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Octopai Data Lineage XD Debuts

May 18, 2021

Octopai's Data Lineage XD takes data lineage to the next level by providing the first advanced, multidimensional data lineage platform on the market. With Octopai's Data Lineage XD, enterprises have a complete, in-depth view of data flow, enabling them to drive more value from their data assets.

Octopai's new platform takes data lineage from the classic, monolithic, limited view of data to a multi-dimensional approach by offering three layers of data lineage. Data Lineage XD, with its visual representations, eases the discovery of the data flow and movement from its source to destination. With the three dimensions, it's not just about the horizontal and vertical movement of data but a complete understanding of the data origin, what happened to it, and where it is distributed within the ever-growing data landscape. With Octopai's automation and in-depth view of the data journey, it is easy to trace sources of specific data for the purposes of tracking errors, implementing changes in processes, and implementing system migrations to save significant time and resources, tremendously improving BI efficiency.

The Octopai Data Lineage XD layers include: cross-system lineage, inner-system lineage, and end-to-end column lineage. Cross-system lineage provides end-to-end lineage at the system level from the entry point into the BI landscape all the way to reporting and analytics. This level provides high-level visibility into the data flow mapping where data is coming from and where it is going. This type of lineage reflects data flows and dependencies using automated and augmented methods to provide the most extensive cross-system view of the entire data landscape. Cross-system lineage would be used to understand the impact of a broken process, making a change to a process, visualize data flow at a high-level, or discover parallel processes performing the same tasks, etc.

The inner-system lineage details the column-level lineage within an ETL process, report, or database object. Understanding the logic and data flow for each column provides visibility at the column level no matter how complex the process, report, or object. Some examples of inner system lineage functions would include visualizing the logic of a report, ETL, or database object data flow, locating dependencies within a report, etc. This includes all the components of each ETL process and report logic.

Additionally, the end-to-end column lineage details column to column-level lineage between systems from the entry point into the BI landscape all the way through to reporting and analytics. This lineage type is particularly important for regulations, impact analysis of a change to a column in the source system, root cause analysis, etc. since users can visualize the data flow at the column level.

"Corporations manage an abundance of data every day and many business decisions are dependent on that information. We are seeing more than ever that data access no longer resides in the Business Intelligence department alone; executives throughout a corporation need access to accurate data, fast," says Amnon Drori, CEO of Octopai. "Our platform addresses the needs of each data user, providing a complete data lineage solution at every level. Our customers feel that with our platform they are getting a premium platform at an affordable price."

Octopai's lineage enables collaboration for BI teams, democratizes data management, and simplifies the onboarding process for new employees. Octopai provides full end-to-end coverage of the entire BI environment including ETL, Database, and Reporting & Analytics systems - from on-prem to cloud-based systems - to allow BI & Analytics teams to gain full visibility into the data movement processes within their own unique organizational environment.

Getting Octopai's Data Lineage XD running takes up to just one hour of time, and does not require any additional dedicated resources. Within 48 hours, customers have access to all three types of data lineage for their entire BI landscape, allowing teams to be agile and forward thinking, creating better and smarter insights in a fast growing data environment.

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