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
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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 that every member, from executives to front-line staff, has a role
in ensuring data integrity.
Continuous Improvement TDQM is built on the principle of continuous improvement.
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
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 Warehouse (EDW) The Enterprise Data Warehouse (EDW) is a
centralized warehouse that provides a comprehensive view of an organization by
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
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