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Data analytics is an essential skill for students, professionals and organisations that want to make informed decisions using data. This practical class will help you develop the skills required to clean, analyse, visualise and interpret data using widely used analytical tools. Depending on your learning objectives, lessons may cover Microsoft Excel, Power Query, Power BI, SQL or Python. You can learn how to clean and transform datasets, write formulas and queries, develop data models, calculate meaningful performance indicators and design interactive dashboards. Each lesson is customised according to your current level and goals. I use clear explanations, guided exercises, realistic datasets and practical projects to help you understand both the technical steps and the business meaning behind the results. This class is suitable for beginners, university students, job seekers and working professionals. By the end of the programme, you should be able to analyse data more confidently, create professional reports and apply your skills to academic or workplace projects.

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if you've ever looked at a database and thought, "Where do I even start?"—this course is for you. I'm going to teach you SQL from the ground up, no fluff, no jargon, just the real stuff you need to get confident writing queries that actually do something useful. We'll start with the basics—how to pull data from a table—and build up to more advanced topics like joins, aggregations, subqueries, and even window functions. You’ll learn how to ask the right questions, write clean, readable queries, and solve real-world problems with data.

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Much of the world's raw data—from electronic medical records to customer transaction histories—lives in organized collections of tables called relational databases. Being able to wrangle and extract data from these databases using SQL is an essential skill within the data industry and in increasing demand. In this two-hour introduction to SQL, you'll get to know the theory and the practice through bite-sized videos and interactive exercises where you can put your new-found skills to the test. SQL is an essential language for building and maintaining relational databases, which opens the door to a range of careers in the data industry and beyond. You’ll start this course by covering data organization, tables, and best practices for database construction. The second half of this course looks at creating SQL queries for selecting data that you need from your database. You’ll have the chance to practice your querying skills before moving on to customizing and saving your results. PostgreSQL and SQL Server are two of the most popular SQL flavors. You’ll finish off this course by looking at the differences, benefits, and applications of each. By the end of the course you’ll have some hands-on experience in learning SQL and the grounding to start applying it on projects or continue your learning in a more specialized direction. Relational Databases Before writing any SQL queries, it’s important to understand the underlying data. In this chapter, we’ll discover the role of SQL in creating and querying relational databases. Using a database for a local library, we will explore database and table organization, data types and storage, and best practices for database construction. Querying Learn your first SQL keywords for selecting relevant data from database tables! After practicing querying skills in a database of books, you’ll customize query results using aliasing and save them as views so they can be shared. Finally, you’ll explore the differences between SQL flavors and databases such as PostgreSQL and SQL Server.

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Module 1: SQL Overview Outlining SQL as the cornerstone of database activity Applying the ANSI/ISO standards Describing the fundamental building blocks: tables, columns, primary keys, and foreign keys Module 2: Building the Database Schema - Creating tables and columns Building tables with CREATE TABLE Modifying table structure with ALTER TABLE Adding columns to an existing table Removing tables with DROP TABLE - Protecting data integrity with constraints Guaranteeing uniqueness with primary key constraints Enforcing integrity with foreign key constraints Imposing business rules with check constraints - Improving performance with indexes Expediting data retrieval with indexes Recommending guidelines for index creation Module 3: Manipulating Data - Modifying table contents Adding table rows with INSERT Changing row content with UPDATE Removing rows with DELETE - Applying transactions Controlling transactions with COMMIT and ROLLBACK Deploying BEGIN TRANSACTION in SQL Server Module 4: Working with the SELECT Statement - Writing Single Table queries Retrieving data with SELECT Specifying column expressions Sorting the result with ORDER BY Handling NULL values in expressions - Restricting rows with the WHERE filter Testing for equality or inequality Applying wildcard characters Avoiding NULL value pitfalls Module 5: Querying Multiple Tables - Applying the ANSI/ISO standard join syntax Matching related rows with INNER JOIN Including nonmatched rows with OUTER JOIN Creating a Cartesian product with CROSS JOIN - Combining results with set operators Stacking results with UNION Identifying matching rows with INTERSECT Utilizing EXCEPT to find nonmatching rows Module 6: Employing Functions in Data Retrieval - Processing data with row functions Conditional formatting with the CASE expression Utilizing the CASE expression to simulate IF tests Dealing with NULL values - Performing analysis with aggregate functions Summarizing data using SUM, AVG and COUNT Finding the highest/lowest values with MAX and MIN Defining the summary level with GROUP BY Applying filter conditions with HAVING Module 7: Constructing Nested Queries - Applying subqueries in filter conditions Creating correlated vs. noncorrelated subqueries Testing the existence of rows - Including subqueries in expressions Placing subqueries in the column list Creating complex expressions containing subqueries Handling subqueries that return no rows Module 8: Developing In-Line and Stored Views - Breaking down complex problems Selecting data from a query result set Using subqueries in the FROM clause - Creating views in a database Building reusable code Creating updateable vs. non-updateable views