Data lineage can be documented differently depending on a company’s needs. It is important to realize that a company as a whole cannot accurately define the needs for and benefits of data lineage because these needs and benefits vary by business driver. Each business driver has different data lineage stakeholders within a company; they have different business needs and expectations and require various benefits from data lineage. Let’s take as an example a company’s management.
Any data management initiative, including a data lineage one, is time and resource-consuming. A company’s management must see significant business benefits and anticipate a worthwhile ROI to invest in such an initiative. From my experience, if we use the “carrot and stick” metaphor, the “stick” business driver is usually more effective in starting a data lineage initiative.
Compliance with various regulations is one of the key drivers. Financial institutions experience the most significant pressure in terms of regulations regarding data lineage. BCBS239 (Principles for effective risk data aggregation and risk reporting by the Basel Committee on Banking Supervision), GDPR (General Data Protection Regulation), and IFRS 17 are examples of such regulations. The need to comply with these regulations pushes companies to start compliance-related initiatives. Compliance with regulations leads to reducing operational risk and avoiding potential fines. Many companies want to decrease high IT costs to improve their overall financial results. To do so, a company should replace legacy software, move to the cloud, and optimize data chains to avoid data redundancy. The corresponding initiatives will require significant initial investments. A company should expect an ROI on such initiatives in a medium-term timeframe due to ultimately decreased IT costs.
Many companies also need to improve decision-making in a currently turbulent business environment. Artificial intelligence and machine learning methodologies assist in achieving this goal. The application of these methodologies leads to improvements in data processing and analysis.
Business optimization, i.e., digital transformation, is on the agenda of many companies. These initiatives require significant initial investments to be paid off in medium- or long-term. These initiatives should lead to optimizing data chains and reducing IT costs.
A company should have documented metadata lineage to meet these needs and perform all related initiatives. Documentation of data lineage will require establishin a solid data management function.
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