+1(978)310-4246 credencewriters@gmail.com
  

Description

Read chapter 1 of the textbook.
Write a summary of Chapter 1Practical Analytics
Chapter 1: Data Analytics Overview
Chapter 1 Learning Objectives
After completing this chapter, you will be able to:

Describe what data analytics is

Explain why the study of analytics is important

Recap examples of analytics in real-world situations, particularly business scenarios

Describe the structure of the model company GBI,
▪ Get familiar with GBI employees, who appear in many of the examples in this text
© 2014 Epistemy Press All rights reserved. / Page 2
Outline

What is Data Analytics?

Why Study Data Analytics?

Applications of Analytics

Analytics Methodology

Introduction to Global Bike, Inc.

Summary
© 2014 Epistemy Press All rights reserved. / Page 3
Overview of Analytics Techniques
Analytics Techniques
Exploration and
Reporting
• Slicing/dicing
• Multidimensional
analysis
• Reporting
Knowledge Discovery
• Forecasting
• Descriptive data
mining
• Predictive data mining
© 2014 Epistemy Press All rights reserved. / Page 4
Visualization
• Charts
• Dashboards
• Advanced
visualization
What is Data Analytics?

Data Analytics can answer these and other questions:
▪ What has happened in the past?
▪ Why did it happen?
▪ What could happen in the future? With what certainty?
▪ What actions can we take now to support or prevent certain events from happening in the future?
▪ Can some of the actions resulting from our discoveries be automated?
© 2014 Epistemy Press All rights reserved. / Page 5
What is Data Analytics?

It is a process that involves
▪ Gathering data that are sometimes not in a usable form
▪ Cleaning up the data to make them usable
▪ Loading the data into storage models
▪ Manipulating them to discover the information
© 2014 Epistemy Press All rights reserved. / Page 6
Data Analytics Takes Us from Data to Decision
© 2014 Epistemy Press All rights reserved. / Page 7
Data Analytics – The Convergence of Vocabulary

Statistics is used in data analytics

Computer science improves capabilities to perform data
analytics

Domain knowledge in every area has its unique
vocabulary and analytical applications
▪ Examples:
▪ Medicine and each area within medicine
▪ Public services
▪ Sports and Entertainment
▪ Business
© 2014 Epistemy Press All rights reserved. / Page 8

By line of business

By functional area within a business

By geographical location, and so on…
Data Science and Analytics
© 2014 Epistemy Press All rights reserved. / Page 9
Why Study Analytics?

Demand for employees who understand and can analyze data

Huge growth in the amount of data available

Analytics can provide strategic advantages to an organization
© 2014 Epistemy Press All rights reserved. / Page 10
Who Uses Analytics?
© 2014 Epistemy Press All rights reserved. / Page 11

Data analysis is performed at many levels in the
organization

Analytics is performed and used by individuals who may
not have formal training
Examples of Business Analytics Examples

Retail – pricing, timing or pricing strategies, discounts, product placement, up-selling and cross-selling of
products

Manufacturing – demand forecasting, production planning

Marketing – targeted marketing

Supply chain – vendor selection, optimizing distribution costs

Customer service/help desk – customized service

Forecasting and budgeting

Audit and analysis of internal controls – risk assessment

Governments – resource allocations, tax compliance

Utilities – demand forecasting, management of power supplies

Investors – determine which investments are acceptable
© 2014 Epistemy Press All rights reserved. / Page 12
Other Examples of Data Analytics Applications

Science – in just about every area of science, analytics are important for interpretation of data

Medicine – many applications: risk factor identification, treatment plans, disease prevention and control

Sports – player acquisitions, analysis of player performance

Fraud Prevention – credit card fraud

Law Enforcement – criminal activity patterns, resource allocation
© 2014 Epistemy Press All rights reserved. / Page 13
Analytics Methodology within a Framework
© 2014 Epistemy Press All rights reserved. / Page 14
Global Bike Inc. (GBI)

Company History
▪ John Davis and Peter Weiss are co-CEOs
▪ Operations in the United States (US) and Germany (DE)

The Business
▪ Professional and prosumer cyclist market
▪ GBI sells high quality bicycles and cycling accessories
▪ Sells to retailer partners, not to the consumer directly
© 2014 Epistemy Press All rights reserved. / Page 15
GBI Organizational Structure
© 2014 Epistemy Press All rights reserved. / Page 16
GBI Business Structure
© 2014 Epistemy Press All rights reserved. / Page 17
GBI Products
© 2014 Epistemy Press All rights reserved. / Page 18
GBI Customers
© 2014 Epistemy Press All rights reserved. / Page 19
GBI Vendors (Suppliers)
© 2014 Epistemy Press All rights reserved. / Page 20
GBI – Sample Business Process
© 2014 Epistemy Press All rights reserved. / Page 21
Master Data and Transactional Data at GBI

Master data are business entities
▪ Customers, vendors, products, employees, fixed assets…
▪ Transactional data are data about an event
▪ Sales, purchases, pay employees, collect payments…
▪ GBI uses an integrated system (ERP)
© 2014 Epistemy Press All rights reserved. / Page 22
Some GBI Employees and Their Business Questions
Nina Kane – U.S. Sales Manager
▪ How do I anticipate and compete with new competitors for market share in the prosumer bike market?
▪ What data do I need to evaluate sales, discover trends, and identify opportunities?
▪ How can I motivate my sales team?
▪ Is there value in organizing invitation-only promotional events for our loyal customers?
▪ Are there any delays in our supply chain that have led to lost sales?
Donna Vasant – Business Analyst
▪ Are there new markets for GBI products?
▪ Are there new products that GBI could bring to the market? How about bike-integrated video cameras, body-monitoring
devices, and a bike trolley to carry pets, babies, and groceries, especially in urban areas?
▪ Is an electric bike a viable and profitable new product?
▪ Are internet sales the future for high-end bikes (instead of or in addition to retail stores)? Will internet sales compete with our
loyal customers (distributors)?
© 2014 Epistemy Press All rights reserved. / Page 23
Some GBI Employees and Their Business Questions
Jessi Mard – Controller
▪ Are profit margins in line with expectations?
▪ Are operational efficiencies affecting profitability?
▪ How can we encourage customers to pay more quickly?
▪ How well can we forecast cash flows and other key accounting indicators?
▪ Are our internal accounting controls effective?
Peter Pollard – Production Manager
▪ How can we become more efficient in the manufacturing processes?
▪ Is the quality of raw materials affecting production?
▪ Can the manufacturing plant meet sales demand?
▪ Is the manufacturing facility set up to reduce unnecessary material movements and encourage efficiency in the production
process?
© 2014 Epistemy Press All rights reserved. / Page 24
Some GBI Employees and Their Business Questions
Tony Liu – Shipping Personnel
▪ What percentage of orders are shipping within 24 hours of order receipt?
Bruce Hewlett – Shipping Manager
▪ How many orders have not shipped within 24 hours of receipt and why?
▪ How many products were damaged during the packing and shipping process?
▪ Did any orders ship to the incorrect customer or address?
▪ How many orders were damaged by the shipping company?
▪ How many orders did not arrive at the customer’s site on time due to shipping problems and how can those problems be
avoided in the future?
© 2014 Epistemy Press All rights reserved. / Page 25
Summary

Data analytics is the process of gathering, cleaning, storing, and manipulating data to provide insights

The data analytics process converts raw data to information to knowledge to wisdom and finally a decision

Analytic skills are in high demand and help companies compete

There are many applications of data analytics. We will focus on business applications

Enablers of analytics include technology, infrastructure, tools, and techniques

Some benefits of analytics are value, performance, safety, and longevity.

People, controls, and training are the foundation of the analytics cycle

You should now be familiar with Global Bike, Inc. (GBI) the model company used throughout the rest of the
chapters
© 2014 Epistemy Press All rights reserved. / Page 26

Purchase answer to see full
attachment

  
error: Content is protected !!