Data Vault and Data Lineage: Understand the journey of your data

Understanding the journey of your organisation’s data is essential to making informed decisions. This process is known as data lineage. Keep reading to discover how Data Vault provides the framework for you to understand the journey of your data, and why data lineage is important.

What is Data Lineage?

Data lineage refers to your ability to visualise your data’s journey through a clear pathway. It enables you to define the start-point of your data, as well as how the data changes as it moves through different systems in the organisation. It is an essential component of any data governance strategy! Data Vault allows you to do that with its unique capabilities.

Benefits of Data Lineage

Save time

Data lineage allows you to readily diagnose problems related to your historical data.

Trustworthy analytics reports

Understanding the journey of your data ensures reliability and accuracy of analytics reports. Leading to more informed decision-making.

Assure auditability and compliance

Data lineage helps you ensure auditability and compliance. For example, with data protection regulations such as GDPR or CCPA. It provides you with a transparent view of data sources and transformations.

How data vault helps with data lineage

Data Vault accommodates changing business needs and complex data structures. The Data Vault has inherent advantages, enabling data lineage by design. Here are four ways it does that:

1. Data tracking

Data Vault allows granular and historic tracking of data, giving full source-to-target mapping. Enabling you to understand what transformation have taken place so you can easily track data lineage.

It also captures changes over time, enabling a comprehensive view of data lineage. This includes recording the timing of updates, inserts, and deletions.

2. Hub-and-spoke architecture

Data Vault uses a hub-and-spoke model. It separates business keys (hubs) from their descriptive attributes (satellites) and relationships (links). The architecture maintains a clear separation between different data entities and their relationships. This facilitates the tracking of data lineage across various entities.

3. Traceability

The modular and scalable approach to ETL/ ELT processes is unique to the Data Vault method. The method advocates extracting raw source data to give end-to-end visibility. Each data source is loaded and modelled into the Data Vault structure before business rules are applied. This layered approach enables easier tracking of your data lineage. Even back to specific processes or source systems – enhancing transparency and auditability.

4. Metadata management

Data Vault uses metadata to define and manage the structure of the data warehouse. Metadata contains information about the data sources, transformations, mappings, and business rules. Data Vault provides valuable context for data lineage with metadata.

Summary

In summary, Data Vault 2.0 is a powerful data warehousing method that can help you effectively manage your data. Implementing Data Vault 2.0 allows you to gain insights into your operations, identify opportunities for growth, and make informed decisions based on accurate and reliable data.

Need some help implementing Data Vault? Chat to us today. Our team of experts are happy to help.