Overview
Data Sources
Learn
Engage
Books
Holistics Data Modeling is an abstract layer that stores the logic mapping between the logical business layer and the physical data warehouse.
This allows data teams to manage different data logics centrally, and the business teams to query data without having to learn technical SQL queries.
using SQL formulas
between different tables into models.
into reusable data models for consistent usage.
for business users
Maintainable
Define your company’s business logic in Holistics modeling layer to be used by the entire company.
Define your data model once and reference any piece of it anywhere else to avoid writing the same SQL queries over and over again.
As your business changes, updated metrics keep everyone aligned around fresh data.
Self-service
Business users now can perform self-service analysis without knowing SQL or relying on data teams.
SQL as underlying modeling engine
Holistics data modeling layer is built completely on top of SQL, translating every action into a SQL query that eventually runs against the MPP databases to query live results.
This utilizes the power of MPP data warehouses and prevents data duplication in traditional approach.
Unify ELT + BI
With the rise of MPP, more people are loading raw data into data-warehouses before transforming (ELT), then use SQL to transform and run analysis.
Holistics implement this idea by using SQL to unifying the Transform and BI step together, covering the entire analytics pipeline from end to end.
Best practices from software development
Holistics copies ideas expressed from DevOps in software development, and apply them to analytics. This speed up BI deployment, increase reliability and quality of analytics.
Fewer ad-hoc data questions. Happier data teams. All starts with Holistics.