What is Dataslayer Atlas and who is it for?

It is designed for teams that want to centralize, explore, visualize, and understand their business data without having to manage a separate data warehouse and BI platform.

With Atlas, you can connect data from marketing, CRM, ecommerce, databases, operational systems, files, APIs, and more, store it in the Dataslayer Data Warehouse, build dashboards, query the data with SQL, and use AI to investigate what is driving performance.

How does Dataslayer Atlas work?

Atlas covers the main steps between a data source and a business decision.

You connect the sources you need, and Dataslayer handles the ingestion and synchronization of that data into its managed data warehouse.

From there, you can work with the data using:

• Workspaces to organize different projects, teams, clients, or areas of the business.
• SQL Workbench to query the data directly when needed.
• Saved queries for analyses you want to reuse.
• Dashboards to monitor metrics and explore performance visually.
•  A range of visualization types for presenting and exploring your data. 
• AI Analyst for analyzing the data using natural language.

This means the same platform can handle both the data infrastructure behind your reporting and the analysis that happens on top of it.

What data can I connect to Atlas?

Atlas is not limited to paid media or marketing data.

All data connectors available in Dataslayer can also be used with Atlas, allowing you to bring different parts of the business into the same environment.

For example, you can connect:

• CRM platforms such as HubSpot, Pipedrive, and Zoho CRM.
• Ecommerce platforms such as Shopify, WooCommerce, and BigCommerce.
• Databases and data platforms including PostgreSQL, MySQL, BigQuery, Snowflake, and Databricks.
• Files and spreadsheets such as CSV, Excel, and Google Sheets.
• APIs and cloud storage including REST APIs, Amazon S3, Google Cloud, and Azure Blob.
• Dataslayer's marketing and advertising connectors.

You can therefore use Atlas for a single function, such as marketing reporting, or combine marketing, sales, ecommerce, operations, and other business data in the same data environment.

What does the AI Analyst do?

The Atlas AI Analyst sits on top of the data stored in Atlas and lets you investigate it using natural language.

For example, it can:

• Answer questions about your data.
• Summarize an entire dashboard.
• Compare periods and identify trends.
• Analyze individual segments.
• Highlight weak areas or potential risks.
• Explain which segments are associated with performance changes.
• Suggest a concrete next action based on the analysis.
• Generate tables and analyses that can be added to a dashboard.
• Find anomalies in your data.

Instead of only showing what happened, the AI Analyst is designed to help you investigate why it happened and what deserves your attention next.

Who is Dataslayer Atlas for?

Atlas is useful for teams that need to work with data regularly but do not want to maintain a fragmented analytics stack.

Typical use cases include:

• Marketing and growth teams combining data from multiple channels.
• Agencies managing reporting and analysis across clients.
• Sales and revenue teams analyzing CRM and commercial data.
• Ecommerce teams combining store, advertising, and customer data.
• Operations teams working with databases, spreadsheets, APIs, or internal data.
• Analysts who need SQL access as well as dashboards.
• Companies that want different departments to work from the same source of data.

You can start with one area of the business and expand Atlas as more data needs to be connected.

Can Atlas replace a data warehouse and BI tool?

Atlas was built specifically to combine capabilities that traditionally require separate products.

A common analytics setup might use a platform such as BigQuery to store and query data, together with a BI platform such as Tableau to visualize and explore it. 

Atlas brings those layers together by providing data ingestion and synchronization, a managed warehouse, SQL tools, saved queries, dashboards, visualizations, and AI-powered analysis within the same product.

For many business intelligence and reporting workflows, this can remove the need to maintain separate warehouse and BI platforms.

For a detailed comparison and guidance on when Atlas can replace an existing BigQuery and Tableau setup, see Can Dataslayer Atlas replace BigQuery and Tableau? [LINK]

Where should I start?

If you are new to Atlas, the best next step is to connect your first data source and create a workspace.

See Getting started with Dataslayer Atlas [LINK] for a step-by-step introduction.