Download GTU (Gujarat Technological University) MBA (Master of Business Administration) 2019 Summer 2nd Sem 3529201 Business Analytics Ba Previous Question Paper
Seat No.: ________ Enrolment No.___________
GUJARAT TECHNOLOGICAL UNIVERSITY
MBA ? SEMESTER 2 ? EXAMINATION ? SUMMER 2019
Subject Code: 3529201 Date:09/05/2019
Subject Name: Business Analytics (BA)
Time: 10:30 AM To 01:30 PM Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1 Explain the following concepts.
(a) Define Business Analytics.
(b) What is a Database?
(c) Define Data Warehouse.
(d) Give examples of Machine Generated Data.
(e) What is Social Media? Also give some examples.
(f) What is a Dashboard?
(g) Name different data models for OLAP.
14
Q.2 (a) Explain framework for Data Driven Decision Making in Business. 07
(b) You belong to a big corporate house who has invested heavily in IT
infrastructure. Explain different categories of IT application users you
will find in your company with examples.
07
OR
(b) You are a new manager in a conventional company. You want to
convince the top management how IT can improvise the business.
Prepare a report to highlight the purposes of using IT in Business.
07
Q.3 (a) Explain the difference between OLTP and OLAP systems. 07
(b) We generate, process and use digital data every day. Explain with proper
examples which are the different sources of digital data.
07
OR
Q.3 (a) Explain characteristics of structured data. 07
(b) What are the practical challenges faced while storing unstructured data. 07
Q.4 (a) What is Big data? Describe characteristics of big data. 07
(b) Explain practical application of data mining in business. 07
OR
Q.4 (a) Explain the types of machine learning. 07
(b) Explain the application of social media analytics in business. 07
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Page 1 of 2
Seat No.: ________ Enrolment No.___________
GUJARAT TECHNOLOGICAL UNIVERSITY
MBA ? SEMESTER 2 ? EXAMINATION ? SUMMER 2019
Subject Code: 3529201 Date:09/05/2019
Subject Name: Business Analytics (BA)
Time: 10:30 AM To 01:30 PM Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1 Explain the following concepts.
(a) Define Business Analytics.
(b) What is a Database?
(c) Define Data Warehouse.
(d) Give examples of Machine Generated Data.
(e) What is Social Media? Also give some examples.
(f) What is a Dashboard?
(g) Name different data models for OLAP.
14
Q.2 (a) Explain framework for Data Driven Decision Making in Business. 07
(b) You belong to a big corporate house who has invested heavily in IT
infrastructure. Explain different categories of IT application users you
will find in your company with examples.
07
OR
(b) You are a new manager in a conventional company. You want to
convince the top management how IT can improvise the business.
Prepare a report to highlight the purposes of using IT in Business.
07
Q.3 (a) Explain the difference between OLTP and OLAP systems. 07
(b) We generate, process and use digital data every day. Explain with proper
examples which are the different sources of digital data.
07
OR
Q.3 (a) Explain characteristics of structured data. 07
(b) What are the practical challenges faced while storing unstructured data. 07
Q.4 (a) What is Big data? Describe characteristics of big data. 07
(b) Explain practical application of data mining in business. 07
OR
Q.4 (a) Explain the types of machine learning. 07
(b) Explain the application of social media analytics in business. 07
Page 2 of 2
Q.5
CASE STUDY:
Today?s customers are more empowered and connected than ever before.
Using channels like mobile, social media and e-commerce, customers can
access just about any kind of information in seconds. This informs what
they should buy, from where and at what price. Based on the information
available to them, customers make buying decisions and purchases
whenever and wherever it?s convenient for them.
At the same time, customers expect more. For example, they expect
companies to provide consistent information and seamless experiences
across channels that reflect their history, preferences and interests. More
than ever, the quality of the customer experience drives sales and
customer retention. Given these trends, marketers need to continuously
adapt how they understand and connect with customers. This requires
having data-driven insights that can help you understand each customer?s
journey across channels.
But consumers today interact with companies through multiple
interaction points ? mobile, social media, stores, e-commerce sites and
more. This dramatically increases the complexity and variety of data
types you have to aggregate and analyze. With big data engineering
technologies, you can bring together all of your structured and
unstructured data into application like Hadoop and analyze all of it as a
single data set, regardless of data type. The analytical results can reveal
totally new patterns and insights you never knew existed ? and aren?t
even conceivable with traditional analytics. Data engineering is capable
of correlating customer purchase histories and profile information, as
well as behavior on social media sites. Data-driven customer insights are
critical to tackling challenges like improving customer conversion rates,
personalizing campaigns to increase revenue, predicting and avoiding
customer churn, and lowering customer acquisition costs.
Considering the above provide answers to complex online retail questions
such as:
(a) What?s really happening across every step in the customer journey?
07
(b) What are the Key Performance Indicators (KPIs) that you will monitor
for large online retail operations?
07
OR
Q.5 (a) How you will successfully use web analytics and social media analytics
for better customer engagement.
07
(b)
Explain different type of analytics you will use in your whole retail
supply chain.
07
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This post was last modified on 19 February 2020