Data Analysis for Business

Data Analysis for Business

This course is part of Data & Finance for the future Specialization

Instructor: Fabiana Cherubim Bortoleto

Access provided by Siemens

5 modules

Gain insight into a topic and learn the fundamentals.

27 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

27 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

20 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the Data & Finance for the future Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 5 modules in this course

The Data Science in Business course equips participants with the tools and techniques to leverage data for informed decision-making in the corporate world. Covering data analysis, and data-driven strategies, this course empowers individuals to extract valuable insights, enhance business processes, and drive strategic initiatives through data-driven approaches. Combining theoretical foundations with hands-on applications, learners will be well-prepared to navigate the intersection of data science and business analytics.

This week, you’ll learn the impact of data analysis and its elements on business. Also, the diferences of variables, measurement scales and types of data analysis.

What's included

5 videos5 readings4 assignments1 discussion prompt

5 videos Total 24 minutes

Information, Database and Statistics 7 minutes
Types of Variable and Measurement Scales 5 minutes
Types and Sources of Data 5 minutes
Types of Data Analysis 3 minutes
Example in Excel of a Database Construction 5 minutes

5 readings Total 127 minutes

My Bio 2 minutes
Syllabus 10 minutes
Week 1 - Slide deck 45 minutes
Introduction 30 minutes
Data, data analysis, and descriptive statistics 40 minutes

4 assignments Total 45 minutes

Types of variables 10 minutes
Information, database and statistic 10 minutes
Types of data 10 minutes
Data Analysis 15 minutes

1 discussion prompt Total 10 minutes

Why being data-driven is so important? 10 minutes

This week, you’ll learn how to tell something through data. Managing data in graphs and tables, and the principals pitfalls about data visualization.

What's included

7 videos2 readings4 assignments1 discussion prompt

7 videos Total 62 minutes

Tables 7 minutes
Charts for Categorical Variables 4 minutes
Charts for Numerical Variables - Part 1 2 minutes
Charts for Numerical Variables - Part 2 2 minutes
Other Types of Chart and the Pitfalls of DCOVA 7 minutes
Excel Example 5 minutes
Recording of Data Analysis for Business Live Session on 22-03-17 20:07:20 [21:09] 35 minutes

2 readings Total 135 minutes

Week 2 - Slide deck 45 minutes
Week 2 reading: Data Visualization 90 minutes

4 assignments Total 45 minutes

Tables 10 minutes
Chart 10 minutes
Numerical Charts 10 minutes
Pitfalls of DCOVA 15 minutes

1 discussion prompt Total 10 minutes

What is a good data visualization? 10 minutes

This week, you’ll learn how to deal with data and how to describe data in terms of some parameters: the differences between dispersion and central tendcy measures.

What's included

8 videos2 readings4 assignments1 discussion prompt

8 videos Total 30 minutes

Measures of Central Tendency 5 minutes
Measures of Variation and Shape 5 minutes
Skewness and Kurtosis 2 minutes
Quartiles and Percentiles 3 minutes
Boxplot 1 minute
Population and Sample 3 minutes
Covariance and Correlation 3 minutes
Excel Example 7 minutes

2 readings Total 120 minutes

Week 3 - Slide deck 45 minutes
Week 3 reading: Descriptive Measures 75 minutes

4 assignments Total 55 minutes

Central Tendency 15 minutes
Shape 10 minutes
Boxplot 15 minutes
Population and sample 15 minutes

1 discussion prompt Total 10 minutes

Sampling 10 minutes

In this week you will see some probability principles which are linked with datasets and data visualization. Also, statistical principles which are applied in data analysis.

What's included

7 videos5 readings4 assignments1 discussion prompt

7 videos Total 85 minutes

Probability Basics for Inferential Statistics 9 minutes
Main probability distributions: uniform, binomial, Poisson, normal, and exponential 11 minutes
Sampling and Confidence Interval 5 minutes
Confidence Interval for the Mean 10 minutes
Hypothesis Testing Fundamentals 5 minutes
T and Z Test for the Mean 19 minutes
Recording of Data Analysis for Business Live Session on 22-03-31 20:01:35 [04:00] 25 minutes

5 readings Total 225 minutes

Week 4 - Slide deck 45 minutes
Probability Concepts and their analysis 30 minutes
Probability fundamentals - part 2 30 minutes
Sampling and Confidence Interval 90 minutes
Hypothesis testing 30 minutes

4 assignments Total 55 minutes

Probability 15 minutes
Probability 10 minutes
Confidence Interval 10 minutes
Hypothesis testing 20 minutes

1 discussion prompt Total 10 minutes

Predictive vs. Analytics 10 minutes

In this week you will see topics in linear regressions. Regression analysis is used to investigate the relationship between two or more variables. Often used in predicting some characteristic using one or more independent variables .