DITF304 MBA BUSINESS INTELLIGENCE AND TOOLS

Description

SESSION	MAY 2024
PROGRAM	MASTER OF BUSINESS ADMINISTRATION (MBA)
SEMESTER	III
COURSE CODE & NAME	DITF304 – BUSINESS INTELLIGENCE AND TOOLS

 

 

Assignment Set – 1

 

 

1. What is the significance of Business Intelligence in improving decision-making within businesses, and how are Business Intelligence tools applied across various industries to enhance operational strategies? Can you illustrate with any one example or case study?

Ans 1.

Significance of Business Intelligence in Business Decision-Making

Enhanced Decision-Making: Business Intelligence (BI) plays a crucial role in enhancing decision-making processes within organizations. By transforming data into actionable insights, BI tools enable managers to make informed decisions quickly and accurately. This is essential in today’s fast-paced business environment, where timely and data-driven decisions can determine a company’s success or failure.

Strategic Planning: BI tools assist in strategic planning by providing comprehensive analytics that reveal trends,

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2. What are the key principles and strategies involved in Total Data Quality Management (TDQM)? How does TDQM enhance data reliability, accuracy, and usability within organisations?

Ans 2.

Key Principles of Total Data Quality Management (TDQM)

Data Quality as a Way of Life One of the core principles of Total Data Quality Management (TDQM) is viewing data quality as an integral aspect of the organizational culture. This principle advocates for continuous attention to data quality throughout the organization, emphasizing

 

 

3. Explain the fundamental concepts of data mining and its advantages and disadvantages. Provide examples of how data mining has been applied in different industries.

Ans 3.

Fundamental Concepts of Data Mining

Data mining involves several fundamental concepts that empower organizations to extract valuable insights from vast datasets. At its core, data mining starts with pattern discovery, a process aimed at identifying hidden patterns and correlations among large volumes of data, which might include identifying prevalent trends, sequences, or relationships that aren’t immediately obvious. Another essential concept is classification, where data is analyzed and organized into predefined categories. This technique is particularly useful in scenarios like email filtering or

 

 

Assignment Set – 2

 

 

4. Discuss the different types of business models used in data warehousing. Provide examples of industries or scenarios where each business model is commonly employed.

Ans 4.

Types of Business Models in Data Warehousing

Data warehousing involves organizing and managing large volumes of data from various sources to enable effective decision-making and data analysis. Several business models are commonly used in data warehousing, each serving different business needs and scenarios.

Enterprise Data

 

5. Explain why it’s crucial to identify data sources during data extraction. How does accurate and reliable data extraction support effective decision-making and data analysis?”

Ans 5.

Identifying data sources during the data extraction phase is crucial because it lays the foundation for all subsequent data processing and analysis activities. In the vast landscape of data-driven decision-making, the integrity and usability of data are highly dependent on the initial steps of data extraction. This process involves not just gathering data, but also ensuring that it comes from reliable and relevant sources. When data sources are clearly identified and validated, organizations can ensure that the data they are using is accurate, complete, and trustworth

           

6. Analyse the strategies involved in developing a Business Intelligence solution. Explore how a well-defined strategy and roadmap contribute to the success of a BI initiative.

Ans 6.

Strategies in Developing a Business Intelligence Solution

Developing a robust Business Intelligence (BI) solution involves several key strategies that ensure the effective collection, integration, analysis, and presentation of data.

Needs Assessment and Requirement Gathering The first strategy is to conduct a thorough needs assessment and requirement gathering. This involves engaging stakeholders to understand their data needs, business objectives, and key performance indicators (KPIs). By clearly defining what the organization seeks to achieve with BI, the solution can be tailored to provide relevant insights and