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Lyftron launches universal data access platform

Lyftron launched a data access platform that uses a data hub, data insights, enterprise-wide data catalogs and lineage, and hybrid cloud management and migration to unify data.

Lyftron Inc. has launched its universal data access platform that unifies structured and semi-structured data from more than 100 sources and enables real-time analysis.

The sources of data include data warehouses such as Snowflake, Redshift, BigQuery, Yellowbrick, Azure SQL Data Warehouse and Apache Spark, as well as business intelligence tools such as Looker, Tableau and Power BI.

Key features of the platform include:

  • Data hub -- Lyftron uses Transact-SQL, Microsoft's implementation of the SQL programming language, and SQL Server drivers to draw data from BI tools and eliminate the need for manually building data pipelines. It enables users to utilize Lyftron's prebuilt connects to connect to any data source and deliver data in normalized, ready-to-query schemas. Lyftron claims this reduces the time required for reporting.
  • Insights -- Collaborative data modeling, self-service data preparation and instant logical data warehousing results in BI being delivered in real time. Data preparation uses real-time access to selected sources and the legacy data warehouse from one place. Transformations are then applied and the data is bulk-loaded to the new database of the user's choice. Then, Lyftron's data warehouse layer provides parallel access to both data warehouses and all data sources in one place.
  • Enterprise-wide data catalog and data lineage -- This enables full database objects search guided by tagging, aliases and data set definitions. According to Lyftron, the data lineage process is simplified by enabling teams to bring in visibility for data sets usage on various stages and maintain a healthy warehouse.
  • Hybrid cloud management and migration -- Users can build a hybrid cloud data warehouse that acts as a data bridge between leading cloud platforms, on-premises data warehouses and data sources. It also enables access to data from different regions in a data hub and migration from legacy databases to a modern data warehouse without coding data pipelines manually. The data loading keeps data synchronized across databases, and the data bridge lets BI tools execute SQL queries across the cloud boundary.

According to Lyftron, its technology combines a columnar data pipeline process with modern data hub architecture to eliminate bottlenecks that can occur in both traditional extract, transform and load (ETL) processes and the alternative ELT ones often used in big data systems through the automatic creation of data pipelines.

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How would using a universal data access platform help you?
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It will help you to make your data pipeline and BI semantic layer fully dynamic with the changes coming from the source. So, with this feature you don’t need to manually add those fiend in your semantic layer as Lyftron handles that and you can also get the flexibility of replacing your BI platform with ease as now Lyftron becomes your anti corruption layer and controlling your universal data model that will work on any BI platform.
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