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.
Business Analytics Executive Overview
일리노이대학교 어버너-섐페인캠퍼스이 강좌에 대하여
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일리노이대학교 어버너-섐페인캠퍼스
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.
석사 학위 취득 시작
This 강좌 is part of the 100% online Master of Science in Accountancy (iMSA) from 일리노이대학교 어버너-섐페인캠퍼스.
If you are admitted to the full program, your courses count towards your degree learning.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 6시간 필요
Course Overview & Module 1 Analytics Beyond the Spreadsheet
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.
완료하는 데 6시간 필요
17개 동영상 (총 97분), 7 개의 읽기 자료, 2 개의 테스트
17개의 동영상
Meet Instructor Doug Laney1m
Lesson 1-1 Overview of Analytics5m
Lesson 1-2 Beyond Basic Business Intelligence6m
Lesson 1-3-1 The Analytics Continuum7m
Lesson 1-3-2 Analytic Output6m
Lecture 1-3-3 Basic Analytic Techniques2m
Lecture 1-4 Analytic Graphical Representation (Visualization)11m
Interview with Kevin Hartman14m
Lecture 1-5-1 Key Analytics Concepts to Know (Data Literacy)32
Lecture 1-5-2 Data, What Data? (Sources of Data)5m
Lecture 1-5-3 Where to Put the Data and How to Get it There?8m
Lecture 1-5-4 Analytic Methods, Techniques and Concepts6m
Lecture 1-5-5 Other Data Concepts4m
Lecture 1-6-1 Purpose-Built Analytic Solutions17
Lecture 1-6-2 Data-specific Analytic Solutions4m
Lecture 1-6-3 Business Function-Specific Analytics8m
7개의 읽기 자료
Syllabus20m
About the Discussion Forums10m
Glossary20m
Brand Descriptions20m
Update Your Profile10m
Module 1 Overview20m
Module 1 Readings2시간
2개 연습문제
Orientation Quiz30m
Module 1 Graded Quiz30m
완료하는 데 3시간 필요
Module 2 Industry and Business Function Analytics
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.
완료하는 데 3시간 필요
11개 동영상 (총 66분), 2 개의 읽기 자료, 1 개의 테스트
11개의 동영상
Lecture 2-1 Banking and Financial Institution Examples6m
Lecture 2-2 Insurance Examples3m
Lecture 2-3 Retail Examples7m
Lecture 2-4 Manufacturing, Consumer Package Goods Examples5m
Lecture 2-5 Energy Sector Examples7m
Lecture 2-6 Telecommunications Examples3m
Lecture 2-7 Government and the Public Sector Examples10m
Lecture 2-8 Healthcare Examples6m
Lecture 2-9 Sports and Entertainment Examples4m
Lecture 2-10 Other Examples7m
2개의 읽기 자료
Module 2 Overview20m
Module 2 Readings1시간 30분
1개 연습문제
Module 2 Graded Quiz30m
완료하는 데 4시간 필요
Module 3 Staffing and Organizing for Analytics
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.
완료하는 데 4시간 필요
11개 동영상 (총 74분), 2 개의 읽기 자료, 2 개의 테스트
11개의 동영상
Lecture 3-1 The Chief Information Officer (CIO)3m
Lecture 3-2 The Chief Data Officer (CDO)7m
Lecture 3-3 Chief Digital Officer2m
Lecture 3-4 The Chief Analytics Officer (CAO)3m
Lecture 3-5 The Data Scientist8m
Lecture 3-6 Data Scientist Soft Skills4m
Lecture 3-7 Other Analytics Related Roles9m
Lecture 3-8 The Analytics Center of Excellence4m
Lecture 3-9 Analytics Consulting and Crowdsourcing5m
Interview with Graham Waller23m
2개의 읽기 자료
Module 3 Overview20m
Module 3 Readings1시간
1개 연습문제
Module 3 Graded Quiz30m
완료하는 데 3시간 필요
Module 4 Analytics Success Today and Tomorrow
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.
완료하는 데 3시간 필요
15개 동영상 (총 57분), 3 개의 읽기 자료, 1 개의 테스트
15개의 동영상
Lecture 4-1-2 Analytics Maturity Levels3m
Lecture 4-1-3 Key Maturity Disciplines3m
Lecture 4-2 Analytics Success Factors11m
Lecture 4-3-0 Analytics Trends and Futures41
Lecture 4-3-1 Analytics as a Corporate Strategy2m
Lecture 4-3-2 Data Literacy3m
Lecture 4-3-3 Valuing Information Assets4m
Lecture 4-3-4 A Data Science and AI Ethical Code of Conduct4m
Lecture 4-3-5 Continuous Intelligence2m
Lecture 4-3-6 Reinventing, Digitalizing and Eliminating Business Offerings2m
Lecture 4-3-7 AI will Struggle to Scale in the Organization3m
Lecture 4-3-8 Most Analytic Insights Will Fail to Deliver Business Value3m
Lecture 4-3-9 Quantum Computing Will Start to Outperform Traditional Analytics Computing4m
Gies Online Programs3m
3개의 읽기 자료
Module 4 Overview20m
Module 4 Readings1시간
Congratulations!10m
1개 연습문제
Module 4 Graded Quiz30m
검토
BUSINESS ANALYTICS EXECUTIVE OVERVIEW의 최상위 리뷰
S 제공2020년 7월 29일
A good course that introduces us to the trends / organization roles etc. A few more real-life examples with the actual set up and organization of the data/analytics department would have helped more.
EC 제공2020년 11월 1일
I thoroughly enjoyed the course. It has given me sufficient insights to move forward to the data science and analytics fields. The real-world examples are on point for each lesson.
EM 제공2019년 6월 19일
Definetly a source for present day information and upcoming trends in analytics. This professor definetly can offer a new comers guide to data analytics.
S 제공2020년 5월 15일
knowledgeable and a lot of insight towards the role of analytics in the business world and in a nations economy and its different elements.
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