Data Lineage for Snowflake
Snowflake is a cloud-based data management platform that provides enterprises with a flexible, scalable architecture for effective data collaboration.
MANTA’s unified lineage platform automates metadata discovery to deliver a complete, detailed overview of data flows across the enterprise’s data pipelines. When planning migrations, implementing DataOps, or preparing for a compliance audit, MANTA can help teams extract more value from their data.
MANTA’s Snowflake scanner generates detailed lineage for a comprehensive overview of the journey the data undergoes throughout its lifecycle. By leveraging MANTA’s scanner to map lineage in Snowflake, users can understand their data in context, increase business agility without sacrificing quality, and deliver data intelligence that fuels growth.
Snowflake components currently supported by MANTA’s scanner (and more are coming soon!)
- Data dictionaries—get lineage for asset catalogs in hierarchical databases
- Scripts—lineage for custom SQL code and ETL activities in MANTA’s native UI
- Views—visualize the SQL code logic for user-defined tables to boost data accuracy and trust and speed up reporting
- Functions—extract metadata from Snowflake functions for custom logic and pipeline insights
- External tables—see connections and dependencies across offsite data sources for queried files
- Procedures—experimentally enjoy analysis of dataflow of procedural code
- Learn how to maximize the value of your Snowflake data with MANTA’s data lineage
- Whitepaper: Migrating from Teradata to Snowflake in 1, 2, 3: How One Company Painlessly Migrated to the Cloud with MANTA
- Explore our latest updates and improved capabilities for MANTA’s Snowflake scanner in MANTA’s Release 33
Frequently Asked Questions
What is a data lineage scanner?
A data lineage scanner connects to database repositories, ETL tools, reporting tools, and other types of source technology to document how data flows, transforms, and impacts assets both downstream and upstream as well as where the data is sourced from, making it possible to gain full visibility and control over even the most complex data pipelines.
Why augment Snowflake with data lineage?
If Snowflake is utilized as a source for reports, applications, or another relational database, then having an up-to-date auditable blueprint of its data lineage is a must. Automated lineage gathering can reduce the time and costs of moving data to Snowflake by boosting business outcomes and migration benefits.
How can data lineage improve data quality?
When you have a complete overview of all your data flows, sources, transformations, and dependencies, you have control of your data assets. You can speak to the accuracy and quality of your data and have confidence in your data information and reports. By giving you a full overview of how your data moves across systems, where it originated, how it transforms along the way, and how it’s interconnected, data lineage can help you to ensure the quality of your data, reinforce your overall data management strategy, and increase trust in your data.
What is the purpose of data lineage?
Data lineage helps you tame data complexity and gives you a full overview of how your data moves across systems, including where it originated, how it transforms along the way, and how it’s interconnected. Such an overview will help you boost your data governance efforts, increase overall trust in data, achieve full regulatory compliance, accelerate root cause and impact analyses, roll out our frequent bug-free releases, painlessly migrate to the cloud, and more.
Get to Know Your Data’s Complete Story with Data Lineage
Metadata—data about your data—holds necessary information that helps you unlock valuable insights. Insights that will allow you to fully understand your data and get rid of anecdote-driven decisions and processes once and for all.