While most companies recognize at some level that data is a valuable corporate asset, only a few have appointed a Chief Data Officer (CDO) to help bridge the gap between …
Build the Data Management Organization – Part 02
Identify and Analyze Stakeholders A stakeholder is any person or group who can influence or be affected by the Data Management program. Stakeholders can be internal to or external to …
Build the Data Management Organization – Part 01
Identify Current Data Management Participants When implementing the operating model, start with teams already engaged in data management activities. This will minimize the effect on the organization and will help …
Data Science – Process and Iterative Phases
The Data Science process follows the scientific method of refining knowledge by making observations, formulating and testing hypotheses, observing results, and formulating general theories that explain results. Within Data Science, …
Data Science – Dependency
Developing Data Science solutions involves the iterative inclusion of data sources into models that develop insights. Data Science depends on: Rich Data Sources: Data with the potential to show otherwise …
Data Quality – Policy and Metrics
Data Quality – Policy Data Quality efforts should be supported by and should support data governance policies. For example, governance policies can authorize periodic quality audits and mandate compliance to …
Data Quality Program – Implementation Guidelines
Typically, a hybrid approach works best – top-down for sponsorship, consistency, and resources, but bottom-up to discover what is actually broken and to achieve incremental successes. Improving data quality requires …
Data Quality – Audit Code Module and Metrics
Quality Check and Audit Code Modules Create shareable, linkable, and re-usable code modules that execute repeated data quality checks and audit processes that developers can get from a library. If …
Data Quality – Preventive and Corrective Actions
Preventive Actions The best way to create high quality data is to prevent poor quality data from entering an organization. Preventive actions stop known errors from occurring. Inspecting data after …
Data Quality – Incident Tracking System
The incident tracking system will collect performance data relating to issue resolution, work assignments, volume of issues, frequency of occurrence, as well as the time to respond, diagnose, plan a …