SQL for Data Engineers Designing and Building Data Pipelines

Explore data definition language concepts to design schemas, define constraints, and understand how DDL, data manipulation language, and transaction data control language enable normalization and referential integrity.

Learn how read, insert, and update authorizations govern access in MySQL databases, and review DDL and DML concepts, including create, alter, drop, rename, constraints, and slowly changing dimensions type two.

Explore primary key constraints and auto-increment in table design, define regions with a primary key, and use DDL to enable reliable joins across tables.

Learn to alter table structures using sql, adding or modifying columns, setting data types and constraints (primary key, not null), and dropping or renaming columns or tables.

Learn the basics of data manipulation language, renaming columns or tables with simple syntax, and using replace and nested queries to retrieve and validate data in sql.

Explore data manipulation language basics, including the select command, and contrast procedural and declarative DML; learn how declarative queries optimize retrieval and see examples with select, insert, update, and delete.

Explore the insert command in SQL, including inserting single or multiple values, data type constraints, and how inserts affect related tables and key relationships.

Master update and delete commands in SQL, using set and where clauses, with examples of dependent and employee IDs, and learn practical advantages and safe data deletion practices.

Explore domain constraints such as not null, unique, and check, and learn how primary and foreign keys enforce data integrity in SQL pipelines.

Explore how not null and check constraints, including named constraints and multi-column checks, enforce data integrity in table design, with examples of primary key, foreign key, and domain constraints.

learn how primary keys enforce uniqueness and non-null values and how foreign keys link tables for joins. explore composite primary keys and the use of constraints to manage table relationships.

Learn how primary keys uniquely identify records and how foreign keys link tables via project_id to enforce referential integrity, and compare truncate versus delete for data refresh.

Explore SQL procedures to load big data tables and manage data with delete, truncate, and triggers, then master set operations including union, union all, and intersect to combine results efficiently.

Learn how the where clause filters data using conditions and common operators in SQL. Expect practical examples of selecting from tables, retrieving records, and filtering by salary or other criteria.

Master the difference between where and having clauses, learn how group by and aggregation filter data such as salaries and direct reports in SQL for data engineers.

Apply where and having clauses to filter salary ranges and compute sums or minimum salaries by department; explore in/not in, and, or, and existence checks to refine data queries.

Explore or and logic, null values, and conditional expressions in SQL queries. Use department filters and aggregation basics like order by, group by, and having.

Master grouping in sql using group by and order by to summarize data with aggregation functions. See practical examples with department head counts, employee counts, and inner joins.

Explore grouping sets and the like operation in sql, using group by, having, and order by to analyze department headcounts and salaries.

Learn to apply advanced grouping with group by, sort results with order by, and control output with limit and offset, using aliases and keywords safely in MySQL.

Learn how to use limit and filtering expressions like not like and is null, and explore grouping sets with group by and order by to retrieve and summarize data.

Explore how inner, outer (full) joins use primary keys to link tables, and how null values arise in left and right joins, with Venn diagram intuition.

Explore SQL join operations, including left and right joins, inner and outer joins, and cross joins, with examples showing nulls when no match and using aliases for column clarity.

Learn inner, left, right, full outer, and cross joins with examples using employees, departments, and countries; understand nulls in left joins and the matrix-multiplication intuition for cross joins.

Explore rank, dense_rank, and row_number in sql, including how ties affect ranking, how partition by and order by power descending shape results, and a primer on views and triggers.

Explore sql window functions rank, dense_rank, and row_number, with practical examples using company and power data, showing how partition by and order by affect ties and sequencing.