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Holistics is a self-service BI platform

Self-service analytics, with DevOps best practices

Holistics helps data teams set up self-service BIs that are reliable and easy to maintain.

How? By applying software's best practices to analytics development:
• Define analytics logic once, reuse in multiple reports
• Build reports and metrics using code and Git
• Prebuild datasets for self-serve exploration

Everyone can now self-serve data with confidence.

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Centralized Analytics Logic

Centralized Analytics Logic

Maintain a central store of analytics. Define metrics and analytics logic once, reuse in multiple reports.

Define Analytics using Code

Define Analytics using Code

Define models & build reports using code. Check in Git for version control. Go through code review process.

Self-service Analytics

Self-service Analytics

Analysts prepare and curate datasets. Business users can self-serve data without writing SQL.

Semantic Modeling Layer

Define analytics logic in one single place

Define analytics logic in one place. Build reports off these well-defined metrics and dimensions.

  • Reusable: Update business logic once, auto-propagate to all reports
  • Accuracy: Metric definitions are consistent across different reports
No more fighting over which metrics are "right".

“The semantic layer is Holistics’ biggest draw because I was able to build reusable models, dimensions, metrics, and then describe them as code.”

Sterling Paramore

Sr Staff Data Engineer, Mainspring Energy

Define analytics logic in one single place

Analytics As-Code, Version Control

Build models & reports using code

Define analytics logic using our code-based analytics language. Check in to Git. Perform code reviews before deploying.

Manage your BI system the same way you manage software development.

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“Holistic effectively allows us to be repeatable. We add a new client, copy and paste all the data models, and change the data source. Done!”

David Aldred

Insight Director, Retail Insight

Build models & reports using code

Self-service Analytics

Curate datasets for self-serve analytics

Simplify self-serve process with pre-built datasets. Everyone can confidently achieve complex aggregation results with minimal effort.

No more “request queue frustration” for both business & data teams.

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“The ability for everyone to explore. Massive win!

Guido Stark

Head of Data, Optimal Workshop

Curate datasets for self-serve analytics

dbt Integration

Integration With dbt

Holistics integrates deeply with dbt, allowing metadata from dbt to be surfaced to the BI layer.

Leverage dbt as a central place for data documentation and use Holistics as the central entrypoint for data consumers.

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“Holistics’s dbt integration was the biggest draw for me and demonstrates a clear understanding of where the modern data stack is headed.

Stuart Shiell

Lead Data Insight, Semios

Integration With dbt

What makes Holistics different?

Holistics offers both experiences in the same platform: a SQL-friendly, maintainable interface for data analysts, and a reliable self-service experience for non-technical users.

SQL friendly

Friendly for data analysts who enjoy the flexibility of SQL.

Self-service

Let non-technical users run analysis without having to learn SQL.

Maintainable

Modularize and reuse data components, no more SQL spaghetties across multiple places.

With Holistics in our setup with BigQuery and dbt, if we have a new dataset available and we want to implement it, we can literally do it in like two hours from start to finish, including all the descriptions and metrics, as compared to probably 10 to 12 hours in our previous tool.

We really like the clean look and feel of creating reports and adding them to a dashboard. The main feedback from our business users was when are we getting more data ready to use?

Olaf V., Senior Intelligence Analyst at Feeld

Olaf V., Senior Intelligence Analyst at Feeld

Want to understand the complex landscape of data analytics?

Want a quick primer on the practice of modern data analytics? We wrote The Analytics Setup Guidebook to help you with that.

Get a soup-to-nuts overview of the broader data landscape in less than 200 pages. (Plus we drew all the pictures ourselves!)

Learn more

I'm shocked to be telling you this next sentence: I read a free ebook from a company and actually loved it.

See full review here

Mark MacArdle

Data Engineer