Business Intelligence Overview

Business Intelligence (BI)

• A broad field that encompasses the collection and analysis of information to assist decision making and assess organizational performance
• Applied to enhance a variety of business questions for measurement and analysis
• Areas of application include process cost, efficiency, quality, customer satisfaction, customer profitability, achievement of key performance indicators, and risk management
• Factors which increased interest in BI:
  • The increasing size and complexity of modern organizations, requiring BI capabilities to answer fundamental business questions
  • Legal requirements that enforce companies to understand the “whole of business"
  • The pursuit of competitive advantage
• To effectively deliver BI, organizations need to design and implement a data architecture

Complete data architecture components

• Enterprise data flow architecture (EDFA)
• A logical data architecture
• A business or per department structure

Layers/Components of Enterprise Data Flow Architecture (EDFA)

• Presentation/Desktop Access Layer: The topmost layer where end users directly deal with information
  • Includes desktop tools (e.g., spreadsheets), direct querying tools, reporting and analysis suites, and purpose-built applications (e.g., balance scorecards, digital dashboards)
  • Includes Power Users who have the ability to build their own queries and reports, and Admin Users who have greater access to the system
  • Other regular or normal users interact with data in predefined ways
• Data Source Layer: The lowest layer which houses sources of information; includes operational data, external data and nonoperational data
• Core Data Warehouse (DW): Where all or most data of interest to an organization is captured and organized for reporting and analysis
  • Normally instituted as a large relational database
  • DW: should hold normalized data for flexibility in dealing with complex and changing
  • Data Mart: Subset of DW that focuses on specific areas of the business, e.g., customer data, sales data
• Data Integration and Transformation Layer: Where data from different sources are integrated and transformed into a consistent format
  • ETL: Extract, Transform, Load - process for moving data between different data sources
• Data Quality Layer: Ensures the accuracy, completeness, consistency, timeliness, and validity of data
• Analytical Processing Layer: Provides the ability to perform complex queries and analyses across the enterprise data warehouse
• Reporting and Visualization Layer: Presents data in an understandable and insightful format
• Metadata Repository Layer: Metadata are the data about data. It provides comprehensive scope across data as they flow between various layers. This layer also includes documenting, transformation, and validation rules

This quiz delves into the essential concepts of Business Intelligence (BI), focusing on its role in decision-making and performance assessment within organizations. Explore the components of data architecture necessary for effective BI implementation and understand the various applications and factors influencing BI adoption in modern enterprises.