Name: Mohammed Varaliya

Roll No: 54

Questions

1. What is business intelligence? Explain the architecture of business intelligence.
2. Explain different phases in the development of business intelligence system.
3. Explain the cycle of BI Analysis.
4. Explain various tools used in business intelligence.
5. How does business intelligence benefit an organization?
6. How can companies ensure they are using data ethically in their BI practices?

1. What is Business Intelligence? Explain the Architecture of Business Intelligence

   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:

         

      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.

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2. Explain Different Phases in the Development of a Business Intelligence System

   1. The development of a Business Intelligence system typically follows a structured process, which can be divided into the following phases:
   2. Requirement Analysis:
      1. Objective: Understand the business needs and define the goals of the BI system.
      2. Activities: Conduct interviews with stakeholders, identify key performance indicators (KPIs), and document requirements.
   3. Data Collection and Integration:
      1. Objective: Gather data from various sources and integrate it into a centralized repository.
      2. Activities: Extract data from source systems, clean and transform data, and load it into a data warehouse.
   4. Data Modeling:
      1. Objective: Design the structure of the data warehouse to support efficient querying and analysis.
      2. Activities: Create dimensional models (e.g., star schema, snowflake schema), define relationships between tables, and optimize for performance.
   5. Data Analysis and Processing:
      1. Objective: Analyze the data to generate insights.
      2. Activities: Apply statistical analysis, data mining, and machine learning techniques to uncover patterns and trends.
   6. Data Visualization and Reporting:
      1. Objective: Present the analyzed data in a user-friendly format.
      2. Activities: Create dashboards, reports, and visualizations using BI tools like Tableau or Power BI.
   7. Deployment and Maintenance:
      1. Objective: Deploy the BI system and ensure its ongoing performance and relevance.
      2. Activities: Train users, monitor system performance, and update the system as business needs evolve.

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