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What is Business Intelligence? - Explanation & Meaning

Learn what business intelligence (BI) is, how dashboards and data visualization work, and why BI is essential for data-driven decision making.

Definition

Business intelligence (BI) encompasses the strategies, technologies, and tools organizations use to analyze raw data and convert it into actionable insights for better business decisions. BI makes data accessible through dashboards, reports, and visualizations.

Technical explanation

A BI architecture consists of multiple layers: data sources (databases, APIs, files), data integration (ETL/ELT pipelines), data storage (data warehouse or data lake), a semantic layer (data models and KPI definitions), and the presentation layer (dashboards and reports). Modern BI platforms like Power BI, Tableau, and Looker offer self-service capabilities enabling business users to perform analyses themselves without SQL knowledge. OLAP cubes (Online Analytical Processing) enable fast multidimensional analysis. Embedded analytics integrates BI functionality directly into business applications. In 2026, AI plays an increasingly important role in BI: natural language querying lets users ask questions in plain language, while augmented analytics automatically detects patterns and anomalies. Real-time dashboards display live KPIs through streaming data integration. Data governance ensures reporting is reliable and consistent through standardized definitions and access control.

How MG Software applies this

MG Software builds custom BI solutions and dashboards for clients who want to turn data into action. We integrate data from diverse sources, design clear data models, and build interactive dashboards that provide real-time insight into business performance. Whether it is an embedded analytics solution in an existing application or a standalone dashboard environment, we make data accessible to everyone in the organization.

Practical examples

  • A retail chain building Power BI dashboards that display real-time sales data per location, including year-over-year comparisons and forecasts based on historical trends.
  • A SaaS company integrating embedded analytics into their platform, allowing customers to analyze their own usage data through interactive charts and filters.
  • A hospital using BI dashboards to visualize wait times, occupancy, and staffing to support operational decisions and improve patient experience.

Related terms

data engineeringdata lakedata privacysql injectioncompliance

Further reading

What is Data Engineering?What is a Data Lake?What is Data Privacy?

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Frequently asked questions

Business intelligence primarily focuses on descriptive analysis: what happened and what is happening now, through dashboards and standard reports. Data analytics goes further with diagnostic (why), predictive (what will happen), and prescriptive (what should we do) analyses. BI is the foundation on which advanced analytics is built.
The best BI tool depends on your needs. Power BI is strongly integrated with the Microsoft ecosystem and cost-effective. Tableau excels in advanced visualizations. Looker is ideal for organizations that want to manage BI as code. Metabase is an excellent open-source option. The choice depends on budget, technical knowledge, and integration requirements.
A basic dashboard can be realized in a few weeks. A full BI implementation with data integration, data modeling, and multiple dashboards typically takes two to six months, depending on the number of data sources, the complexity of the data model, and organizational readiness for change.

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