Initial Postings: Read and reflect on the assigned readings for the week. Then post what you thought was the most important concept(s), method(s), term(s), and/or any other thing that you felt was worthy of your understanding in each assigned textbook chapter.
Your initial post should be based upon the assigned reading for the week, so the textbook should be a source listed in your reference section and cited within the body of the text. Other sources are not required but feel free to use them if they aid in your discussion.
Also, provide a graduate-level response to each of the following questions:

Based on what you have read in Chapter 1, can you tell me how data analytics applies to your current or future role?  What value can data analytics bring to your position? Please share your thoughts.

[Your post must be substantive and demonstrate insight gained from the course material. Postings must be in the student’s own words – do not provide quotes!] 
[Your initial post should be at least 200+ words and in APA format (including Times New Roman with font size 12 and double spaced).The Roles of Data and Predictive Analytics in Business
Chapter 1
© 2019 McGraw-Hill Education. All rights reserved. Authorized only for instructor use in the classroom. No reproduction or distribution without the prior written consent of McGraw-Hill Education.

Learning Objectives
Explain how predictive analytics can help in business strategy formulation.
Distinguish structured from unstructured data.
Differentiate units of observation.
Outline a data-generating process.
Describe the primary ways that data analysis is used to aid business performance.
Discriminate between lead and lag information.
Discriminate between active and passive prediction.
Recognize questions pertaining to business strategy that may utilize (active) predictive analytics.

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© 2019 McGraw-Hill Education.

Defining Data & Data Uses in Business
Data
A collection of information
Database
Organized collection of data that firms use for analysis
Business analytics
The use of data analysis to aid in business decision making
Predictive analytics
The use of data analysis to designed to form predictions about future, unknown, events or outcomes

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© 2019 McGraw-Hill Education.

Business Strategy
Plan of action designed by a business practitioner to achieve a business objective
Business objectives include profit maximization, enhanced employee satisfaction, etc.
Examples of action include pricing decisions, advertising campaigns, and methods of employee compensation

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© 2019 McGraw-Hill Education.

Predictive Analytics for Business Strategy
With no data, strong theoretical model is often not enough to predict effective business strategies
Sound theoretical arguments coupled with data becomes a strong tool to predict effective business strategies
Predictive analytics is an ideal complement to create a successful business strategy

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© 2019 McGraw-Hill Education.

Data Features
Structured Data
Data with well-defined units of observation which can be classified and structured in the form of a spreadsheet.
An example:

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© 2019 McGraw-Hill Education.

Data Features
Unstructured Data
Any data that cannot be classified and structured.
An example:

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© 2019 McGraw-Hill Education.

The Unit of Observation
The entity for which information has been collected
Crucial component of structured data
Tells us the way the in which the information in a dataset varies
Answers the questions: What, Where, Who, When?
Four main groupings: cross-sectional data, pooled cross-sectional data, time-series data, and panel data

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© 2019 McGraw-Hill Education.

Data Types
Cross-Sectional Data
Data that provide a snapshot of information at one fixed point in time.
An example:

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© 2019 McGraw-Hill Educati




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