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 reporting platform.

If you are looking for a simpler, less technical alternative to managing BigQuery together with a separate BI tool, Atlas can support many of the same reporting and analytics workflows in one managed platform.

How does Dataslayer Atlas work?

Atlas covers the main steps between connecting your data and making a business decision.

You connect the sources you need, and Dataslayer handles bringing that data into the managed Dataslayer Data Warehouse and keeping it synchronized.

From there, you can work with your data using:

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

This means that Atlas combines the data infrastructure behind your reporting with the tools used to understand and act on that data.

What data can I connect to Atlas?

Atlas is not limited to paid media or marketing data.

You can connect the data sources available through Dataslayer, including marketing platforms, analytics tools, CRM systems, ecommerce platforms, databases, spreadsheets, files, APIs, cloud storage, and other business systems.

For example, you can connect:

• Marketing and advertising platforms.
• Analytics and measurement tools.
• CRM and sales platforms such as HubSpot, Pipedrive, and Zoho CRM.
• Ecommerce platforms such as Shopify, WooCommerce, and BigCommerce.
• Databases such as PostgreSQL, MySQL, Microsoft SQL Server, BigQuery, Snowflake, and Databricks.
• Files and spreadsheets such as CSV, Excel, and Google Sheets.
• APIs and cloud storage services such as REST APIs, Amazon S3, Google Cloud, and Azure Blob.

You can use Atlas for one area of the business, such as marketing reporting, or combine marketing, sales, ecommerce, operations, and other business data in the same environment.

What does the AI Analyst do?

The Atlas AI Analyst helps you investigate your data using natural language.

For example, you can ask it to:

• Answer questions about your data.
• Summarize a dashboard.
• Compare periods and identify trends.
• Analyze specific segments, channels, markets, or campaigns.
• Highlight weak areas or potential risks.
• Explain which segments are associated with performance changes.
• Find anomalies or unusual movements.
• Suggest what deserves your attention next.
• Generate tables or analyses that can be added to a dashboard.

The AI Analyst is designed to help you understand not only what happened, but also why it may have happened and what you should investigate next.

It does not replace business judgment. The quality of its analysis depends on the quality and availability of the underlying data, and users should review important findings before making decisions.

Who is Dataslayer Atlas for?

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

Typical users include:

• Marketing and growth teams combining data from multiple channels.
• Agencies managing reporting and analysis for multiple clients.
• Sales and revenue teams working with 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 dashboards as well as SQL access.
• Companies that want different departments to work from the same source of data.

Non-technical users can work with existing dashboards and ask questions using the AI Analyst without writing SQL. SQL tools remain available for analysts and advanced users who need more control.

You can start with one area of the business and expand Atlas as your data and reporting needs grow.

Is Atlas an alternative to BigQuery and separate reporting tools? 

For many reporting and business intelligence workflows, yes.

BigQuery is used to store and query data. A separate BI or reporting tool is usually needed to turn that data into dashboards and reports. Teams also often need to coordinate data connections, permissions, refreshes, and analysis across several different products.

Atlas brings these capabilities together by providing:

• Data ingestion and synchronization.
• A managed data warehouse.
• Dashboards and visualizations.
• SQL tools and saved queries.
• AI-powered analysis.

This can make Atlas a simpler alternative for teams that want the benefits of a warehouse without having to operate a separate cloud warehouse and BI platform.

Atlas is especially relevant for marketing teams, agencies, and business users who want to work with reliable data without requiring a dedicated data specialist to manage the entire setup.

Atlas is not intended to replace every BigQuery use case. BigQuery may still be the better fit for organizations that need a general-purpose data platform, advanced data engineering, extensive customization, or deep Google Cloud integrations.

Atlas can also be evaluated alongside an existing setup. You do not necessarily need to replace every tool or migrate every workflow at once.

For a detailed comparison, see BigQuery Alternative for Data Studio: Atlas for Marketing Data.

Where should I start?

If you are new to Atlas, start by creating a workspace and connecting your first data source.

Once your data is available, create a dashboard and use the AI Analyst to ask questions about trends, changes, anomalies, and performance drivers.

You can then add more sources, dashboards, users, and analysis workflows as your needs grow.