Data Analytics Expert Certification
Categories: Business Analytics and Management
About Course
Welcome to Business Analysis Essentials—the ultimate course for anyone aiming to become a skilled Business Intelligence (BI) Analyst.
I’m thrilled to offer you this unique, all-inclusive learning experience. While many courses cover some aspects of the BI Analyst profession, this course goes above and beyond to provide everything you need to excel in this field.
Unlike other programs, this course is truly comprehensive, covering key skills in depth across multiple modules:
Introduction to Data and Data Science
Statistics and Excel
Database Theory
SQL
Tableau
SQL + Tableau Integration
These are the essential technical skills that today’s recruiters are searching for in BI Analysts. By enrolling, you’re giving yourself a competitive edge over other candidates. This course could be the key to your success, and I’m here to support you every step of the way!
Here’s what you’ll master in the course:
Introduction to Data and Data Science: Get familiar with critical terms like business intelligence, big data, machine learning, predictive analytics, supervised and unsupervised learning, and much more.
Statistics and Excel: Build a solid foundation in statistical testing and critical thinking, skills that are becoming increasingly valuable despite modern software automating many tasks.
Database Theory: Understanding the theory behind databases is crucial before diving into SQL. Learn why databases are created and how they help manage data efficiently.
SQL: Master SQL so you can independently query data, making you more self-sufficient and capable of uncovering valuable insights for your company.
Tableau: Learn to use one of the most powerful data visualization tools available, widely used by large companies to enhance their BI operations. Tableau helps you create impactful charts and dashboards with ease.
SQL + Tableau: Discover how to integrate SQL and Tableau to perform real-world Business Intelligence tasks and put your new skills into practice.
Throughout the course, you’ll receive full support whenever you need it. I’m passionate about teaching and excited to guide you on your journey into this dynamic and growing profession.
Don’t wait—enroll today, and you’ll only wish you had found this course sooner!
What Will You Learn?
- Become proficient in Statistics, SQL, Tableau, and problem-solving. Enhance your resume with sought-after data skills. Gather, organize, analyze, and visualize data effectively. Use data insights to drive better business decisions. Present metrics, KPIs, reports, and dashboards clearly. Perform both quantitative and qualitative business analysis. Analyze trends, market conditions, and competitor positioning. Understand core concepts of database theory. Create, design, and manipulate databases using SQL. Write custom queries to extract data from databases. Build professional data visualizations in Tableau. Integrate SQL and Tableau to visualize data directly from the source. Tackle real-world business analysis tasks with SQL and Tableau.
Course Content
Python – Python Variables and Data Types
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Python Variables – Exercise #1
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Python Variables – Exercise #2
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Python Variables – Exercise #3
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Python Variables – Exercise #4
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Python Variables
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Understanding Numbers and Boolean Values
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Numbers and Boolean Values – Exercise #1
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Numbers and Boolean Values – Exercise #2
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Numbers and Boolean Values – Exercise #3
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Numbers and Boolean Values – Exercise #4
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Numbers and Boolean Values – Exercise #5
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Understanding Numbers and Boolean Values
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Strings
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Strings – Exercise #1
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Strings – Exercise #2
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Strings – Exercise #3
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Strings – Exercise #4
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Strings – Exercise #5
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Strings
SQL – Window Functions
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The ROW_NUMBER() Ranking Window Function and the Relevant MySQL Syntax
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The ROW_NUMBER Ranking Window Function – Exercise
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The ROW_NUMBER Ranking Window Function – Solution
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A Note on Using Several Window Functions in a Query
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A Note on Using Several Window Functions in a Query – Exercise
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A Note on Using Several Window Functions in a Query – Solution
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MySQL Window Functions Syntax
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MySQL Window Functions Syntax – Exercise
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MySQL Window Functions Syntax – Solution
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The PARTITION BY Clause vs the GROUP BY Clause
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The PARTITION BY Clause vs the GROUP BY Clause – Exercise
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The PARTITION BY Clause vs the GROUP BY Clause – Solution
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The MySQL RANK() and DENSE_RANK() Window Functions
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The MySQL RANK() and DENSE_RANK() Window Functions – Exercise
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The MySQL RANK() and DENSE_RANK() Window Functions – Solution
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Working with MySQL Ranking Window Functions and Joins Together
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Working with MySQL Ranking Window Functions and Joins Together – Exercise
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Working with MySQL Ranking Window Functions and Joins Together – Solution
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The LAG() and LEAD() Value Window Functions
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The LAG() and LEAD() Value Window Functions – Exercise
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The LAG() and LEAD() Value Window Functions – Solution
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MySQL Aggregate Functions in the Context of Window Functions – Part I
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MySQL Aggregate Functions in the Context of Window Functions – Part I-Exercise
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MySQL Aggregate Functions in the Context of Window Functions – Part I-Solution
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MySQL Aggregate Functions in the Context of Window Functions – Part II
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MySQL Aggregate Functions in the Context of Window Functions – Part II-Exercise
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MySQL Aggregate Functions in the Context of Window Functions – Part II-Solution
SQL – Common Table Expressions (CTEs)
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An Alternative Solution to the Same Task
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An Alternative Solution to the Same Task-Exercise
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An Alternative Solution to the Same Task-Solution
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Using Multiple Subclauses in a WITH Clause – Part I
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Using Multiple Subclauses in a WITH Clause – Part II
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Using Multiple Subclauses in a WITH Clause-Exercise
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Using Multiple Subclauses in a WITH Clause-Solution
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Referring to Common Table Expressions in a WITH Clause
SQL – Temporary Tables
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MySQL Temporary Tables in Action
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MySQL Temporary Tables in Action-Exercise
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MySQL Temporary Tables in Action-Solution
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Other Features of MySQL Temporary Tables
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Other Features of MySQL Temporary Tables-Exercise
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Other Features of MySQL Temporary Tables-Solution
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Test 1
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Test 2
Part 4: Introduction to Tableau
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Why Use Tableau: Make Your Data Make an Impact
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Let’s Download Tableau Public
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Connecting Data in Tableau
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Exploring Tableau’s Interface
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Let’s Create our first Chart in Tableau!
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Test 1
Tableau – Tableau functionalities
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Creating a Table
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Creating Custom Fields
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Creating a Custom Field and Adding Calculations to a Table
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Adding Totals and Subtotals
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Adding a Custom Calculation
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Inserting a Filter
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Working with Joins in Tableau
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Test 1
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Test 2
Tableau – The Tableau Exercise
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Let’s Create a Dashboard – Visualizing the Three Charts We Want to Create
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Using Joins in Tableau
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Performing a Numbers Check – Attempt #1
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Blending Data in Tableau
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Performing a Numbers Check – Attempt #2
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First Chart
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Second Chart
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Third Chart
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Creating and Formatting a Dashboard
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Adding Interactive Filters for Improved Analysis
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Interactive Filters – fix
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Using Joins in Tableau
Part 5: Combining SQL and Tableau – Introduction
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Combining SQL and Tableau
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Loading the Database
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Loading the Database
Combining SQL and Tableau – Problem 1
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Problem 1: Task – Text
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Important clarification!
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Problem 1: Solution in SQL
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Problem 1: Solution in SQL – Code
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Exporting Your Output from SQL and Loading it in Tableau
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Chart 1: Visualizing the Solution in Tableau – Part I
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Chart 1: Visualizing the Solution in Tableau – Part II
Combining SQL and Tableau – Problem 2
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Problem 2: Task – Text
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Problem 2: Solution in SQL
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Problem 2: Solution in SQL – Code
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Chart 2: Visualizing the Solution in Tableau
Combining SQL and Tableau – Problem 3
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Problem 3: Task – Text
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Problem 3: Solution in SQL
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Problem 3: Solution in SQL – Code
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Chart 3: Visualizing the Solution in Tableau
Combining SQL and Tableau – Problem 4
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Problem 4: Task – Text
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Problem 4: Solution in SQL
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Problem 4: Solution in SQL – Code
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Chart 4: Visualizing the Solution in Tableau
Part 6: Introduction to Programming with Python
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A 5-minute explanation of Programming
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Why use Python?
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Why Use Python?
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Why use Jupyter?
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Why Use Jupyter?
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How to Install Python and Jupyter
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Understanding Jupyter’s Interface – Dashboard
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Understanding Jupyter’s Interface – Prerequisites for Coding
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Understanding Jupyter’s Interface
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Python 2 vs Python 3
SQL – The CASE Statement
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The SQL CASE Statement – Exercise 1
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THE SQL CASE Statement – Solution 1
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THE SQL CASE Statement – Exercise 2
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THE SQL CASE Statement – Solution 2
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THE SQL CASE Statement – Exercise 3
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THE SQL CASE Statement – Solution 3
Python – Python Syntax Fundamentals
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The Arithmetic Operators in Python – Exercise #1
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The Arithmetic Operators in Python – Exercise #2
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The Arithmetic Operators in Python – Exercise #3
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The Arithmetic Operators in Python – Exercise #4
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The Arithmetic Operators in Python – Exercise #5
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The Arithmetic Operators in Python – Exercise #6
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The Arithmetic Operators in Python – Exercise #7
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The Arithmetic Operators in Python – Exercise #8
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Using Arithmetic Operators in Python
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What is the Double Equality Sign?
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What is the Double Equality Sign? – Exercise #1
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What is the Double Equality Sign?
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How to Reassign Values
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How to Reassign Values – Exercise #1
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How to Reassign Values – Exercise #2
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How to Reassign Values – Exercise #3
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How to Reassign Values – Exercise #4
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How to Reassign Values
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How to Add Comments
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How to Add Comments
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Understanding Line Continuation
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Understanding Line Continuation – Exercise #1
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How to Index Elements
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How to Index Elements – Exercise #1
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How to Index Elements – Exercise #2
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How to Index Elements
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How to Structure Your Code with Indentation
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How to Structure Your Code with Indentation – Exercise #1
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How to Structure Your Code with Indentation
Python – Other Python Operators
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Python’s Comparison Operators – Exercise #1
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Python’s Comparison Operators – Exercise #2
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Python’s Comparison Operators – Exercise #3
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Python’s Comparison Operators – Exercise #4
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Python’s Comparison Operators
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Python’s Logical and Identity Operators
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Python’s Logical and Identity Operators – Exercise #1
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Python’s Logical and Identity Operators – Exercise #2
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Python’s Logical and Identity Operators – Exercise #3
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Python’s Logical and Identity Operators – Exercise #4
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Python’s Logical and Identity Operators – Exercise #5
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Python’s Logical and Identity Operators – Exercise #6
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Python’s Logical and Identity Operators
Python – Conditional Statements
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The IF Statement – Exercise #1
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The IF Statement – Exercise #2
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Getting to know the IF Statement
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Adding an ELSE statement
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The ELSE Statement – Exercise #1
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Else if, for Brief – ELIF
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The ELIF Statement – Exercise #1
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The ELIF Statement – Exercise #2
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An Additional Explanation of Boolean Values
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An Additional Explanation of Boolean Values
Python – Functions
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How to Create a Function with a Parameter
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How to Create a Function with a Parameter – Exercise #1
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How to Create a Function with a Parameter – Exercise #2
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Define a Function in Another Way
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Define a Function in Another Way – Exercise #1
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How to Use a Function within a Function
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How to Use a Function within a Function – Exercise #1
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Use Conditional Statements and Functions Together
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Conditional Statements and Functions – Exercise #1
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How to Create Functions Which Contain a Few Arguments
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Built-In Functions in Python Worth Knowing
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Built-In Function in Python Worth Knowing – Exercise #1
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Built-In Function in Python Worth Knowing – Exercise #2
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Built-In Function in Python Worth Knowing – Exercise #3
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Built-In Function in Python Worth Knowing – Exercise #4
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Built-In Function in Python Worth Knowing – Exercise #5
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Built-In Function in Python Worth Knowing – Exercise #6
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Built-In Function in Python Worth Knowing – Exercise #7
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Built-In Function in Python Worth Knowing – Exercise #8
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Built-In Function in Python Worth Knowing – Exercise #9
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Python – Functions
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Test 1
Python – Python Sequences
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Introduction to Lists – Exercise #1
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Introduction to Lists – Exercise #2
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Introduction to Lists – Exercise #3
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Introduction to Lists – Exercise #4
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Introduction to Lists – Exercise #5
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Introduction to Lists
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Using Methods in Python
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Using Methods in Python – Exercise #1
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Using Methods in Python – Exercise #2
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Using Methods in Python – Exercise #3
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Using Methods in Python – Exercise#4
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Using Methods in Python
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What is List Slicing?
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What is List Slicing? – Exercise #1
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What is List Slicing? – Exercise #2
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What is List Slicing? – Exercise #3
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What is List Slicing? – Exercise #4
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What is List Slicing? – Exercise #5
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What is List Slicing? – Exercise #6
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What is List Slicing? – Exercise #7
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Working with Tuples
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Working with Tuples – Exercise #1
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Working with Tuples – Exercise #2
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Working with Tuples – Exercise #3
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Working with Tuples – Exercise #4
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Python Dictionaries
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Python Dictionaries – Exercise #1
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Python Dictionaries – Exercise #2
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Python Dictionaries – Exercise #3
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Python Dictionaries – Exercise #4
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Python Dictionaries – Exercise #5
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Python Dictionaries – Exercise #6
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Python Dictionaries
Python – Using Iterations
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Using For Loops – Exercise #1
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Using For Loops – Exercise #2
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Using For Loops
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Using While Loops and Incrementing
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Using While Loops and Incrementing – Exercise #1
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Use the range() Function to Create Lists
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Use the range() Function to Create Lists – Exercise – #1
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Use the range() Function to Create Lists – Exercise – #2
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Use the range() Function to Create Lists – Exercise – #3
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Use the range() Function to Create Lists
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Combine Conditional Statements and Loops
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Conditional Statements and Loops – Exercise #1
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Conditional Statements and Loops – Exercise #2
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Conditional Statements and Loops – Exercise #3
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All In – Conditional Statements, Functions, and Loops
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All In – Conditional Statements, Functions, and Loops – Exercise #1
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How to Iterate over Dictionaries
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How to Iterate over Dictionaries – Exercise #1
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How to Iterate over Dictionaries – Exercise #2
Python – Advanced Python tools
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Introduction to Object Oriented Programming (OOP)
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Using Modules and Packages
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Using Modules and Packages
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What is the Standard Library?
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What is the Standard Library?
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How to Import Modules in Python
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How to Import Modules in Python
Part 7: Integration – Software Integration
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Getting Started with Data, Servers, Clients, Requests, and Responses
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Getting Started with Data Connectivity, APIs, and Endpoints
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Getting Started with Data Connectivity, APIs, and Endpoints
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Become Better Acquainted with APIs
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Become Better Acquainted with APIs
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Communication through Text Files
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Communication through Text Files
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What is Software Integration and How is it Applied?
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What is Software Integration and How is it Applied?
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Become Better Acquainted with APIs
Integration – What is contained in this Course?
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Presenting the Task: Absenteeism at Work
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Presenting the Data Set
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Presenting the Data Set
Integration – Data Preprocessing Step by Step
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How to Import the Data Set in Python
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Exploring the Data Set
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Programming vs the Rest of the World
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A Brief Summary of Regression Analysis
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The Approach we will Take to Solve this Exercise
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Dropping Variables We Don’t Need
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EXERCISE – Dropping Variables We Don’t Need
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SOLUTION – Dropping Variables We Don’t Need
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A Deeper Look at the ‘Reasons for Absence’ Column
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Splitting a Variable into Multiple Dummy Variables
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SOLUTION – Splitting a Variable into Multiple Dummy Variables
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How to Drop a Dummy Variable from the Data Set
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A Statistical Perspective on Dummy Variables
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Categorizing the Various Reasons for Absence
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Concatenation in Python
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EXERCISE – Concatenation in Python
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SOLUTION – Concatenation in Python
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How to Reorder Columns in a DataFrame in Python
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EXERCISE – How to Reorder Columns in a DataFrame in Python
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SOLUTION – How to Reorder Columns in a DataFrame in Python
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Using Checkpoints to Ease Your Work in Jupyter
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EXERCISE – Using Checkpoints to Ease Your Work in Jupyter
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SOLUTION – Using Checkpoints to Ease Your Work in Jupyter
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Analyzing the “Date” Column
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Retrieving the Month Value From the “Date” Column
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Adding the “Day of the Week” Column
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EXERCISE – Dropping Columns
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Analysis of the Next 5 Columns in DF
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Dealing with More Numerical Features which may Behave like Categorical Ones
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A Final Note on this Section
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Programming vs the Rest of the World
Integration – Integrating Python and SQL
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How to Use the ‘absenteeism_module’ in Python – Part II
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Creating the ‘predicted_outputs’ Database in MySQL
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Importing ‘pymysql’ in Python
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Creating a Connection and Cursor
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EXERCISE – Creating ‘df_new_obs’
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Creating the ‘predicted_outputs’ Table in MySQL
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Executing and SQL SELECT Statement from Python
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Sending Data from Jupyter to Workbench – Part I
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Sending Data from Jupyter to Workbench – Part II
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Sending Data from Jupyter to Workbench – Part III
Integration – Using Tableau to Analyze the Predicted Outputs
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Using Tableau to Analyze Age vs Probability
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EXERCISE – Reasons vs Probability
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Using Tableau to Analyze Reasons vs Probability
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EXERCISE – Transportation Expense vs Probability
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Using Tableau to Analyze Transportation Expense vs Probability
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Completing 100%
Statistics – Practical Example: Inferential Statistics
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Practical Example: Inferential Statistics Exercise
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Test for the Mean. Population Variance Known
Intro to Data and Data Science – The Different Data Science Fields
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Why Are There So Many Business and Data Science Buzzwords?
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Analysis vs Analytics
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Intro to Business Analytics, Data Analytics, and Data Science
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Adding Business Intelligence (BI), Machine Learning (ML), and AI to the Picture
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Adding Business Intelligence (BI), Machine Learning (ML), and AI to the Picture
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An Overview of our Data Science Infographic
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An Overview of our Data Science Infographic
Intro to Data and Data Science – The Relationship between Different Fields
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When are Traditional data, Big Data, BI, Traditional Data Science and ML applied
Intro to Data and Data Science – What is the Purpose of each Data Science Field
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Why do we Need each of these Disciplines?
Intro to Data and Data Science – Common Data Science Techniques
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Traditional Data: Techniques
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Traditional Data: Real-life Examples
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Big Data: Techniques
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Big Data: Techniques
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Big Data: Real-life Examples
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Business Intelligence (BI): Techniques
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Business Intelligence (BI): Techniques
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Business Intelligence (BI): Real-life Examples
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Traditional Methods: Techniques
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Traditional Methods: Techniques
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Traditional Methods: Real-life Examples
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Machine Learning (ML): Techniques
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Machine Learning (ML): Techniques
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Machine Learning (ML): Types of Machine Learning
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Machine Learning (ML): Types of Machine Learning
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Machine Learning (ML): Real-life Examples
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Machine Learning (ML): Real-life Examples
Intro to Data and Data Science – Common Data Science Tools
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Programming Languages & Software Employed in Data Science – All the Tools Needed
Intro to Data and Data Science – Data Science Career Paths
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Data Science Job Positions: What do they Involve and What to Look out for?
Intro to Data and Data Science – Dispelling Common Misconceptions
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Dispelling common Misconceptions
Part 2: Statistics – Population and Sample
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Population and Sample
Statistics – Descriptive Statistics
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Types of data
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Levels of Measurement
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Levels of measurement
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Categorical Variables – Visualization Techniques
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Categorical variables. Visualization Techniques
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Categorical Variables Exercise
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Numerical Variables – Frequency Distribution Table
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Numerical variables. Using a frequency distribution table
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Numerical Variables Exercise
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The Histogram
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The Histogram
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Histogram Exercise
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Cross Table and Scatter Plot
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Cross Tables and Scatter Plots
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Cross Tables and Scatter Plots Exercise
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Mean, median and mode
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Mean, Median and Mode Exercise
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Skewness
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Skewness
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Skewness Exercise
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Variance
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Variance Exercise
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Standard Deviation and Coefficient of Variation
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Standard deviation
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Standard Deviation and Coefficient of Variation Exercise
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Covariance
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Covariance
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Covariance Exercise
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Correlation Coefficient
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Correlation Coefficient
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Correlation Coefficient Exercise
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Test 1
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Test 2
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Test 3
Statistics – Practical Example: Descriptive Statistics
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Practical Example
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Practical Example Exercise
Statistics – Inferential Statistics Fundamentals
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Statistics – Inferential Statistics: Confidence Intervals
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What are Confidence Intervals?
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Confidence Intervals; Population Variance Known; z-score
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Confidence Intervals; Population Variance Known; z-score Exercise
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Confidence interval clarifications
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Student’s T Distribution
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Student’s T Distribution
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Confidence Intervals; Population Variance Unknown; t-score
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Confidence Intervals; Population Variance Unknown; t-score Exercise
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Margin of Error
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Margin of Error
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Confidence intervals. Two means. Dependent samples
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Confidence intervals. Two means. Dependent samples Exercise
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Confidence intervals. Two means. Independent samples (Part 1)
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Confidence intervals. Two means. Independent samples (Part 1) Exercise
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Confidence intervals. Two means. Independent samples (Part 2)
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Confidence intervals. Two means. Independent samples (Part 2) Exercise
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Confidence intervals. Two means. Independent samples (Part 3)
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Confidence Intervals; Population Variance Known; z-score
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Confidence intervals. Two means. Dependent samples
Part 1: Introduction
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What Does the Course Cover
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Download All Resources
Statistics – Hypothesis Testing
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Further Reading on Null and Alternative Hypothesis
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The Null vs Alternative Hypothesis
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Rejection Region and Significance Level
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Rejection Region and Significance Level
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Type I Error and Type II Error
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Type I Error and Type II Error
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Test for the Mean. Population Variance Known
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Test for the Mean. Population Variance Known Exercise
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p-value
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p-value
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Test for the Mean. Population Variance Unknown
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Test for the Mean. Population Variance Unknown Exercise
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Test for the Mean. Dependent Samples
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Test for the Mean. Dependent Samples Exercise
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Test for the mean. Independent samples (Part 1)
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Test for the mean. Independent samples (Part 1). Exercise
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Test for the mean. Independent samples (Part 2)
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Test for the mean. Independent samples (Part 2)
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Test for the mean. Independent samples (Part 2)
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Test 1
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Test 2
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Test 3
Statistics – Practical Example: Hypothesis Testing
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Practical Example: Hypothesis Testing Exercise
Part 3: Relational Database Theory & Introduction to SQL
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Why use SQL?
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Why use MySQL?
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Why use MySQL?
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Introducing Databases
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Introducing Databases
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Relational Database Fundamentals
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Relational Database Fundamentals
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Comparing Databases and Spreadsheets
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Important Database Terminology
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Important Database Terminology
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The Concept of Relational Schemas: Primary Key
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The Concept of Relational Schemas: Primary Key
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The Concept of Relational Schemas: Foreign Key
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The Concept of Relational Schemas: Foreign Key
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The Concept of Relational Schemas: Unique Key and Null Values
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The Concept of Relational Schemas: Unique Key
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The Concept of Relational Schemas: Relationships Between Tables
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The Concept of Relational Schemas: Relationships Between Tables
SQL — Install and get to know MySQL
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Installing Visual C
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Installing MySQL on macOS and Unix systems
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The Client-Server Model
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Linking GUI with the MySQL Server
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Read me!!!
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Creating a New User and a New Connection to it
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Familiarize Yourself with the MySQL Interface
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SQL Fundamentals – MySQL Session and Databases
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SQL Fundamentals – DROP, CREATE, SELECT, INSERT, DELETE
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Installing MySQL on macOS and Unix systems
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Creating a New User and a New Connection to it
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SQL Fundamentals – MySQL Session and Databases
SQL – Best SQL Practices
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Coding Tips and Best Practices – I
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Coding Tips and Best Practices – II
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Coding Tips and Best Practices – II
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Coding Tips and Best Practices – III
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Coding Tips and Best Practices – IV
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Coding Tips and Best Practices – V
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Coding Tips and Best Practices – VI
SQL – Loading the ’employees’ Database
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Loading the ’employees’ Database
SQL – Practical Application of the SQL SELECT Statement
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Using SELECT – FROM – Exercise
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Using SELECT – FROM – Solution
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Using WHERE
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Using WHERE – Exercise
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Using WHERE – Solution
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Using AND
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Using AND – Exercise
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Using AND – Solution
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Using OR
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Using OR – Exercise
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Using OR – Solution
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Operator Precedence and Logical Order
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Operator Precedence and Logical Order – Exercise
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Operator Precedence and Logical Order – Solution
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Using IN – NOT IN
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Using IN – NOT IN – Exercise 1
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Using IN – NOT IN – Solution 1
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Using IN – NOT IN – Exercise 2
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Using IN – NOT IN – Solution 2
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Using LIKE – NOT LIKE
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Using LIKE – NOT LIKE – Exercise
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Using LIKE – NOT LIKE – Solution
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Using Wildcard Characters
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Using Wildcard characters – Exercise
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Using Wildcard characters – Solution
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Using BETWEEN – AND
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Using BETWEEN – AND – Exercise
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Using BETWEEN – AND – Solution
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Using IS NOT NULL – IS NULL
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Using IS NOT NULL – IS NULL – Exercise
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Using IS NOT NULL – IS NULL – Solution
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Using Other Comparison Operators
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Using Other Comparison Operators – Exercise
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Using Other Comparison Operators – Solution
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Using SELECT DISTINCT
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Using SELECT DISTINCT – Exercise
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Using SELECT DISTINCT – Solution
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Getting to Know Aggregate Functions
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Getting to Know Aggregate Functions – Exercise
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Getting to Know Aggregate Functions – Solution
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Using ORDER BY
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Using ORDER BY – Exercise
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Using ORDER BY – Solution
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Using GROUP BY
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Using Aliases (AS)
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Using Aliases (AS) – Exercise
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Using Aliases (AS) – Solution
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Using HAVING
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Using HAVING – Exercise
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Using HAVING – Solution
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Using WHERE vs HAVING – Part I
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Using WHERE vs HAVING – Part II
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Using WHERE vs HAVING – Part II – Exercise
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Using WHERE vs HAVING – Part II – Solution
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Using LIMIT
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Using LIMIT – Exercise
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Using LIMIT – Solution
SQL – Expanding on MySQL Aggregate Functions
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Applying COUNT() – Exercise
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Applying COUNT() – Solution
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Applying SUM()
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Applying SUM() – Exercise
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Applying SUM() – Solution
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MIN() and MAX()
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MIN() and MAX() – Exercise
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MIN() and MAX() – Solution
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Applying AVG()
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Applying AVG() – Exercise
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Applying AVG() – Solution
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Rounding Numbers with ROUND()
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Rounding Numbers with ROUND() – Exercise
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Rounding Numbers with ROUND() – Solution
SQL – SQL JOINs
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What are JOINs? – Exercise 1
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What are JOINs? – Exercise 2
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What are JOINs? – Exercise 3
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What are JOINs? – Exercise 4
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What are JOINs? – Exercise 5
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The Functionality of INNER JOIN – Part I
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The Functionality of INNER JOIN – Part II
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The Functionality of INNER JOIN – PART II – Exercise
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The Functionality of INNER JOIN – PART II – Solution
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Extra Info on Using Joins
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Duplicate Rows
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The Functionality of LEFT JOIN – Part I
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The Functionality of LEFT JOIN – Part II
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The Functionality of LEFT JOIN – Part II – Exercise
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The Functionality of LEFT JOIN – Part II – Solution
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The Functionality of RIGHT JOIN
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Differences between the New and the Old Join Syntax
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Differences between the New and the Old Join Syntax – Exercise
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Differences between the New and the Old Join Syntax – Solution
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Using JOIN and WHERE Together
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Important – Prevent Error Code: 1055!
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Using JOIN and WHERE Together – Exercise
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Using JOIN and WHERE Together – Solution
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The Functionality of CROSS JOIN
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The Functionality of CROSS JOIN – Exercise 1
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The Functionality of CROSS JOIN – Solution 1
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The Functionality of CROSS JOIN – Exercise 2
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The Functionality of CROSS JOIN – Solution 2
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Combining Aggregate Functions with Joins
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JOIN More than Two Tables
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JOIN More than Two Tables – Exercise
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JOIN More than Two Tables – Solution
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Top Tips for Joins
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Top Tips for Joins – Exercise
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Top Tips for Joins – Solution
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The Differences Between UNION and UNION ALL
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The Differences Between UNION and UNION ALL – Exercise
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The Differences Between UNION and UNION ALL – Solution
SQL – SQL Subqueries
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SQL Subqueries with IN Embedded Inside WHERE – Exercise
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SQL Subqueries with IN Embedded Inside WHERE – Solution
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SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE
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SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE – Exercise
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SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE – Solution
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SQL Subqueries Nested in SELECT and FROM
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SQL Subqueries Embedded in SELECT and FROM – Exercise 1
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SQL Subqueries Embedded in SELECT and FROM – Exercise 2
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SQL Subqueries Nested in SELECT and FROM – Solution 2
SQL – Stored Routines
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Defining Stored Routines
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Create Stored Procedures with MySQL Syntax
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An Example of Stored Procedures Part I
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An Example of Stored Procedures Part II
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An Example of Stored Procedures Part II – Exercise
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An Example of Stored Procedures Part II – Solution
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Creating a Procedure in MySQL Another Way
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Create Stored Procedures with an Input Parameter
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Create Stored Procedures with an Output Parameter
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Create Stored Procedures with an Output Parameter – Exercise
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Stored Procedures with an Output Parameter – Solution
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SQL Variables
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SQL Variables – Exercise
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SQL Variables – Solution
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The Benefit of User-Defined Functions in MySQL
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Error Code: 1418.
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The Benefit of User-Defined Functions in MySQL – Exercise
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The Benefit of User-Defined Functions in MySQL – Solution
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Concluding Stored Routines
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Concluding Stored Routines