The Value of Data Governance and Lineage
Data has become an invaluable asset for organisations across all sectors. Ensuring its accuracy, security, and proper management is essential for informed decision-making and staying compliant with regulatory requirements.
Data governance plays a crucial role here, encompassing the policies, procedures, and standards that govern how data assets are managed within an organisation. Its purpose is to maintain data quality, consistency, and availability while safeguarding sensitive information. A key aspect of effective data governance is data lineage – the process of tracing the journey of data throughout an organisation.
By tracing its origins, movements, transformations, and usage, data lineage enables transparency, identifies and resolves data issues, and ensures regulatory compliance.
What is data lineage?
Data lineage involves tracking and visualising the flow of data from its source to its final destination within an organisation. This means documenting where data originates, how it moves through various systems, and how it changes along the way.
Understanding data lineage is vital for several reasons. Firstly, it enhances transparency by providing a clear view of the data’s journey. This visibility is important for both internal audits and external regulatory compliance. Secondly, it helps pinpoint exactly where the data quality issues arise, making it easier to fix discrepancies. Finally, data lineage aids impact analysis, showing how changes to data sources or processing can affect downstream systems and reports.
Real-World Applications of Data Lineage
In financial institutions, for instance, data lineage can trace a customer transaction from its initial entry point through various processing systems. This ensures every modification is logged and accounted for, a requirement for meeting strict regulatory standards.
In healthcare, data lineage might track patient information from the point of intake through various electronic health record (EHR) systems. This helps ensure data integrity across platforms and enables quick identification and correction of data breaches or inaccuracies.
These examples highlight the importance of data lineage in supporting operational efficiency, governance, and compliance. At ADC, we recognise its value from both operational and regulatory perspectives. Below, we outline some use cases we have implemented for our clients to demonstrate the benefits of data lineage.
Data Lineage at ADC: Our Approach and Use Cases
Case Study 1: Implementing Data Lineage Solutions for Large Banks
We have worked with several large banks to implement data lineage. We see that a couple of banks use PowerDesigner to integrate data lineage into their data management processes. PowerDesigner is used to create Logical Data Models (LDMs) and define primary keys, foreign keys, data types, and data definitions.
The tool enables automatic generation of both Data Definition Language (DDL) and Data Manipulation Language (DML) scripts, streamlining the transformation of data models into functional database structures and efficiently loading it into the database. This ensures vertical data lineage is instantly available and consistent, as the implementation is automatically generated from the model.
This end-to-end visibility spanning from design to implementation, enables banks to manage their data assets more effectively, improving both operational efficiency and regulatory compliance.
Case Study 2: Enhancing Scalability and Efficiency in Data Mart Solutions for Smaller Banks
For multiple smaller banks, we have developed data mart solutions using dbt to make analytics more scalable and efficient. We see a trend in the market that more and more banks are using dbt to improves scalability and efficiency stemmed from better understanding of definitions and business logic, made possible by following the data lineage within dbt.
While dbt excels at establishing horizontal lineage by tracking the movement of data between tables and views (from source to staging, intermediate layers, and the datamart), it initially had limitations at the column level. However, a beta feature in dbt now supports column-level lineage, offering more detailed lineage tracking in the near future.
Case Study 3: Documenting Data Definitions and Compliance for Small Banks
Another way to use dbt is to document data definitions and movements. This documentation is essential for complying with Dutch Central Bank (DNB) regulations, as it provides clear records of data flow and transformations across systems.
In both cases, dbt’s flexibility allows the banks to manage data lineage effectively, enhancing their data governance and regulatory compliance.
The Benefits of Implementing Data Lineage
Implementing data lineage does not have to be expensive. With the range of tools available, including open-source options like dbt, organisations of all sizes can benefit from data lineage solutions.
The key benefits are clear: improved transparency, operational efficiency, and streamlined compliance with regulatory frameworks like those imposed by the ECB and other governing bodies. By mapping data flow, organisations can quickly identify issues, ensure data accuracy, and demonstrate accountability, all of which are crucial in today’s regulatory landscape.
Starting the Data Lineage Journey
It is often more beneficial to start implementing data lineage now and learn along the way rather than waiting for the perfect solution. Data lineage is an ongoing process, and trying to build an error-free system from the outset can lead to unnecessary delays.
By taking an iterative approach—starting small, learning from initial implementations, and refining as needed—organisations can gradually build a comprehensive data lineage framework that grows and improves over time. The sooner you begin, the sooner you will experience the benefits of stronger data governance and regulatory compliance.
Continue the Conversation
Interested in learning more about data lineage? Reach out to one of our experts, Viviënne Haring (Manager, Technology & Innovation), to discuss.
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