# Business Analyst for Big Data

Unit 1 Individual Project
Assignment Details
Assignment Description
Scenario
Big Data is everywhere and various businesses around the world are driven by Big Data. However, while some businesses rely on Big Data for organizational decision making,
this does not mean that the implications and applications of Big Data are properly used to ensure optimal effectiveness for the organization
For this scenario, you have been appointed as the Business Analyst for Big D Incorporated charged with providing authoritative recommendations to the Board of Directors.
As the Business Analyst, the recommendation you provide will be based upon data calculated from statistical appropriate formulas. Be reminded that you are not the
company’s statistician yet the Business Analyst and therefore responsible for interpreting statistical data and making the appropriate recommendations.
Big D Incorporated was offered a series of business opportunities and it is your job as the Business Analyst to provide expert insight and justification for recommendations
regarding these potential prospects.
Assignment Details
Big D Incorporated has a business opportunity to provide two different types of information to a new client. As the Business Analyst, you are tasked to assess the financial
feasibility of this opportunity. The new client is a retailer and looking to expand their product offerings. However, they are requesting Big D Incorporated to assist in the
decision making process.
Prepare a presentation that addresses the following:
Explain the difference between nominal and ordinal data.
List 3 qualitative attributes of outdoor sporting goods that the client may want to ask consumers. Make sure 1 of the qualitative attributes is nominal.
For each ordinal attribute, assign names for the endpoints of a 5 point rating scale.
Explain the difference between interval and ratio data.
List 2 quantitative attributes of outdoor sporting goods that market researchers might want to measure.
Explain the difference between a population and a sample.
Williams, S., & Williams, N. (2007). The Profit Impact of Business Intelligence. Amsterdam: Elsevier/Morgan Kaufmann. Chapter 6. Business Intelligence In the
Read Bowerman, O’Connell, Orris, & Porter
Chapter 2: Descriptive Statistics: Tabular and Graphical Methods
Chapter 4: Probability
Chapter 5: Discrete Random Variables
Chapter 10: Statistical Inferences Based on Two Samples
Assignment Objectives
Apply methods of data aggregation and reduction to business data in a manner that reveals insight about underlying pattern and key parameters of the data set.
Determine appropriate sampling methodologies for business settings and situations.
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Assignment Overview
Type: Individual Project
Unit: Concepts and Terminology of Statistics Applied to Business Decision
Making
Points Possible: 120
Points Earned:
Deliverable Length: 5- 6 slides with speaker notes (100 150 words per
slide)
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