Best Data Lineage Tools in Asia

Aggua is an AI platform with augmented data fabric that gives data and business teams access to their data. It creates Trust and provides practical Data Insights for a more holistic and data-centric decision making. With just a few clicks, you can find out what's happening under the hood of your data stack. You can access data lineage, cost insights and documentation without interrupting your data engineer's day. With automated lineage, data engineers and architects can spend less time manually tracing what data type changes will break in their data pipelines, tables, and infrastructure.

DataGalaxy’s all-in one data catalog provides out-of-the box actionability, with fully-customizable features, visualization tools, AI integration, to give business teams a way to document, link and track their metadata assets. The Data Catalog 360deg platform's user-centric approach is dedicated to metadata management, knowledge sharing, and mapping. This helps your organization manage data in the way that you want. A data catalog allows employees from different teams to collaborate by using homogeneous, centralized data sets. Our data catalog provides clarity for data definitions, synonyms and essential business attributes. It also includes a semantic layer to help all users understand and leverage data. If you are looking for answers on a specific metadata, the data catalog will identify 360deg data experts and owners. This will empower your team by facilitating collaboration.

Get a clear view of your data assets: popularity, usage, and schema coverage. Get important insights into your data assets, such as popularity and utilization. Find and filter data based on tags and descriptions in metadata. Get valuable insights about your data assets, such as popularity, usage, quality, and schema cover. Drive data governance and ownership throughout your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Lineage maps are automatically generated at the field level to help understand the entire data ecosystem. Anomaly detection is based on your data and seasonality patterns. It uses automatic backfilling from historical data. Machine learning thresholds are trained for each data segment and not just metadata.

Data knowledge management platform that allows teams to simplify data discovery and understanding with the ultimate goal to be able to trust their data. Stop costly mistakes and misreporting analytics today!

Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.