Learning Objectives

By the end of this chapter, you will be able to:

  • Define Business Intelligence (BI).
  • Describe the purpose of BI.
  • Identify the key technologies used in BI.

What is Business Intelligence (BI)?

Business Intelligence (BI) is a broad term that refers to the technologies, applications, and practices for the collection, integration, analysis, and presentation of business information. The purpose of BI is to support better business decision-making.

BI systems take large amounts of raw data and turn it into meaningful, actionable information. This is often presented to business users in the form of reports, dashboards, and data visualizations.

Key BI Technologies and Tools

  • Data Warehouses: BI systems rely on data warehouses to provide a central repository of clean, integrated, and historical data for analysis.
  • ETL (Extract, Transform, Load): The process used to get data from various source systems into the data warehouse.
  • Reporting and Querying Tools: Allow users to ask questions of their data and create reports.
  • Data Visualization and Dashboards: Tools like Tableau and Power BI are used to create interactive charts, graphs, and dashboards that allow users to explore the data visually.

Summary

Business Intelligence is the process of turning raw data into actionable insights that can guide business decisions. It encompasses the technologies and strategies used to analyze business information, with the ultimate goal of improving performance. Key components of a BI strategy include a data warehouse to store the data and visualization tools like dashboards to present the findings to decision-makers.

Key Takeaways

  • BI is the process of analyzing data to support better business decisions.
  • BI systems turn raw data into actionable information.
  • Key BI tools include data warehouses and data visualization dashboards.

Discussion Questions

  1. What is the difference between raw data and “actionable information”?
  2. How can a BI dashboard help a sales manager?
  3. Why is a data warehouse an important foundation for a BI system?