Test Genius

The data lineage helps to standardize the metadata and integrate the information, avoiding errors derived from the different version schemes.

Get Started

Allows standardize the metadata and integrate the information from the data schemas of various versions of entities, avoiding the existence of errors derived from the different schemas.

and integrate the information, avoiding errors derived from different version schemas. It also allows integrate new tables with old schemas, unifying to a destination table. The internal process of this solution performs a cycle between different versions, where each version will be placed in its corresponding destination according to the comparison made in the cycle (data lineage).

The source and target can be

Any combination of connected and allowed relational database providers

  • SQL Server database versions 2012 or later
  • Azure SQL Database
  • SQL Server in virtual machine
  • Azure Database for PostgreSQL
  • Azure Database for MySQL
  • Among others.

Once it have the complete mapping of the different versions

You can perform the required operations:

  • Validation
  • Comparison and
  • Integration.

The base of this solution is in Databricks

which allows handling large volumes of data and unify your data teams. to collaborate across the entire data and AI workflow.

Teia Data Version Unifier

This solution performs some simple detections of paterns in fields automatically, however, for optimal operation the process requires business rules and manual validation in case of not detecting simple paterns between the fields.

The differences between source and destination appear in a comparative matrix to facilitate their validation. Once you have the complete mapping of the different versions, you can perform the required operations:

  • Validation
  • Comparison and
  • Integration

Once the process is finished, a notifications are sent via email to the administrators with the report of the integration results.

The comparisons are saved and can be integrated into a script to be versioned, and modified and used later.

The base of this solution is in Databricks, which allows handling large volumes of data.

Reliable data engineering & modern high-performance data storage .

Repudiandae rerum velit modi et officia quasi facilis

Laborum omnis voluptates voluptas qui sit aliquam blanditiis. Sapiente minima commodi dolorum non eveniet magni quaerat nemo et.

Incidunt non veritatis illum ea ut nisi

Non quod totam minus repellendus autem sint velit. Rerum debitis facere soluta tenetur. Iure molestiae assumenda sunt qui inventore eligendi voluptates nisi at. Dolorem quo tempora. Quia et perferendis.

Consequuntur inventore voluptates consequatur aut vel et. Eos doloribus expedita. Sapiente atque consequatur minima nihil quae aspernatur quo suscipit voluptatem.

Repudiandae rerum velit modi et officia quasi facilis

Laborum omnis voluptates voluptas qui sit aliquam blanditiis. Sapiente minima commodi dolorum non eveniet magni quaerat nemo et.

Incidunt non veritatis illum ea ut nisi

Non quod totam minus repellendus autem sint velit. Rerum debitis facere soluta tenetur. Iure molestiae assumenda sunt qui inventore eligendi voluptates nisi at. Dolorem quo tempora. Quia et perferendis.

Data Version Unifier main features are:

Consulting Service. Analysis phase where the information on the structures to be migrated as well as the structures and rules to be configured is closely obtained.

Configurable.

Allows you mapping the distincts source schemas into a destiny for each data source

Integration capacity.

Take advantage of the integration capacity of data sources as different as those that SAP HANA, MySQL, SQL Server, Oracle, PostgreSQL and others.

Robust.

Allows loading of large volumes of data

Transparent and reliable.

Allows to know by means of control figures the results of the process

Secure.

Able to set profiles or roles of access to the information for each user of your company.

See what customers are saying

“The problem of having different schemas and not being able to compare the information in the same entity is common in projects where it's required to validate, perform operations, use derived columns, compare and integrate historical information”...

– Government Client