Step 3: Assessing data readiness

Data rationalization involves the systematic review, cleansing, and organization of your organization’s data assets to bolster efficiency, curtail costs, and amplify data quality, accessibility, and reliability. This critical process involves purging unnecessary data (termed as redundant, obsolete, or trivial (ROT)), identifying valuable data based on relevance, accuracy, and business value, and aligning data initiatives with business strategies, metrics, objectives and key results (OKRs), and initiatives.

To execute a successful data rationalization project, a clear and defined focus is crucial, often established through a specific business use case with a well-defined scope and exit criteria. The involvement of a cross-functional team inclusive of key stakeholders such as C-suite sponsors, business operations, partner ecosystems, IT, and relevant business application and data teams is vital for success. Additionally, your data governance...