Managing Big Data with MySQL (Coursera)

Offered by Duke University,
Managing Big Data with MySQL (Coursera)

This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases. No more waiting 48 hours for someone else in the company to provide data to you – you will be able to get the data by yourself!
By the end of this course, you will have a clear understanding of how relational databases work, and have a portfolio of queries you can show potential employers. Businesses are collecting increasing amounts of information with the hope that data will yield novel insights into how to improve businesses. Analysts that understand how to access this data – this means you! – will have a strong competitive advantage in this data-smitten business world.
Course 4 of 5 in the Excel to MySQL: Analytic Techniques for Business Specialization.

Syllabus

WEEK 1
Understanding Relational Databases
Welcome to week 1! This week you will learn how relational databases are organized, and practice making and interpreting Entity Relationship (ER) diagrams and relational schemas that describe the structure of data stored in a database. By the end of the week, you will be able to: (1) Describe the fundamental principles of relational database design (2) Interpret Entity Relationship (ER) diagrams and Entity Relationship (ER) schemas, and (3) Create your own ER diagrams and relational schemas using a software tool called ERDPlus that you will use to aid your query-writing later in the course. This week’s exercises are donated from a well-known Database Systems textbook, and will help you deepen and strengthen your understanding of how relational databases are organized. This deeper understanding will help you navigate complicated business databases, and allow you to write more efficient queries. At the conclusion of the week, you will test your understanding of database design principles by completing the Week 1 graded quiz.

WEEK 2
Queries to Extract Data from Single Tables
Welcome to week 2! This week, you will start interacting with business databases. You will write SQL queries that query data from two real companies. One data set, donated from a local start-up in Durham, North Carolina called Dognition, is a MySQL database containing tables of over 1 million rows. The other data set, donated from a national US department store chain called Dillard’s, is a Teradata database containing tables with over a hundred million rows. By the end of the week, you will be able to:1. Use two different database user interfaces2. Write queries to verify and describe all the contents of the Dognition MySQL database and the Dillard’s Teradata database3. Retrieve data that meet specific criteria in a socially-responsible using SELECT, FROM, WHERE, LIMIT, and TOP clauses, and4. Format the data you retrieve using aliases, DISTINCT clauses, and ORDER BY clauses.Make sure to watch the instructional videos about how to use the database interfaces we have established for this course, and complete both the MySQL and the Teradata exercises. At the end of the week, you will test your understanding of the SQL syntax introduced this week by completing the Week 2 graded quiz.

WEEK 3
Queries to Summarize Groups of Data from Multiple Tables
Welcome to week 3! This week, we are going to learn the SQL syntax that allows you to segment your data into separate categories and segment. We are also going to learn how to combine data stored in separate tables. By the end of the week, you will be able to: (1) Summarize values across entire columns, and break those summaries up according to specific variables or values in others columns using GROUP BY and HAVING clauses (2) Combine information from multiple tables using inner and outer joins (3) Use strategies to manage joins between tables with duplicate rows, many-to-many relationships, and atypical configurations (4) Practice one of the slightly more challenging use cases of aggregation functions, and (5) Work with the Dognition database to learn more about how MySQL handles mismatched aggregation levels. Make sure to watch the videos about joins, and complete both the MySQL and the Teradata exercises. At the end of the week, you will test your understanding of the SQL syntax introduced this week by completing the Week 3 graded quiz. We strongly encourage you to use the course Discussions to help each other with questions.

WEEK 4
Queries to Address More Detailed Business Questions
Welcome to week 4, the final week of Managing Big Data with MySQL! This week you will practice integrating the SQL syntax you’ve learn so far into queries that address analysis questions typical of those you will complete as a business data analyst. By the end of the week, you will be able to: (1) Design and execute subqueries (2) Introduce logical conditions into your queries using IF and CASE statements (3) Implement analyses that accommodate missing data or data mistakes, and (4) Write complex queries that incorporate many tables and clauses. By the end of this week you will feel confident claiming that you know how to write SQL queries to create business value. Due to the extensive nature of the queries we will practice this week, we have put the graded quiz that tests your understanding of the SQL strategies you will practice in its own week rather than including it in this week’s materials. Make sure to complete both the MySQL exercises and the Teradata exercises, and we strongly encourage you to use the course Discussions to help each other with questions.

WEEK 5
Strengthen and Test Your Understanding
This week contains the final ungraded Teradata exercises, and the final graded quiz for the course. The exercises are intended to hone and build your understanding of the last important concepts in the course, and lead directly to the quiz so be sure to do both!

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

MySQL for Data Analytics and Business Intelligence (Coursera) Coursera
Edureka

MySQL for Data Analytics and Business Intelligence (Coursera)

Embark on a thorough educational expedition through the "Fundamentals of Database Management with MySQL" module. This foundational program aims to impart a robust comprehension of MySQL, a prominent Relational Database Management System (RDBMS). Participants will delve into crucial concepts, ranging from the fundamentals of SQL to more advanced topics like data retrieval, relationships, business intelligence, and data visualization.

Nov 2nd 2026
1 Week
Mastering Data Analysis in Excel (Coursera) Coursera
Duke University

Mastering Data Analysis in Excel (Coursera)

Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality. This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. Your first model will focus on minimizing default risk, and your second on maximizing bank profits.

Oct 19th 2026
5-12 Weeks
AWS Cloud Practitioner Essentials (Coursera) Coursera
AWS

AWS Cloud Practitioner Essentials (Coursera)

Welcome to AWS Cloud Practitioner Essentials. If you’re new to the cloud, whether you’re in a technical or non-technical role such as finance, legal, sales, marketing, this course will provide you with an understand of fundamental AWS Cloud concepts to help you gain confidence to contribute to your organization’s cloud initiatives. This course is also the starting point to prepare for your AWS Certified Cloud Practitioner certification whenever it’s convenient for you.

Nov 2nd 2026
5-12 Weeks
Getting Started with CyberGIS (Coursera) Coursera
University of Illinois at Urbana-Champaign

Getting Started with CyberGIS (Coursera)

This course is intended to introduce students to CyberGIS—Geospatial Information Science and Systems (GIS)—based on advanced cyberinfrastructure as well as the state of the art in high-performance computing, big data, and cloud computing in the context of geospatial data science. Emphasis is placed on learning the cutting-edge advances of cyberGIS and its underlying geospatial data science principles.

Oct 26th 2026
4 Weeks
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera) Coursera
Icahn School of Medicine at Mount Sinai

Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera)

In this course we briefly introduce the DCIC and the various Centers that collect data for LINCS. We then cover metadata and how metadata is linked to ontologies. We then present data processing and normalization methods to clean and harmonize LINCS data. This follow discussions about how data is served as RESTful APIs. Most importantly, the course covers computational methods including: data clustering, gene-set enrichment analysis, interactive data visualization, and supervised learning. Finally, we introduce crowdsourcing/citizen-science projects where students can work together in teams to extract expression signatures from public databases and then query such collections of signatures against LINCS data for predicting small molecules as potential therapeutics.

Oct 19th 2026
5-12 Weeks
Business Metrics for Data-Driven Companies (Coursera) Coursera
Duke University

Business Metrics for Data-Driven Companies (Coursera)

In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs.

Oct 19th 2026
4 Weeks
Introduction to Big Data (Coursera) Coursera
University of California, San Diego

Introduction to Big Data (Coursera)

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world!

Oct 19th 2026
3 Weeks
Media ethics & governance (Coursera) Coursera
University of Amsterdam

Media ethics & governance (Coursera)

This course explores some of the basic theories, models and concepts in the field of media ethics. We will introduce influential ethical theories and perspectives, explore changing societal demands and expectations of media creation and media use, and we will elaborate on existing ethical norms for media professionals. After following this course, you will be able to reflect on ethical dilemmas and develop a well-substantiated argumentation for ethical decision making in a variety of media-related contexts.

Oct 19th 2026
4 Weeks
Code Free Data Science (Coursera) Coursera
University of California, San Diego

Code Free Data Science (Coursera)

The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data.

Oct 26th 2026
4 Weeks
Linear Regression for Business Statistics (Coursera) Coursera
Rice University

Linear Regression for Business Statistics (Coursera)

Regression Analysis is perhaps the single most important Business Statistics tool used in the industry. Regression is the engine behind a multitude of data analytics applications used for many forms of forecasting and prediction. This is the fourth course in the specialization, "Business Statistics and Analysis". The course introduces you to the very important tool known as Linear Regression. You will learn to apply various procedures such as dummy variable regressions, transforming variables, and interaction effects. All these are introduced and explained using easy to understand examples in Microsoft Excel.

Oct 19th 2026
4 Weeks
Foundations of marketing analytics (Coursera) Coursera
ESSEC Business School

Foundations of marketing analytics (Coursera)

Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role, in particular in marketing. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering. However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data and explore new features and statistical functions in R.

Oct 19th 2026
5-12 Weeks