Business Intelligence Systems

Business Intelligence Overview

• Definition: Business Intelligence (BI) refers to the information that supports decision-making in organizations.

• Key Benefits:

  • Enhances understanding of business operations.

  • Improves decision-making capabilities.

  • Facilitates easy access and sharing of information.

  • Mitigates risks of bottlenecks.

  • Aids in identifying wasteful processes in the system.

• Real-time Analysis: Enables quick navigation and timely data analysis.

Growing Importance of Data

• Digital Data Explosion: By 2025, an estimated 175 zettabytes of data will exist, necessitating effective mining to extract valuable insights for BI.

Understanding Business Intelligence

• Key Components:

  • Data Handling: BI relies on the extraction of data from various sources including operational databases and social data.

  • BI Enablers: Technology, People, Culture are fundamental to the implementation of effective BI systems.

Business Intelligence vs. Business Analytics

• Business Intelligence (BI): Utilizes existing data for operational management and assists in decision-making.

• Business Analytics (BA): Focuses on statistical methods and tools to predict future trends and develop growth strategies.

Organizational Needs for BI

• Organizations generate vast amounts of operational data that reveal patterns and relationships which can aid in management, planning, and forecasting.

Key Questions in BI Study

1. How do organizations leverage BI systems?

2. Utilization of data warehouses and data marts for data acquisition.

3. Techniques for processing BI data.

4. Alternative methods for publishing BI insights.

BI Process: Three Primary Activities

1. Acquire Data:

   • Sources: operational databases, social data, purchased data, employee knowledge.

   • Cleanse by organizing and relating data.

2. Perform Analysis:

   • Techniques include reporting, data mining, machine learning, etc.

3. Publish Results:

   • Delivery methods include web servers, report servers, and knowledge management systems.

BI System Components

• Data Sources:

  • Internal/Operational Databases

  • External/Purchased Databases

  • Social Data

  • Employee Knowledge

• Applications: The necessary software that enables BI functionalities.

Data Transformation and Mining

• Data Processing Cycle:

  1. Acquire Transaction Data.

  2. Data Transformation: Convert raw data into organized formats.

  3. Data Mining: To uncover hidden patterns and insights.

Big Data and AI Integration

• Concepts:

  • Involves managing vast datasets (petabytes and larger).

  • Combines various disciplines: Technology, Psychology, Sociology, Statistics.

  • Requires advanced computational tools and sophisticated professionals.

Reporting and Data Mining Tools

• Reporting Tools: Essential for summarizing data into understandable formats.

• Data Mining Tools: Used for comprehensive analysis of data through techniques like regression analysis, cluster analysis, and association detection.

Advanced Data Analysis Techniques

1. Regression Analysis: Useful for predicting dependent variables influenced by independent variables.

2. Statistical Analysis: Involves correlation and variance analysis for forecasting.

3. Cluster Analysis: Segments data into distinct groups based on similarities.

4. Decision Trees: Hierarchical models predicting classifications based on criteria.

5. Association Detection: Identifies relationships and patterns in purchasing behavior.

Knowledge Management (KM)

• Key Aspects:

  • Emphasizes sharing, creating, capturing, and distributing knowledge.

  • Supports decision-making and enhances collaborative work environments.

• Systems: Technologies supporting the KM processes include databases and collaborative tools.

Benefits of Knowledge Management

• Increases profits by leveraging employee knowledge.

• Enhances customer service through rapid response times.

• Fosters innovation and streamlines operations.