# Cube Partner - Semantic Layer Experts - Rittman Analytics

URL: https://rittmananalytics.com/partners/cube
Description: Rittman Analytics is an official Cube partner, specializing in semantic layer implementations, data modeling, and modern data stack architecture with Cube.dev technology.

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Experts in the Semantic Layer

![Cube Partner Network](https://rittmananalytics.com/lovable-uploads/82155628-cf07-432b-9221-8ae6dcaa2d35.png)

Rittman Analytics is a boutique analytics consultancy specializing in the modern data stack. As a founding member of the Cube Partner Network, our team provides expert consulting services to help organizations get started with Cube, either as part of a wider data strategy engagement or as a focused project to implement Cube's semantic layer on top of an existing data warehouse.

## What Is Cube?

Trust your insights. Consume data from any source, organize it into consistent metrics, and use it with every data app.

### Universal Semantic Layer + Agentic Analytics

**Best-of-Breed Semantic Layer with No Platform Lock-In:**A semantic layer is a middleware between your data source and your data application. Cube is an API-first, four-part semantic layer that enables data engineers and developers to make their data consistent, secure, performant, and accessible across every application.

**Works with All SQL-Enabled Data Sources:**Designed to work with all SQL-enabled data sources including Snowflake, Google BigQuery, Presto and Postgres, Cube has a built-in caching engine to provide sub-second latency and high concurrency for API requests.

**Built for embedding and data apps:**Headless, API-first, and decoupled from visualizations, You can use Cube with any charting library to build your own custom UI, or connect existing dashboarding and reporting tools to Cube and expose your data to every application via REST, GraphQL, and SQL APIs.

**D3 Agentic Analytics Platform:**Composed of AI-powered agents that specialize in data engineering and data analysis, these new capabilities capitalize on a growing market demand for trustworthy, autonomous AI systems that are explainable, governed, and enterprise-ready.

### Proof in Practice

![RIXO Store Front](https://rittmananalytics.com/lovable-uploads/b6da3bf6-740b-43ee-baa7-8bd1754d549f.png)

![Osprey Charging Network](https://rittmananalytics.com/lovable-uploads/29e54000-f903-4152-aada-f143b45338da.png)

#### How Rittman Analytics Helped Osprey Scale Their Data Platform

Osprey Charging partnered with Rittman Analytics to scale its data platform during rapid expansion, installing 800 chargers in nine months. We delivered a modern analytics stack using Snowflake, dbt, Fivetran, Preset, and Cube.

[Read the Full Case Study](https://rittmananalytics.com/case-studies/osprey)

## Cube Quickstart Package

Would you like to run Cube on-top of your Snowflake, Google BigQuery or other cloud data warehouse but don't have the necessary data engineering resources or know-how to develop a production-quality Cube semantic model?

  

We can help. Our data and analytics engineering team can setup Cube for you, build your semantic model and integrate it with your BI tool or help embed it in your SaaS application. We provide your engineers and data team with the training they need to get up to speed, or manage and support Cube for you.

![Rittman Analytics Cube Quickstart Timeline](https://rittmananalytics.com/lovable-uploads/190e3b0f-ee1b-4969-af81-e6f891e76be6.png)

### What Is Included

Cube semantic model design, implementation blueprint and documentation

Deployment of your Cube semantic model into the cloud of your choice using Cube Cloud

Configuration of access control, row- and column-level security

Connection of Cube to your SQL-based BI tool (e.g., Tableau, Superset, etc), notebook (e.g., Deepnote, Hex, etc.) or collaboration with your engineering team to integrate Cube into your application via REST API

Query optimization using Cube's in-memory cache, queue management, and configurable pre-aggregations

Documentation and enablement for your data team or engineering team

### What Do We Need?

To deliver our Quickstart package within four weeks, you will need to have already:

Implemented a cloud data warehouse, structured appropriately for ad-hoc analytics queries

Chosen and implemented your SQL-based BI tool, or developed an application into which Cube will be embedded

Identified a use-case suitable for use with Cube and capable of being delivered within four weeks

Not ready yet to deploy Cube? Don't worry - we can help get you there, and then work with you to deliver the Cube Quickstart!

## Ready to Build a High-Performance Semantic Layer?

Let's discuss how our expert implementation of Cube can accelerate your roadmap and deliver trusted, consistent metrics to your users. Schedule a free, no-obligation call to scope your project.