Automated Data Lineage Capabilities Provide Organizations With Complete Visibility of the Data Flow

Octopai, a leader in metadata management automation for BI & Analytics, announces that the company has added support for Tabular on Azure Analysis Services, IBM’s Netezza, Vertica, and has expanded its support of OLAP cubes to enable organizations to understand their complete data flow to get full control over their data assets through automated data lineage and discovery.

With approximately 35% of enterprise reports residing on Microsoft’s Online Analytical Processing (SSAS – OLAP) cube, largely unsupported by data lineage tools, enterprises are increasingly frustrated by their extremely limited visibility of the data journey. To address this issue, Octopai has added advanced capabilities in its support of OLAP (full coverage of SSAS, both tabular models and OLAP cubes), enabling those organizations who rely on analysis tools to finally enjoy complete data lineage for reports based on OLAP cubes as well as MDX (MultiDimensional eXpressions) statements.

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Additionally, with IBM’s recent announcement of Netezza’s end of life, many Netezza users are looking to migrate their data over to another database (DWH). Now Octopai can assist organizations using Netezza with their migration, specifically to help them quickly and easily find and understand their data so they know what to move to their new system and what to forego. Other newly supported systems include Vertica and Azure Analysis Services. Octopai will announce coverage of Ab Initio, Azure Data Factory, Talend, Amazon Redshift and Snowflake in the coming months to bring ongoing value to the BI & Analytics domain.

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“Once blind in the face of their data, we are very excited to offer our cube customers expanded support of OLAP so that they can finally see the entire data journey with automated data lineage,” said Gal Ziton, CTO. “We are proud to continuously add ongoing capabilities for more and more customers using varying platforms and systems to provide a unified view and map of their data.”

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