CryspIQ® Data Methodology
Learn how the CryspIQ® methodology turns fragmented enterprise data into a governed, reusable model that reduces duplication and improves reporting trust.
Data Model
Learn how CryspIQ® decomposes source records into typed fact stores, shared dimensions and dated relationships, then reassembles them with a link key.
CryspIQ® Platform Architecture
Learn how source data reaches the CryspIQ® enterprise data model, where quality and security are applied, how data is consumed and what Azure requires.
CryspIQ® Platform Features
Explore CryspIQ® features for sources, mapping, operations, data quality, consumption and security across Lite, Professional and Enterprise plans.
CryspIQ® Platform Plug-ins
Learn how to build and connect CryspIQ® plug-ins to extend your enterprise data model with custom source integrations and transformation logic.
Lumen AI
Learn how the CryspIQ® Lumen AI layer supports data mapping, answers questions in business language against a consistent enterprise data structure, and lets assistants like Microsoft Copilot ask questions of enterprise data without writing SQL.
Co-Existence
CryspIQ® does not replace Snowflake, Databricks, Microsoft Fabric, Synapse or AWS. It reads the raw or staging layer they already populate and supplies the enterprise model they expect you to build — with no migration, and benefits arriving productivity first, time to value next, cloud cost savings last.
Comparisons
Compare CryspIQ® with data warehousing methods and cloud data platforms such as Databricks or Snowflake, and understand how they work together.
Compare CryspIQ®
10 items