What Is Data Lineage? Why It’s Important to Track Data Flow
Some professionals view data lineage as the GPS of data.
It’s because data lineage helps users get a visual overview of the data’s path and transformations. It documents how data is processed, transformed, and transmitted to constitute meaningful information businesses use to run their operations.
Data lineage helps businesses get a granular view of how data flows from source to destination. Many organizations use data virtualization software with data lineage to help them track their data while providing real-time information to users.
What is data lineage?
Data lineage is the process of identifying the origin of data, recording how it transforms and moves over time, and visualizing its flow from data sources to end-users. It helps data scientists gain granular visibility of data dynamics and enables them to trace errors back to the root cause.
Data lineage informs engineers about the transformations the data went through and why. It helps organizations track errors, perform system migrations, bring data discovery and metadata closer together, and implement process changes with less risk.
Strategic business decisions depend on data accuracy. Without good data lineage, it becomes challenging to track data processes and verify them. Data lineage enables users to visualize the complete flow of information from source to destination, making it easier to detect and fix anomalies. With data lineage, users can replay specific portions or inputs of data flow to debug or generate lost output.
In situations where users don’t need details on technical lineage, they use data provenance to gain a high-level overview of the data flow. Many database systems leverage data provenance to address debugging and validation challenges.
What is data provenance?
Data provenance is the documentation of where data comes from and the methods by which it’s produced.
Although data provenance and data lineage have similarities, data provenance is more useful to business users who need a high-level overview of where data is coming from. On the contrary, data lineage includes both business-level and technical-level lineage and provides a granular view of data flow.
Data lineage and data governance
Data governance is the set of rules and procedures organizations use to maintain and control data. Data lineage is an essential part of data governance as it informs how data flows from the source to the destination.
Businesses use different tiers of data lineages based on their needs. Lower levels of data lineage provide a simple visual representation of how data flows within an organization, without including specific details about the transformations occurring as it moves through the pipeline. The highest tier is attribute-level data lineage that offers insights into how data flow can be optimized and ways to improve data platforms.
Organizations choose the data lineage tier based on their governance structure, costs incurred in implementation and monitoring, regulatory concerns, and the impact it would have on the business.
Understanding data lineage is a critical aspect of metadata management, making it essential for data warehouse and data lake administrators. Metadata management allows you to view data flow through various systems, making it easier to find all data associated with a particular report or extract, transform, load (ETL) process.
Platform lead at BMW
Why is data lineage important?
Data lineage doesn’t only help you fix issues or perform system migrations, it also enables you to ensure the confidentiality and integrity of data by tracking changes, how they were performed, and who made them.
With data lineage, IT teams can visualize the end-to-end journey of data from start to finish. It makes an IT professional’s job easier and provides business users with the confidence to make effective decisions.
