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Bring SQL to the next level with Holistics Data modeling

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.

How Holistics Data Modeling works

Define business metrics

Define business metrics

using SQL formulas

Map relationships

Map relationships

between different tables into models.

Transform raw tables

Transform raw tables

into reusable data models for consistent usage.

Build explorable datasets

Build explorable datasets

for business users

Business logic

Maintainable

Build consistent metrics definition

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

Perform self-service analysis based on modeled data

Business users now can perform self-service analysis without knowing SQL or relying on data teams.

Self service without sql

What makes Holistics data modeling different?

SQL as underlying modeling engine

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

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

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.

Because Data Team Is Not An IT Help Desk

Fewer ad-hoc data questions. Happier data teams. All starts with Holistics .