The ability to visualize data flows and understand how they move within the data platform is a crucial element in ensuring the efficiency of the data management team.
An integrated Data Governance solution guarantees the possibility of analyzing data flows, both in terms of dependencies between Data Products, in an approach based on the Data Mesh paradigm, and in terms of relationships between individual columns of the data structures present on the various analytical applications (Column-level lineage).
Using dedicated connectors with Reverse Lineage capabilities it is possible to automatically reconstruct data flows, interpreting the transformations they undergo within the various portions of the Data Platform.
Blindata’s SQL Lineage module uses schema metadata and SQL statements (including standard database objects such as views and routines, query logs, and scripts generated by ELT tools) to infer data flows and transformations.
The automated SQL parser within Blindata generates a SQL syntax tree that vividly illustrates the data flows and transformations present in statements. Next, simplify this representation by eliminating transformations, creating a concise line graph that connects tables and columns only.
To improve user accessibility, the lineage view incorporates drill-down capabilities. This feature allows users to quickly identify the script or routine responsible for generating a specific data stream. Additionally, users can easily drill down into the details of transformations with just a few clicks, facilitating a comprehensive analysis of the underlying processes.
Connectors dedicated to a reporting tool, such as Microsoft PowerBi or Tibco Spotfire, allow automatic end-to-end reconstruction of the lineage, from source to final use of the data.
Specific impact analysis functions highlight, starting from any point of the Data Platform, all the impacted data assets, isolating the sections of interest if necessary.
![Data-flow-chart](https://www.quantyca.it/wp-content/uploads/2024/07/dataflowchart.png)
The integration with Data Quality Monitoring functionality allows you to proactively manage the communication of potential critical issues in the data to all affected parties.