.svg){kind=icon}
.svg){kind=icon}
What is Business Intelligence?
Business Intelligence ( BI for short) is the umbrella term for the processes, technologies, and methods that companies use to collect and process data and transform it into information relevant to decision-making.
BI typically encompasses the entire data chain: from data integration from ERP, CRM, production, and external sources, through a central data warehouse or lakehouse, to reports, dashboards, and self-service analytics.
BI is closely related to data warehousing, reporting, analytics, and, increasingly today, AI. In practice, these areas overlap—BI is the umbrella term and includes the analytics layer.
For small and medium-sized businesses, a robust BI foundation is a prerequisite for even meaningfully launching AI projects. Without clean, centrally available data, AI initiatives fail right from the start due to data issues.
Best Practices for BI
These six principles make the difference between uncontrolled dashboard proliferation and a productive BI landscape:
- Metrics First: What should be measured? Define KPIs before selecting tools.
- Single Source of Truth: One central definition per metric—prevents data chaos.
- Take an iterative approach: Integrate one business unit at a time—not all at once.
- Prioritize data quality: Without clean data, there can be no reliable reporting.
- Promote adoption: Training and clear responsibilities encourage usage.
- Incorporate AI from the start: Build the data model in a way that enables machine learning and forecasting.
Common Mistakes in BI Projects
We see these pitfalls particularly often:
- Tool-centric: Buy the tool first, then figure out what it’s for—it almost always ends up gathering dust in a closet.
- Too Big a “Big Bang”: Implementing everything at once—this approach fails time and again.
- Conflicting Metrics: Every department calculates things differently—trust in the numbers plummets.
- Lack of Ownership: Without someone in charge, reports and dashboards fall by the wayside.
- AI treated as an add-on: Setting up BI and AI separately—instead of integrating them architecturally.
Traditional BI vs. Self-Service vs. AI-powered BI
Three approaches that aren’t mutually exclusive—but all coexist in modern landscapes:
- Traditional BI: Standard reports generated by Controlling and IT—for regular KPIs and management reports.
- Self-Service BI: Business units build their own exploratory analyses—with clear governance boundaries.
- AI-powered BI: Forecasts, “chat with data,” and anomaly detection—for everyone, in natural language.
BI & AI for Your Decisions
In a free initial consultation, we’ll analyze your data landscape and identify the key metrics and business areas with the greatest BI potential—including a concrete implementation proposal.
As a BI and AI partner for small and medium-sized businesses, we’ll transition your BI landscape from the world of Excel to a future-proof, AI-powered data platform—with clear governance and rapid business value.
What We Offer
- BI Consulting — Designing your BI landscape from strategy through reporting.
- Data Warehouse & Reports — Implementation using Fabric and Power BI.
- AI Consulting — Integrating BI with forecasting and AI assistants.
- Copilot Consulting — Integrating Copilot effectively into your BI processes.
