operationally defined and ensured compliance.
- Enabling the automation of stated business rules and policies.
- Supporting human-centric business and IT workflows should be operationalized.
Define
- Data definitions and business context should be documented.
- Data classification, data linkages, and the establishment of a business lexicon
- Definitions of the hierarchical structure and reference data.
- Supporting business rules and policies, as well as KPIs, are defined.
Monitor and Measure
- Capture and assess the value and efficacy of data governance and stewardship actions.
- Keeping track of policy and rule compliance and exceptions.
- Monitoring data accuracy and policy adherence
- RCA data lineage and impact analysis
DATA MANAGEMENT OVERVIEWOVERVIEWOVERVIEW
Data Management
One-dimensional linear visualizations with varying start and end times
- Scatter Plotlines
- Time – series data
- Polar Region Charts
Visualization in a hierarchical structure
In an organization or system, data or objects are ranked and organized together.
- Trees Diagram & Location
- Circular Packing
- Sunburst Diagram
Visualization of Statistical Data
Numerical and statistical data are included in multidimensional data items.
- Graphs in the form of pie charts
- Histograms
- Maps of the world
- Charts with bubbles
Visualization of Relationship
Data Relationships between various data sets, as well as an analysis of the link between them.
- Network diagram
- Chord graph
- Graph of the temperature
DATA ARCHITECTUREARCHITECTUREARCHITECTURE
- Designing architecture
- Information Strategy That Is Comprehensive
- Developing a management system for data resources
- Developing a data storage strategy
- Architecture based on capabilities
- Data governance in real
- Data governance in real time Consolidation
- Monitoring and improving data quality
- Management of master data quality
- Creating a policy for data retention
- Define the procedures for archiving data
- Identifying data that has been archived
- From north to south systems, give the company end-to-end data visibility.
- Reports for corporate users that are self-serve and off-the-shelf.
- Data reporting in near real time, at any time and from any location