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Keep familiar reports. Make the data behind them easier to manage.
A client asks why acquisition costs rose last week. Before you can answer, you need to check which sources refreshed, reconcile a spreadsheet, and find the person who can fix a data-access issue. Your dashboard is ready. The explanation is still waiting.
When that becomes a routine part of reporting, the work behind the charts deserves a closer look. You need campaign history you can trust, clear access for each client, and a practical way to investigate changes without rebuilding the same process every week.
Atlas Business Intelligence is marketing reporting software for agencies and in-house teams that need a simpler way to manage Data Studio reporting data. It is a BigQuery alternative designed around marketing workflows. Atlas brings a marketing data warehouse, dashboards, and AI-assisted analysis together, while giving teams a way to continue using familiar reports.
What are Atlas, Dataslayer, and Data Studio?
Dataslayer connects your sources, Atlas organizes and analyzes the data, and Data Studio can remain your reporting interface. Each has a different role.
Dataslayer brings data from advertising, analytics, CRM, and other supported platforms. Atlas gives that data an organized home, with workspaces, dashboards, and analysis tools. Data Studio is where teams can continue presenting reports to colleagues and clients.
Naming note: Google reintroduced the Data Studio name in April 2026. If you are searching for a BigQuery alternative for Looker Studio, you are referring to the same reporting product. Read Google's announcement.
Why consider a different way to manage reporting data?
Consider a change when preparing and maintaining reporting data repeatedly delays the decisions your team needs to make. Start with those delays, then assess the product.
BigQuery has a native Data Studio connection and can be a strong foundation for analytics. That connection requires a Google Cloud billing project, and accessing data through reports may incur query or storage costs. Google explains the requirements. The question is how well the complete setup fits your team's daily work.
Problem: every new client adds another preparation task
A new account should lead to a useful report. Too often, it also means another export, another spreadsheet, and another process someone has to remember.
Atlas offers guided imports and scheduled updates for supported sources. Bring in Dataslayer data, files, spreadsheets, or connected systems, then organize the result in a workspace. The benefit is a repeatable place to prepare and reuse reporting data.
Problem: access gets harder to manage as accounts grow
Agencies and in-house teams need clear boundaries between clients, brands, and colleagues. Ad hoc sharing makes it harder to know which data each person should use.
Atlas uses workspaces and assigned roles to organize access. Keep each client or brand in the right context and give people responsibilities appropriate to their work. That creates a clearer process for onboarding collaborators and sharing analysis.
Problem: reporting shows a change without helping you investigate it
An export tells you what happened in one reporting period. Explaining a change may require earlier periods, other channels, and business outcomes that live elsewhere.
Atlas keeps prepared data available for repeated analysis and provides dashboards and analytical signals. With the relevant history and consistent measures in place, the team can examine a change in context instead of starting again from disconnected files.
A useful pilot tests these outcomes: a repeatable import, understandable access, and a faster path from a changed metric to a question worth investigating.
How does AI help turn reporting into analysis?
Atlas uses AI to help create dashboards and explain analytical patterns in prepared data. The useful outcome is a clearer starting point for investigation.
Suppose acquisition costs rise in a client report. The next useful question is where the change is concentrated: one country, a particular campaign, or several channels. Examining those dimensions alongside the recent trend gives your team a more focused place to start.
Atlas can surface signals such as trends, anomalies, and underperforming segments, and explain the evidence in business language. The team can then inspect the underlying measures, consider campaign changes, and decide whether an action is justified.
That work depends on usable data. An uploaded file with one week of results cannot answer questions about a year of performance. Bring the history, dates, and business definitions needed for the question you actually want to answer.
How Atlas makes AI-assisted analysis more reliable
Atlas is designed as an analytics engine that grounds AI analysis in the structure and meaning of your data. It profiles columns, uses semantic inference to distinguish dimensions from measures, detects how metrics should be aggregated, and validates generated SQL before presenting an answer.
This matters when a metric is a ratio. For example, ROAS should be calculated as SUM(revenue) / SUM(spend), not by averaging row-level ROAS values. Atlas can also use time-series patterns, anomaly detection, correlations, and segment comparisons to identify changes that deserve attention.
The AI can help propose dashboards, visualizations, formulas, hierarchies, and business questions. Analysts retain access to SQL and the underlying measures, so the team can inspect the evidence, add business context, and decide what to do next.
Can you keep using Data Studio and your other tools?
You can evaluate Atlas while keeping familiar reporting tools in use. Atlas has its own dashboards and offers ways to connect prepared data to external products.
For Power BI, this CSV route is a web-data connection rather than Microsoft's native DirectQuery mode. Check your destination, data volume, and refresh requirements during the demo so the proposed workflow matches the way your team works.
Once you know how reports will consume the data, the next decision is what to move first.
How can you move from BigQuery to Atlas?
Start with selected data and one reporting workflow, then validate the result before expanding. Atlas supports guided imports of BigQuery tables or views, so a pilot can include existing history.
1. Choose a real reporting problem
Pick one client, brand, or campaign report. Define what is slowing the team down and what a better workflow would achieve.
2. Bring the relevant data
Validate BigQuery access, select the tables or views, and choose the destination workspace. Set supported update schedules and bring any additional sources needed for the pilot.
3. Check the result
Compare row counts, dates, important measures, and refresh results. Confirm that permissions match the people who will use the data.
4. Connect and measure
Build an Atlas dashboard or connect a Data Studio report after validation. Compare preparation time, support needs, and total operating cost with your existing workflow.
Importing data does not automatically rewrite existing reports or their calculations. Keep the current reporting path available while you validate the new one. BigQuery costs can continue for storage, queries, or synchronization while that service remains in use.
When is Atlas a good fit, and when should you keep BigQuery?
Atlas is worth evaluating when marketing reporting is the priority and the team wants imports, access, dashboards, and analysis in one product. BigQuery may remain the better fit when your broader data platform already serves those needs well.
Compare the full proposal: product and connector costs, hosting, migration effort, administration, and tools you will retain. Atlas should earn its place by improving your actual workflow.
Frequently asked questions
These answers clarify the main product, migration, and cost questions before you choose a pilot.
What is Atlas Business Intelligence?
Atlas Business Intelligence is a marketing data warehouse and analytics product integrated with Dataslayer. It brings connected data, workspaces, dashboards, and AI-assisted analysis into one environment for agencies and marketing teams.
How are Atlas, Dataslayer, and Data Studio different?
Dataslayer connects and moves marketing data. Atlas stores and organizes that data for reporting and analysis. Data Studio, formerly Looker Studio, is a reporting interface you can continue using alongside Atlas.
Can I keep my existing Data Studio reports?
You can keep existing reports in use while evaluating Atlas. Connecting them to Atlas requires the configured Atlas connector and deliberate updates to data sources, followed by checks of fields, calculations, and results. Importing BigQuery data does not automatically reconnect reports.
Can Atlas import my existing BigQuery data?
Yes. Atlas supports guided imports of selected BigQuery tables or views after access is validated. Choose the destination workspace and configure supported updates. Validate imported data before switching reports; BigQuery charges can still apply while BigQuery remains in use.
Do I need SQL skills to use Atlas?
You do not need SQL to view prepared dashboards or use reporting assets that are already configured. Initial data preparation and advanced analysis may need specialist input. Analysts can use SQL when the workflow requires it.
How does Atlas use AI?
Atlas supports AI-assisted dashboard creation and analysis of patterns in prepared data, including trends, anomalies, and underperforming segments. AI explains analytical evidence in business language. The team still checks the data, adds context, and decides what action to take.
How should I compare Atlas and BigQuery costs?
Compare the complete reporting workflow: the Atlas proposal, hosting, connectors, migration work, and any retained tools against your BigQuery costs and administration time. Use a pilot to measure the difference with your own data and team.
Make your next reporting question easier to answer
If you are comparing marketing reporting software for a team that already uses BigQuery and Data Studio, bring one real report, one data source, and the task that slows you down. Book an Atlas demo to see the import, reporting connection, and analysis workflow with your team's needs in mind.
