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There are 4 modules in this course
Businesses run on data, and data offers little value without analytics. The ability to process data to make predictions about the behavior of individuals or markets, to diagnose systems or situations, or to prescribe actions for people or processes drives business today. Increasingly many businesses are striving to become “data-driven”, proactively relying more on cold hard information and sophisticated algorithms than upon the gut instinct or slow reactions of humans.
This course will focus on understanding key analytics concepts and the breadth of analytic possibilities. Together, the class will explore dozens of real-world analytics problems and solutions across most major industries and business functions. The course will also touch on analytic technologies, architectures, and roles from business intelligence to data science, and from data warehouses to data lakes. And the course will wrap up with a discussion of analytics trends and futures.
This first module exposes and explains key data and analytics concepts from Big Data to data warehousing to natural language query, and everything in-between. Next we will explore various analytic techniques, types of visualizations, and types of analytics solutions. The course will continue with identifying and learning about key data and analytics roles and organization structures, including chief data and analytics officers, data scientists, and analytics centers of excellence. Alternatives to direct hiring, such as outsourcing and crowdsourcing, will also be covered. Finally, the course will scrutinize analytic trends and futures.
What's included
18 videos9 readings2 assignments
Show info about module content
18 videos•Total 98 minutes
Course Introduction•1 minute
Meet Instructor Doug Laney•2 minutes
Learn on Your Terms•1 minute
Lesson 1-1 Overview of Analytics•6 minutes
Lesson 1-2 Beyond Basic Business Intelligence•6 minutes
Lecture 1-6-3 Business Function-Specific Analytics•9 minutes
9 readings•Total 240 minutes
Syllabus•20 minutes
About the Discussion Forums•10 minutes
Glossary•20 minutes
Brand Descriptions•20 minutes
Update Your Profile•10 minutes
Online Education at Gies College of Business•10 minutes
Congratulations on Completing the Course!•10 minutes
Module 1 Overview•20 minutes
Module 1 Readings•120 minutes
2 assignments•Total 60 minutes
Orientation Quiz•30 minutes
Module 1 Graded Quiz•30 minutes
Module 2 Industry and Business Function Analytics
3 hours to complete
Module details
Over the course of the module, you will also see how data and analytics in each of these organizations can be used in similar ways, in similar business functions. Accordingly, you will appreciate that to be truly data-driven, you need not only look to examples in your own industry, but, also learn and apply analytics concepts from organizations in other fields.
What's included
11 videos2 readings1 assignment
Show info about module content
11 videos•Total 66 minutes
Module 2 Overview•2 minutes
Lecture 2-1 Banking and Financial Institution Examples•7 minutes
Lecture 2-7 Government and the Public Sector Examples•10 minutes
Lecture 2-8 Healthcare Examples•6 minutes
Lecture 2-9 Sports and Entertainment Examples•5 minutes
Lecture 2-10 Other Examples•8 minutes
2 readings•Total 110 minutes
Module 2 Overview•20 minutes
Module 2 Readings•90 minutes
1 assignment•Total 30 minutes
Module 2 Graded Quiz•30 minutes
Module 3 Staffing and Organizing for Analytics
4 hours to complete
Module details
In this module you will learn a bunch of crucial analytical roles and the emergence of new roles in organizations from the C-suite down to various analyst roles. You will take a brief look at the job descriptions and the responsibilities. You will also put yourself in either a job seeker’s or a recruiter’s shoes to see what kind of skill sets are the most important and which position fits you the best. For example, it will introduce you to the three core skills of the data scientist and the crucial soft skills required to be a successful data scientist.
What's included
11 videos2 readings1 assignment1 peer review
Show info about module content
11 videos•Total 74 minutes
Module 3 Overview•0 minutes
Lecture 3-1 The Chief Information Officer (CIO)•4 minutes
Lecture 3-2 The Chief Data Officer (CDO)•7 minutes
Lecture 3-3 Chief Digital Officer•3 minutes
Lecture 3-4 The Chief Analytics Officer (CAO)•3 minutes
Lecture 3-5 The Data Scientist•9 minutes
Lecture 3-6 Data Scientist Soft Skills•5 minutes
Lecture 3-7 Other Analytics Related Roles•10 minutes
Lecture 3-8 The Analytics Center of Excellence•4 minutes
Lecture 3-9 Analytics Consulting and Crowdsourcing•6 minutes
Interview with Graham Waller•23 minutes
2 readings•Total 80 minutes
Module 3 Overview•20 minutes
Module 3 Readings•60 minutes
1 assignment•Total 30 minutes
Module 3 Graded Quiz•30 minutes
1 peer review•Total 60 minutes
Module 3 Peer Reviewed Assignment•60 minutes
Module 4 Analytics Success Today and Tomorrow
3 hours to complete
Module details
This module explores telling stories, through data, that connect emotionally with your audience. It will also review examples and figures that make the concept easy to understand. You will learn the major do’s and don’ts of creating dataviz and rules that lead to the clear depiction of your findings. This unit specifically focuses on Dona Wong’s guidelines for good data visualization and charts. The last leg of Module 4 teaches the three tests that help you improve your visualization. In the final step of dataviz execution, you will learn the McCandless Method for presenting visualizations. This five-step process produces the most effective communication of the graphics to your audience.
What's included
14 videos4 readings1 assignment1 plugin
Show info about module content
14 videos•Total 53 minutes
Lecture 4-1-1 Analytics Maturity•3 minutes
Lecture 4-1-2 Analytics Maturity Levels•4 minutes
Lecture 4-1-3 Key Maturity Disciplines•3 minutes
Lecture 4-2 Analytics Success Factors•12 minutes
Lecture 4-3-0 Analytics Trends and Futures•1 minute
Lecture 4-3-1 Analytics as a Corporate Strategy•3 minutes
Lecture 4-3-2 Data Literacy•3 minutes
Lecture 4-3-3 Valuing Information Assets•5 minutes
Lecture 4-3-4 A Data Science and AI Ethical Code of Conduct•5 minutes
Lecture 4-3-5 Continuous Intelligence•3 minutes
Lecture 4-3-6 Reinventing, Digitalizing and Eliminating Business Offerings•2 minutes
Lecture 4-3-7 AI will Struggle to Scale in the Organization•3 minutes
Lecture 4-3-8 Most Analytic Insights Will Fail to Deliver Business Value•3 minutes
Lecture 4-3-9 Quantum Computing Will Start to Outperform Traditional Analytics Computing•4 minutes
4 readings•Total 100 minutes
Module 4 Overview•20 minutes
Module 4 Readings•60 minutes
Congratulations on completing the course!•10 minutes
Get Your Course Certificate•10 minutes
1 assignment•Total 30 minutes
Module 4 Graded Quiz•30 minutes
1 plugin•Total 15 minutes
End of Course survey•15 minutes
Earn a career certificate
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Taking this course by University of Illinois Urbana-Champaign may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.
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Prepare for a degree
Taking this course by University of Illinois Urbana-Champaign may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
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Learner reviews
4.6
282 reviews
5 stars
71.63%
4 stars
21.27%
3 stars
4.96%
2 stars
0.70%
1 star
1.41%
Showing 3 of 282
I
IK
5·
Reviewed on Aug 8, 2019
Excellent course, very practical and gives students new ideas by highlighting what other companies are doing.
J
JM
4·
Reviewed on Jun 25, 2022
Liked everything except the peer-reviewed assignment. Four reviews is too many. It took several weeks to get submissions to review after I had finished everthing else.
C
CJ
5·
Reviewed on Mar 14, 2021
For a person who does not have much knowledge about Data Analytics, it was very well explained and presented.
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