SQL for Beginner-For Data Analytics & Business Intelligence

Learn how to create a database and tables, insert records, and query data using sql basics for data analytics and business intelligence.

Learn how to use delete, truncate, and drop in SQL. See how to delete specific rows with a where clause, remove all data with truncate, and drop entire tables.

Learn how to modify a database with sql by renaming columns, adding and dropping fields, and refreshing tables to reflect changes.

Discover how to update and delete records in SQL, back up tables before changes, and view updates or restore from backups if needed.

Explore SQL constraints, including not null, unique, primary key, and foreign key, to enforce referential integrity, prevent duplicates, and apply defaults in table design.

Explore the list operator in SQL to filter data by conditions, such as greater than and less than, and learn how to display matching results.

Explore sql operators in practice by applying and or conditions to filter donor data, displaying records when donor condition, production less than three months apart, or health criteria are satisfied.

Use the between operator to filter rows in SQL by specifying inclusive lower and upper bounds, such as values between five and eleven, to refine results.

Explore SQL operators through multiple examples, showing how to handle one or more values and different approaches to achieve the same result.

Explore how the like operator uses wildcards to filter data by patterns, including starting and ending matches across multiple tables. See real-world string examples and scenario comparisons.

Master the like operator in SQL for data analytics and business intelligence, using simple pattern matching to filter results.

Explore the like operator and its negation not like in SQL, including patterns such as not starting with a given string and basic pattern matching.

Explore the like operator and not equal condition in SQL to query single items and filter data for analytics and business intelligence.

Explore aggregate functions in SQL for data analytics, learning to compute sum of hours per team and use min, max, and average values to summarize data.

Explore how aggregate date functions calculate the average by excluding zeros, applying the division formula, and interpreting results like 170 for island west.

Learn to apply aggregate date functions in SQL to calculate and separate months within a sample table, building and testing date-based expressions for analytics and business intelligence.

Explore aggregate date functions in SQL, including current date and time, and calculating date differences between events such as order dates, dispatch, and delivery to analyze timelines.

Learn to use the left text function to extract a specified number of characters from the left of a column. See practical examples and results in sql.

Learn how to use the substring function in SQL to extract portions of text, practical for data analytics and business intelligence tasks.

Explore applying SQL text functions to format and clean text data, use one function at a time, and extract information while addressing gaps in records.

Create sample space data and apply a text function to remove spaces from data. Learn how left- and right-side spaces are handled, with right-side removal prioritized.

Explore SQL text functions to manipulate strings, copy results, and discuss the agenda to determine what they want.

Learn how to concatenate a first name and last name to form a full name using text functions in SQL, including inserting a space between names.

Sort data with order by in ascending or descending order across multiple columns, using distinct to remove duplicates and applying group by with having for an aggregate function.

Learn how the SQL group clause groups data and applies aggregation functions to compute totals, illustrating how sums appear for grouped categories.

Learn how to use a sub query to filter by a maximum value with select from a table where a column equals the max, and handle multiple values.

Apply case when logic to implement conditional filters in SQL queries, such as changing continent values like China and France, for data analytics and business intelligence.

Practice SQL joins to merge two tables, observing how left, right, and full joins display matching and unmatched records—such as employees and departments—across datasets.