Which Business Intelligence (BI) tool fits industrial and machine data?
Business Intelligence tools are widely used in industrial environments, but they are often discussed as if one tool could cover every use case. In practice, industrial data brings very different requirements depending on whether the goal is monitoring, analysis, or decision support.
This article gives an overview of commonly used BI and visualization tools in industrial contexts, what they are designed for, and when they fit best when working with machine and industrial data.
Industrial data brings specific requirements
Industrial data is different from typical business data. It often includes:
- Time-series machine signals
- Events and alarms
- Production context such as shifts and orders
- Maintenance and service data
In practice, BI tools are rarely used on their own. Industrial environments typically rely on multiple tools, each serving a specific purpose. What a tool is designed to do matters more than how many features it offers.
Power BI
What it is
Power BI is a Business Intelligence platform developed by Microsoft, focused on data modeling, analysis, and reporting. Traditionally, it has been used primarily for historical and batch-oriented data rather than live operational data.
Over the past few years, this has started to change. With the introduction of services such as Microsoft Fabric, improved data streaming capabilities, and tighter integration with Azure services, it has become easier to bring near real-time and event-based data into the Power BI ecosystem. In industrial environments, this increasingly includes machine data delivered via protocols such as MQTT, often through an intermediate streaming or storage layer.
Power BI remains tightly integrated with the broader Microsoft ecosystem. Connections with tools such as Excel, Azure Data Explorer, and low-code platforms like Power Apps and Power Automate make it possible to embed insights into existing workflows or trigger follow-up actions outside the BI layer.
Where it fits best
Power BI works well when:
- Machine data is combined with ERP, quality, or maintenance data
- Near real-time insight is sufficient, rather than millisecond-level updates
- Historical analysis, trends, and KPIs are important
- Consistent data models and definitions are required
- Engineers, service teams, or management consume the insights
In this role, Power BI typically functions as a decision-support layer rather than a live monitoring interface.
Where it fits less well
Power BI is still less suitable for:
- High-frequency signal visualization
- Operator-focused live monitoring
- Direct machine interaction or control
Even with improved streaming options, it is not intended to replace dedicated monitoring or control systems.
Typical role:
Decision support and analytical reporting, increasingly supplemented with near real-time machine data.
Grafana
What it is
Grafana is an open-source visualization platform optimized for time-series data. It is commonly used together with industrial gateways, historians, and time-series databases.
Grafana is designed around live data, short-term trends, and alerting based on thresholds. It is widely adopted in environments where immediate visibility into machine behavior is required.
Where it fits best
Grafana fits well when:
- Real-time visibility is required
- Sensor values and machine states are central
- Alerting and fast detection of issues are important
- Users are operators or technical staff
It is often used while production is running, close to operations.
Where it fits less well
Grafana is less suited for:
- Complex data modeling
- Combining many business data sources
- Long-term KPI analysis and reporting
Typical role:
Operational monitoring and alerting.
Tableau
What it is
Tableau is a BI tool focused on visual exploration and interactive analysis. It is commonly used by analysts and engineers to explore data patterns and relationships in an ad-hoc way.
Where it fits best
Tableau works well when:
- Data exploration is the primary goal
- Users want flexibility to analyze data from multiple angles
- Visual pattern recognition is important
It is often used in analytical or improvement-focused settings rather than daily operations.
Where it fits less well
Tableau can become challenging when:
- Strong governance and standardization are required
- Many users depend on the same KPIs
- Central control over data models is needed
Typical role:
Exploratory analysis and insight discovery.
Looker
What it is
Looker is a BI platform built around a centralized semantic layer. It emphasizes consistency and governance by defining metrics and business logic in a shared model.
Where it fits best
Looker fits well when:
- A central data team defines metrics
- SQL-based data platforms are used
- Consistency across departments is critical
- Data maturity is relatively high
Where it fits less well
Looker is less common in:
- Smaller organizations
- Environments without a strong data engineering foundation
- Use cases focused on live monitoring
Typical role:
Governed analytics layer for mature data stacks.
What BI tools are not
It is important to be clear about what BI tools are not intended to replace. BI tools are not designed to function as shop-floor systems. They do not replace HMIs, SCADA systems, MES platforms, or real-time control systems.
Instead, BI tools support analysis and decision-making around operations. They help people understand what is happening across machines, lines, or sites, but they are not meant to control machines or replace operator interfaces.
Using multiple tools is common
In many industrial environments, the most effective setup combines more than one tool. A monitoring solution is typically used for real-time visibility during production, while a BI tool is used for analysis, reporting, and decision support before or after production runs.
Trying to force a single tool to cover all use cases often leads to compromises, either in clarity, usability, or performance.
Choosing the right tool
Rather than asking which BI tool is best in general, a more useful question is which type of data is being analyzed and who needs to use it. Once those aspects are clear, the appropriate tool choice usually becomes obvious.
About StriData
At StriData, we help machine manufacturers and production companies integrate, structure, and analyze industrial and machine data so it can be used effectively across monitoring, analysis, and reporting.
If you want to discuss how BI tools fit within your specific industrial data landscape, you can reach out to us via the contact page. We’re happy to explore your situation and share practical experience.
