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Introduction
The Module Four resources will provide you with a deeper understanding of how data is used by business organizations to address common challenges or problems. By the end of this module, you will be able to answer the following:
· What types of data exist?
· What types of analytics and methods do analysts have in their toolkits?
· What are the six stages of the data analytics lifecycle (DAL)?
· What is a data analyst’s role in each stage of the DAL?
Video:
Qualitative & Quantitative Research – An Introduction opens in new window
(8:52)
Watch this video to learn about the differences between qualitative and quantitative data and the appropriate times to use each. This video includes examples of each type of data and how it is used by business organizations.
Reading:
Data Analytics for IT Networks: Developing Innovative Use Cases,
Chapter 4 opens in new window
In this Shapiro Library e-book, read from the section titled “Data Types and Measurement Considerations” up to the section titled “Key Performance Indicators.” In this reading, you will learn about various types of data along with examples of each. A text version of the images in this reading is available:
Accessing Data From Network Components Image Text Version opens in new window
.
Tip: This link will not take you directly to this section of the chapter. It is recommended that you use the keyboard shortcut (Ctrl + f) to search this e-book by typing in the section title you want to read. For more information, watch this short video on
How to Find Information on a Long Web Page opens in new window
(1:03).
Reading:
Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data,
Chapter 1 opens in new window
Read this Shapiro Library chapter to be introduced to big data analytics and how data analysis can be used in various industries to improve business operations, the customer experience, and much more. A text version of the images in this reading is available:
Introduction to Big Data Analytics Image Text Version opens in new window
.
Reading:
Subject Areas of Data Analytics opens in new window
Review this document to learn about subject areas of analytics including text analytics, fraud analytics, marketing analytics, people analytics, and manufacturing analytics. As you read, take note of the types of data that are collected for each area of analytics.
Reading:
Descriptive, Predictive, and Prescriptive Analytics Explained opens in new window
There are various ways that analysts can utilize data to address organizational problems. Read this article to get a brief overview of the types of analytics that are commonly used by analysts.
Reading:
Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data,
Chapter 2 opens in new window
The data analytics lifecycle (DAL) is an iterative cycle of stages used by analysts and organizations to address organizational challenges. Read this Shapiro Library e-book chapter to learn about each stage of the DAL. A text version of the images in this reading is available:
Module Four Data Analytics Lifecyle Image Text Version opens in new window
.
Reading:
Business Analytics Case Studies opens in new window
Review this webpage, which offers numerous case study examples of how analytics is used to address challenges. You may choose one of the trending cases to read about. As you read, consider the following:
· What is the business problem or challenge?
· What types of data are collected?
· What areas of analytics might be used to address the problem?
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