All Questions

  1. What is business intelligence ? Explain Architecture of BI? List benefits of BI. (10 Marks)
  2. What is Datawarehouse ? Explain various architectures of DW ? Which data warehousing architecture is the best? Why? List the benefits of data warehouses (10 Marks)
  3. Describe the three steps of the ETL process. What are ROLAP, MOLAP, and HOLAP?. How.do they differ from OLAP? (10 Marks)
  4. What are the characteristics of an effective performance measurement system? How Does BPM differ from BI? How are they the same? List the major BPM processes. (10 Marks)
  5. List and briefly define at least two classification techniques. Briefly describe any one general algorithm used in decision trees. (10 Marks)
  6. What is data mining? Explain in detail about data mining. Explain various Analytics in BI. What are the major application areas for data mining? (10 Marks)
  7. Write any 3 short notes on the following (10 Marks)
    1. Statistical Analytics
    2. Business Reports
    3. Data Preprocessing
    4. Neural networks
    5. Decision Tree
  1. What is business intelligence ? Explain Architecture of BI? List benefits of BI. (10 Marks)

    1. What is Business Intelligence (BI)?

      1. Business Intelligence (BI) refers to the technologies, processes, and tools that help organizations collect, analyze, and present business data to support decision-making. BI transforms raw data into meaningful and actionable insights, enabling organizations to make informed decisions, improve efficiency, and gain a competitive edge.
      2. Key Functions of BI:
        1. Data collection and integration.
        2. Data analysis and visualization.
        3. Reporting and dashboard creation.
        4. Predictive and prescriptive analytics.

    2. Architecture of Business Intelligence

      1. The architecture of BI is a framework that outlines how data flows from various sources to end-users in the form of actionable insights. It typically consists of the following layers:

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      2. Data Sources:

        1. Description: Raw data is collected from various sources such as databases, ERP systems, CRM systems, social media, and IoT devices.
        2. Examples: Transactional databases, spreadsheets, cloud storage, and external APIs.

      3. Data Integration (ETL - Extract, Transform, Load):

        1. Description: Data is extracted from multiple sources, transformed into a consistent format, and loaded into a data warehouse or data mart.
        2. Tools: ETL tools like Informatica, Talend, and Microsoft SSIS.

      4. Data Warehouse:

        1. Description: A centralized repository where integrated data is stored for analysis. It supports historical data storage and complex queries.
        2. Types: Enterprise Data Warehouse (EDW), Data Marts (department-specific warehouses).

      5. Data Analysis and Processing:

        1. Description: Data is processed and analyzed using various techniques such as OLAP (Online Analytical Processing), data mining, and machine learning.
        2. Tools: OLAP tools (e.g., Microsoft Analysis Services), data mining tools (e.g., IBM SPSS), and machine learning frameworks (e.g., TensorFlow).

      6. Data Visualization and Reporting:

        1. Description: Processed data is presented in a user-friendly format using dashboards, charts, and reports.
        2. Tools: Tableau, Power BI, QlikView, and SAP BusinessObjects.

      7. End-User Access:

        1. Description: Decision-makers access the analyzed data through dashboards, reports, or mobile apps.
        2. Users: Executives, managers, analysts, and operational staff.

    3. List of Benefits of Business Intelligence

      Benefit Explanation
      Better Decision Making Enables data-driven decisions based on accurate and real-time insights.
      Improved Operational Efficiency Identifies inefficiencies and streamlines processes.
      Enhanced Customer Experience Understands customer behavior and preferences to tailor services.
      Competitive Advantage Analyzes market trends to stay ahead of competitors.
      Data Visibility & Transparency Centralized data improves transparency and accountability.
      Faster Reporting Automated reports and dashboards reduce reporting time.
      Forecasting and Trend Analysis Predictive analytics helps forecast future trends and demands.
      Cost Reduction Identifies areas where costs can be minimized or optimized.
      Compliance and Risk Management Helps monitor compliance and assess risks through real-time analytics.
  1. What is Datawarehouse ? Explain various architectures of DW ? Which data warehousing architecture is the best? Why? List the benefits of data warehouses (10 Marks)
    1. What is a Data Warehouse (DW)?
      1. A Data Warehouse is a centralized repository that stores large volumes of structured data collected from different sources (such as transactional systems, relational databases, and external sources). It is specifically designed for querying, reporting, and data analysis, rather than transaction processing.
    2. Key Characteristics:
      1. Subject-oriented
      2. Integrated
      3. Time-variant
      4. Non-volatile
    3. Purpose of DW:
      1. Supports decision support systems (DSS)
      2. Enables historical analysis
      3. Provides high performance for analytical queries
    4. Various Architectures of Data Warehousing
      1. There are three main types of Data Warehouse architectures:
      2. Single-Tier Architecture
        1. Description:
          1. Involves a single layer that integrates data from multiple sources.
          2. Tries to minimize data redundancy.
          3. Often used for operational databases but not suitable for large-scale analytics.
        2. Drawbacks:
          1. Lacks separation between operational and analytical processing.
          2. Poor performance for complex queries.
      3. Two-Tier Architecture
        1. Description:
        2. Advantages:
        3. Limitations:
      4. Three-Tier Architecture (Most Widely Used)
    5. Which Architecture is Best and Why?
    6. Benefits of Data Warehouses