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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.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Aprox. 17 horas para completar

Inglés (English)

Subtítulos: Inglés (English)

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Aprox. 17 horas para completar

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana

1

Semana 1

6 horas para completar

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.

6 horas para completar

17 videos (Total 97 minutos), 7 lecturas, 2 cuestionarios

17 videos

Course Introduction39s

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)32s

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 Solutions17s

Lecture 1-6-2 Data-specific Analytic Solutions4m

Lecture 1-6-3 Business Function-Specific Analytics8m

7 lecturas

Syllabus20m

About the Discussion Forums10m

Glossary20m

Brand Descriptions20m

Update Your Profile10m

Module 1 Overview20m

Module 1 Readings2h

2 ejercicios de práctica

Orientation Quiz10m

Module 1 Graded Quiz30m

Semana

2

Semana 2

3 horas para completar

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.

3 horas para completar

11 videos (Total 66 minutos), 2 lecturas, 1 cuestionario

11 videos

Module 2 Overview2m

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

2 lecturas

Module 2 Overview20m

Module 2 Readings1h 30m

1 ejercicio de práctica

Module 2 Graded Quiz30m

Semana

3

Semana 3

5 horas para completar

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.

5 horas para completar

11 videos (Total 74 minutos), 2 lecturas, 2 cuestionarios

11 videos

Module 3 Overview28s

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

2 lecturas

Module 3 Overview20m

Module 3 Readings1h

1 ejercicio de práctica

Module 3 Graded Quiz30m

Semana

4

Semana 4

3 horas para completar

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.

3 horas para completar

15 videos (Total 57 minutos), 3 lecturas, 1 cuestionario

15 videos

Lecture 4-1-1 Analytics Maturity2m

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 Futures41s

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

3 lecturas

Module 4 Overview20m

Module 4 Readings1h

Congratulations!10m

1 ejercicio de práctica

Module 4 Graded Quiz30m

Preguntas Frecuentes

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?

You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
Is financial aid available?

Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

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