LARGE SCALE, HIGH-PERFORMANCE SQL ENGINE

BI tools integration

Lentiq comes with a built-in distributed query engine to allow external SQL and Business Intelligence tools to work with data in the data pool.

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More love for the business analysts

While the data scientist gets all the attention, 60% of data lakes are (silently) used by business analysts. With powerful tools like Tableau or DataGrip they are the secret superheroes of many organisations. Lentiq loves them too:

  • Simple, easy to use interface for non-dev people
  • Large scale distributed query engine usable by external BI tools
  • Fine-grained control over resource usage per project
  • Deep collaboration with the rest of the data team

Self service for business analysts

Lentiq has been designed to be operable by a single non-developer, non-data-scientist, non-data-engineer, non-PhD business analyst without any other help:

  • Upload and download data to/from the lake
  • Create managed tables from CSVs
  • Schedule queries and create workflows via SQL notebooks
  • Create ETL pipelines to import data periodically from other data sources via Streamsets
  • Subscribe and publish data to the rest of the organization

BI tools integration

Our distributed query engine can enable business analysts to work on far more data than ever before using Tableau, Qlik or other BI tools.

  • Apache Spark based for in-memory, high performance scalable query processing allowing business analysts to query bigger data
  • Wide compatibility - Almost all BI tools should be compatible with Lentiq via the JDBC/ODBC connectors
  • Low footprint - Start small, from just a few cores and scale as needed
  • Fine-grained resource quota management - This helps prevent your two business analysts from fighting with each other
Tableau
Data Grip
Qlik
Looker
Power BI

Better, simpler collaboration

Business analysts are an integral part of the data team. They work side by side in the same environment, on the same data without delays of any kind like when "null value" has more than one meaning.

  • Same compute and data environment for all members of the team eliminates any data access delays
  • No data conversion required. Business analysts use the same processing engine (spark) and same storage engine (parquet) as data scientists, eliminating field level compatibility issues and wasted time
  • Same metadata & data documentation access. All members of the team see the same data catalogue and data documentation providing a unified perspective

Do you want to try Lentiq with your team?

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