Choosing the right Business Intelligence tool is one of the technology decisions with the greatest impact on a company’s daily operations. It is not just about which tool is “better” in the abstract, but which one fits your current ecosystem, your users’ profile, your budget, and your customization needs.
In this article we compare the three main options we evaluate with our clients: Power BI (Microsoft), Looker Studio (Google), and custom-built dashboards. There is no sponsor or affiliation. These are conclusions based on real implementations in Soamee projects.
The BI landscape in 2026
The BI tools market has matured enormously. Power BI dominates in Microsoft environments. Looker Studio (formerly Data Studio) has gained traction as a free option integrated with Google Cloud. And the custom option (React + D3.js or charting libraries) remains preferred when you need full control or embedding in your own product.
The reality is that many companies end up using a combination of several tools. But starting with the wrong tool has a cost: dashboard migration, user retraining, and months of lost productivity.
Power BI: the enterprise standard
What it is
Power BI is Microsoft’s Business Intelligence tool. It includes Power BI Desktop (report creation), Power BI Service (cloud publishing and collaboration), and Power BI Embedded (integration into your own applications).
When to choose it
- Your company already uses Microsoft 365 and Azure
- You need complex data modeling with DAX
- End users are business analysts who want to create their own reports
- You require data governance with workspaces, roles, and RLS
- You want to embed dashboards in your application (Power BI Embedded)
Advantages
- Integrated Microsoft ecosystem: Native connection with Excel, SharePoint, Dynamics, Azure SQL, Dataverse
- Powerful DAX: The formula language enables complex calculations on the data model
- Dimensional modeling: Power Query and the tabular model allow transforming and relating data from multiple sources
- Enterprise governance: Workspaces, deployment pipelines, RLS, audit logs, sensitivity labels
- Embedded API: JavaScript SDK to integrate reports in any web application
- Huge community: Thousands of custom visuals, training resources, and available consultants
Disadvantages
- Complex licensing: Power BI Pro (EUR 9.99/user/month), Premium per user (EUR 18.70/user/month), Premium per capacity (from EUR 4,675/month). Embedded with separate Azure capacities
- Microsoft ecosystem dependency: Works best within the Microsoft world. Outside it, the experience degrades
- Visual customization limitations: Although custom visuals exist, flexibility does not reach custom code level
- Performance with large datasets: DirectQuery can be slow. Import has size limits. Premium mitigates but at high cost
- Somewhat dated UX: The creation interface is not as modern as Looker or more recent tools
Estimated cost (2026)
| Scenario | Estimated monthly cost |
|---|---|
| Team of 10 with Power BI Pro | EUR 100/month |
| Team of 50 with Premium per user | EUR 935/month |
| SaaS with Embedded (A2 capacity) | EUR 1,400/month |
| Enterprise with Premium P1 | EUR 4,675/month |
Looker Studio (Google): the accessible option
What it is
Looker Studio (formerly Google Data Studio) is Google’s free tool for creating dashboards connected to multiple data sources. Not to be confused with Looker (Google Cloud’s enterprise platform, which is a different product with corporate pricing).
When to choose it
- Your primary source is Google Analytics 4, Google Ads, or BigQuery
- You need reporting dashboards to share with clients or stakeholders
- Budget is limited and you do not want license costs
- Reports are relatively simple (no complex DAX modeling needed)
- You want real-time collaboration Google Docs-style
Advantages
- Free: No license cost for creators or viewers
- Native Google integration: GA4, BigQuery, Google Ads, Google Sheets, YouTube Analytics without configuration
- Easy sharing: Like a Google Doc. Anyone with the link can view the dashboard
- Community connectors: Hundreds of connectors to external sources (Salesforce, HubSpot, Facebook Ads, etc.)
- BigQuery as backend: For advanced analysis with SQL without limitations
- Email scheduling: Automatic sending of PDF reports by email
Disadvantages
- No real data modeling: No semantic model like DAX or LookML. Calculations are done field by field
- Limited performance: With large datasets or complex queries, dashboards become slow
- Limited visual customization: Fewer formatting and design options than Power BI
- No real governance: No workspaces, deployment pipelines, or native RLS
- No professional embedding: No embedding SDK comparable to Power BI Embedded
- Google dependency: If Google deprecates the product (as it has with others), there is no direct alternative
Estimated cost (2026)
| Scenario | Estimated monthly cost |
|---|---|
| Looker Studio alone | EUR 0 (free) |
| + BigQuery (100GB queries/month) | EUR 5-50/month |
| + Premium community connectors | EUR 30-200/month |
| Looker Enterprise (different product) | From EUR 5,000/month |
Custom dashboard: total control
What it is
Dashboards built to order with frontend frameworks (React, Vue) and visualization libraries (D3.js, Recharts, ECharts, Plotly). The backend can be any API, database, or data warehouse.
When to choose it
- You need to embed dashboards in your SaaS product with your brand
- UX/interaction requirements exceed what Power BI or Looker offer
- You want total control over performance and experience
- Data is sensitive and cannot leave your infrastructure
- The dashboard IS the product (not a complement)
Advantages
- Total control: Pixel-perfect design, custom interactions, animations, full responsive
- Optimizable performance: You can optimize queries, caching, lazy loading, table virtualization
- No license cost: Only development and hosting costs
- Native embedding: It is your code, it integrates wherever you want without limitations
- No vendor dependencies: You do not depend on Microsoft or Google decisions
- Sensitive data secure: Data never leaves your infrastructure
Disadvantages
- High development cost: Building a dashboard from scratch costs significantly more than configuring Power BI
- Continuous maintenance: Every new visualization, filter, or feature requires development
- No self-service: Business users cannot create their own reports without development
- Longer time-to-market: Weeks or months vs hours or days with standard tools
- Technical expertise required: You need developers with data visualization experience
Estimated cost (2026)
| Scenario | Estimated cost |
|---|---|
| MVP dashboard (3-5 views) | EUR 15,000-30,000 (one-time) |
| Complete dashboard (10-15 views) | EUR 40,000-80,000 (one-time) |
| Embedded analytics platform | EUR 80,000-200,000 (one-time) |
| Monthly maintenance | EUR 2,000-5,000/month |
| Hosting (cloud) | EUR 200-1,000/month |
Decision matrix
| Criterion | Power BI | Looker Studio | Custom |
|---|---|---|---|
| Initial cost | Low | Zero | High |
| Recurring cost | Medium | Low | Medium |
| Time-to-market | Fast | Very fast | Slow |
| Visual customization | Medium | Low | Total |
| Data modeling | Excellent | Basic | Per development |
| Self-service (users) | Excellent | Good | None |
| Embedding in product | Good | Limited | Native |
| Governance | Excellent | Basic | Per development |
| Data scalability | Good | Medium | Total |
| Vendor dependency | High (Microsoft) | High (Google) | None |
Concrete scenarios
Scenario 1: SaaS startup wanting analytics for its users
Recommendation: Custom
If dashboards are part of your product’s value (your users pay to see their data), the custom option is the only one offering the necessary experience. Power BI Embedded is an alternative, but the UX always feels “embedded” and customization limitations are noticeable.
In InfoAdex, the dashboards ARE the product. Clients (agencies, advertisers) pay to access advertising investment data. A generic-looking Power BI dashboard would not have generated the same value perception.
Scenario 2: Marketing department needing reporting
Recommendation: Looker Studio
If your team already uses Google Analytics, Google Ads, and Google Sheets, Looker Studio is the obvious choice. Free, easy to use, and dashboards can be shared with a link. You do not need IT to maintain it.
Scenario 3: Medium-sized company with multiple departments
Recommendation: Power BI
If you have data from finance, operations, sales, and HR that need consolidation with governance (who sees what), Power BI offers the best balance between functionality and cost. Business analysts can create their own reports without depending on IT.
Scenario 4: ESG/sustainability reporting for third parties
Recommendation: Custom or Power BI Embedded
In Cawa, ESG reports for brands need impeccable presentation with the client’s brand. A beautiful PDF generated from custom dashboards is more appropriate than a link to a generic Power BI report.
The hybrid approach
In practice, most mature companies end up with a hybrid approach:
- Power BI or Looker for internal reporting (finance, operations, marketing)
- Custom dashboards for the client-facing product
- BigQuery or Snowflake as the central data warehouse feeding both
This approach leverages each tool’s strengths. Internal reporting does not need to be pixel-perfect (Power BI is more than enough). Product dashboards need to be impeccable (custom is necessary). And the data warehouse is the single source of truth that guarantees consistency.
Common mistakes we have seen
1. Starting with custom when Power BI was enough
We have seen companies spend EUR 80,000 on custom dashboards that would have been solved with Power BI Pro at EUR 10/user/month. If users are internal and customization requirements are moderate, do not reinvent the wheel.
2. Scaling Looker Studio beyond its capabilities
Looker Studio works well for 5-10 simple dashboards. When you have 50 dashboards with complex data, performance degrades and the lack of governance becomes chaos. At that point, you need to migrate to Power BI or custom.
3. Underestimating custom dashboard maintenance
Development cost is just the beginning. Every new metric, every new filter, every design change requires a developer. If you do not have an internal technical team to maintain it, recurring costs can far exceed Power BI licenses.
4. Not defining KPIs before choosing a tool
The tool is the how, not the what. If you do not know what business questions you want to answer, any tool will give you beautiful dashboards that nobody uses. Define KPIs first, then choose the tool.
Conclusion
There is no universal BI tool. The correct choice depends on your current technology ecosystem, your users’ profile, your budget, and whether dashboards are an internal complement or part of your product’s value.
The general rule we follow:
- If dashboards are internal and you do not need embedding: Power BI (Microsoft) or Looker Studio (Google) depending on your ecosystem
- If dashboards are part of your product: Custom
- If you are starting and budget is zero: Looker Studio to validate which metrics matter, then invest in the definitive solution
At Soamee we help our clients make this decision from analysis, not from hype. If you need guidance on which BI approach is right for your company, we offer a free consultation where we evaluate your specific case and propose the optimal architecture.