# Analytics Overview

Sprinkle’s **Self-Serve analytics** solution enables users to drive more value from the data in the warehouse.&#x20;

Built for modern-day **cloud data warehouses**, Sprinkle’s Analytics Solution empowers various types of users in the organization to uncover **insights**📈 and make **empowered** decisions.

:cloud: The Cloud warehouse acts as the **central hub** of the organizational data for analytics, data engineering, and data science teams. Running Analytics directly on Cloud Warehouses provides you with the flexibility to shape the data the way you want.

## Basic Components

Sprinkle provides a self-serve interface to explore and analyze data in the data warehouse. The below components form the basis of Sprinkle’s Analytics layer.

* [**Data Models**](/product/analysing-your-data/data-models.md): Define **Business Metrics** and **Dimensions** on the data warehouse tables.
* [**Reports**](/product/analysing-your-data/reports.md): Perform drag-and-drop analysis using our Report Builder UI from [**tables**](/product/analysing-your-data/reports/build-using-tables.md), [**Data Models**](/product/analysing-your-data/reports/build-using-models.md) or using [**SQL**](/product/analysing-your-data/reports/build-sql-reports.md) and build stunning visualisations :bar\_chart:
* [**Dashboards**](/product/analysing-your-data/dashboards.md): Club various reports onto the dashboard with custom filter options

{% hint style="success" %}
**Optimised for Performance:** Sprinkle does a lot of optimisations like caching of data, partitioning, etc for delivering high performance at optimal warehouse cost.
{% endhint %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.sprinkledata.com/product/analysing-your-data/analytics-overview.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
