Introduction to Data Analytics

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Introduction to Data Analytics

This course is part of multiple programs.

Instructor: Anke Audenaert

117,725 already enrolled

Included with

5 modules

Gain insight into a topic and learn the fundamentals.

1,082 reviews

Beginner level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

5 modules

Gain insight into a topic and learn the fundamentals.

1,082 reviews

Beginner level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

What you'll learn

Apply the data analysis process OSEMN to marketing data
Compare and contrast various data formats and their applications across different scenarios
Identify data gaps and articulate the strengths and weaknesses of collected data

Skills you'll gain

Category: Key Performance Indicators (KPIs)
Category: Data Manipulation
Category: Data Storytelling
Category: Data Quality
Category: Marketing
Category: Data Management
Category: Analytics
Category: Data Collection
Category: Data Cleansing
Category: Performance Metric
Category: Data Analysis
Category: Data Visualization
Category: Business Metrics
Category: Exploratory Data Analysis
Category: Data Modeling

Tools you'll learn

Category: Generative AI

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

20 assignments¹

AI Graded see disclaimer

Taught in English

Build your subject-matter expertise

This course is available as part of

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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 from Meta

There are 5 modules in this course

This course provides a practical understanding and framework for basic analytics tasks, including data extraction, cleaning, manipulation, and analysis. It introduces the OSEMN cycle for managing analytics projects and you'll examine real-world examples of how companies use data insights to improve decision-making.

By the end of this course you will be able to: • Formulate business goals, KPIs and associated metrics • Apply a data analysis process using the OSEMN framework • Identify and define the relevant data to be collected for marketing • Compare and contrast various data formats and their applications across different scenarios • Identify data gaps and articulate the strengths and weaknesses of collected data You don't need marketing or data analysis experience, but should have basic internet navigation skills and be eager to participate. Ideally you have already completed course 1: Marketing Analytics Foundation in this program.

This week, you will learn what data analytics are and what a data analyst does. You’ll be introduced to the OSEMN framework as well as important business metrics, KPIs and their value to a business.

What's included

13 videos5 readings4 assignments

13 videosTotal 49 minutes

Introduction to the Program2 minutes
Course Introduction Video2 minutes
Introduction to Anke Audenaert2 minutes
Weekly Introduction: What is Data Analytics?2 minutes
Introduction: the Power of Data3 minutes
What Is Data Analytics?9 minutes
What Does a Data Analyst Do?5 minutes
A Framework as a Helpful Tool1 minute
The OSEMN Framework4 minutes
Start with a Goal in Mind4 minutes
Understand the KPIs6 minutes
Using the OSEMN Framework: Example9 minutes
Weekly Review: Working with Data1 minute

5 readingsTotal 40 minutes

Introduction to Data Analytics Course Syllabus5 minutes
Join the Meta Marketing Analytics Community or the Meta Data Analyst Community!10 minutes
How to be Successful in this Program10 minutes
Data Analytics vs. Data Science10 minutes
OSEMN Framework Overview5 minutes

4 assignmentsTotal 90 minutes

Review Your Community Knowledge10 minutes
Practice Quiz: What is Data Analytics?15 minutes
Practice Quiz: The OSEMN Framework15 minutes
Graded Quiz: Working with Data50 minutes

In the second week you will learn how to discover different sources of data and how to evaluate their validity. You will also explore different data formats. You’ll begin to apply the OSEMN framework by learning the steps in the data cleaning process as well as how to handle missing or incorrect data in your datasets.

What's included

16 videos3 readings4 assignments

16 videosTotal 66 minutes

Introduction: Obtaining and Scrubbing Data1 minute
It's a Data World2 minutes
Where to Look for Data8 minutes
Common Data Formats5 minutes
Sampled Data8 minutes
First and Third Party Data5 minutes
Evaluating the Validity of Data Sources8 minutes
Scrubbing Your Data Clean2 minutes
Remove Duplicate Records3 minutes
Format Your Records4 minutes
Handle Missing Values4 minutes
Check for Wrong Values3 minutes
A Real World Example2 minutes
Case Study - Obtaining Data4 minutes
Case Study - Scrubbing Data7 minutes
Weekly Review: Obtaining and Scrubbing Data1 minute

3 readingsTotal 22 minutes

An Overview of Helpful Free Datasources10 minutes
Summary: Validity of Data7 minutes
Summary: Scrubbing data5 minutes

4 assignmentsTotal 145 minutes

Practice Quiz: Obtaining data20 minutes
Practice Quiz: Scrubbing data15 minutes
Activity: Obtaining and Scrubbing Data60 minutes
Graded Quiz: Obtaining and Scrubbing Data50 minutes

This week moves onto the Exploring and Modeling phases of OSEMN. You will learn how to inspect and summarize your data as well as evaluate data relationships. You will discover the purpose of data modeling and common types of data models and data visualizations.

What's included

15 videos2 readings4 assignments

15 videosTotal 56 minutes

Introduction: Exploring and Modeling Data1 minute
Getting to Know Your Data Better2 minutes
The Language of Data5 minutes
Creating Visualizations5 minutes
Examine Data Distributions5 minutes
Examine Data Relationships6 minutes
Feature Engineering4 minutes
Make Predictions from Your Data with Modeling1 minute
What Are Models and Why Use Them?4 minutes
How Do Models Work?5 minutes
Different Types of Models5 minutes
A Real World Example3 minutes
Case Study - Exploring Data4 minutes
Case Study - Modeling Data3 minutes
Weekly Conclusion1 minute

2 readingsTotal 15 minutes

Summary: Exploring Data10 minutes
Common Model Types5 minutes

4 assignmentsTotal 130 minutes

Practice Quiz: Exploring data20 minutes
Practice Quiz: Modeling15 minutes
Activity: Exploring and Modeling Data45 minutes
Graded Quiz: Exploring and Modeling Data50 minutes

This week you will learn how to interpret the data you have working with and relate the results of your analysis back to a specific business goal. You will also learn how to create a story for a presentation of your data in order to explain and engage an audience.

What's included

15 videos1 reading5 assignments

15 videosTotal 51 minutes

Introduction: Interpreting Data2 minutes
Answer Your Business Question with Your Data3 minutes
Understand the Results of Your Model6 minutes
Explain Your Findings7 minutes
The Power of Stories2 minutes
Explain, Enlighten, and Engage4 minutes
Telling a Compelling Story5 minutes
Introduction2 minutes
Obtaining Data4 minutes
Scrubbing data3 minutes
Exploring Data6 minutes
Modeling Data3 minutes
Interpreting Data3 minutes
Weekly Review: Interpreting Data1 minute
Congratulations!1 minute

1 readingTotal 10 minutes

Summary Reading: iNterpreting Data & Storytelling10 minutes

5 assignmentsTotal 170 minutes

Practice Quiz: Interpreting Your Data15 minutes
Practice Quiz: Storytelling with Data15 minutes
Activity: iNterpreting Data45 minutes
Comprehensive Activity: Applying OSEMN45 minutes
Graded Quiz: Interpreting Data50 minutes

In this optional module, you learn what generative AI is and how it functions. You also discover how GenAI can be applied in different business scenarios as well as navigating the concerns around its usage. Then you explore how to incorporate GenAI into your data analytics efforts to streamline processes and improve data quality.

What's included

8 videos4 readings3 assignments1 discussion prompt

8 videosTotal 64 minutes

Understanding Generative AI: An Overview8 minutes
Exploring Different GenAI Technologies12 minutes
Applications of Generative AI in Business8 minutes
Navigating the Challenging: Concerns with AI8 minutes
Integrating GenAI with Data Analytics6 minutes
Improving Data Quality and Generation with GenAI7 minutes
GenAI in Predictive Analytics9 minutes
Case Studies: GenAI in Data Analytics5 minutes

4 readingsTotal 40 minutes

Responsible AI - AI at Meta10 minutes
Summary: Key Takeaways on Generative AI10 minutes
Summary: Key Points on GenAI in Data Analytics10 minutes
Using GenAI in Your Data Analytics Projects10 minutes

3 assignmentsTotal 65 minutes

Practice Quiz: Understanding Generative AI20 minutes
Activity: Experience the Power of GenAI30 minutes
Practice Quiz: Understanding GenAI in Data Analytics15 minutes

1 discussion promptTotal 10 minutes

Share Your Thoughts!10 minutes

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Instructor

Instructor ratings

(329 ratings)

Anke Audenaert

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Reviewed on Oct 2, 2024

Best module to understand the Fundamentals of Data Analysis and much more. I love the way of teaching and doing exercises

Reviewed on Oct 3, 2024

I recently completed the "Introduction to Data Analytics" course, and I found it to be quite informative and engaging

Reviewed on May 15, 2024

The course is made easy to understand with practice exercises and Anke made it so fascinating.

Frequently asked questions

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.