FAQ

What is ZebClient Analytics data format and Lakehouse?

The key data Lakehouse features delivered by the ZebClient Analytics infrastructure includes:

  • Single data low-cost data store for all data types (structured, unstructured, and semi-structured)

  • Data management features to apply schema, enforce data governance, and provide ETL processes and data cleansing

  • Transaction support for ACID (atomicity, consistency, isolation, and durability) properties to ensure data consistency when multiple users concurrently read and write data

  • Standardised storage formats that can be used in multiple software programs

  • End-to-end streaming to support real-time ingestion of data and insight generation

  • Separate compute and storage resources to ensure scalability for a diverse set of workloads

  • Direct access for BI apps or AI SQL agent to the source data in the lakehouse to reduce data duplication.

What is AI SQL agent that ZebClient Analytics supports?

ZebClient Analytics supports to deliver SQL query answers to natural language questions using a private integrated LLM. The LLM is specifically trained to generate text to sql queries and then tuned to the specific use case.

What is a Modern Data Analytics Platform?

A Modern Data Analytics Platform like ZebClient Analytics delivers an unified environment with a broad deployment footprint and the ability to handle a wide range of analytical use cases while meeting high-performance requirements at scale without subverting security, management, and total cost of ownership (TCO) expectations

Get started with ZebClient Analytics

Useful links

Public repos

ZebClient documentation

Zebware support

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