Advanced SQL for Data Analytics

Develop technical skills in the high-growth field of advanced data analytics.




Hours per week


Live Sessions

Sep 25, 2023

Next Date


The objective of this course is to provide participants with the knowledge and skills to effectively utilize advanced SQL queries and techniques for data manipulation and analysis. Participants will learn how to write SQL queries to manipulate and analyze large datasets. They will explore advanced topics such as subqueries and joins, enabling them to effectively retrieve data from multiple tables and perform intricate data analysis. Participants will also learn how to aggregate and group data using SQL functions like COUNT, SUM, and AVG, and understand the use of window functions for analyzing data over specific ranges. Additionally, participants will learn how to integrate SQL with popular business intelligence tools like Excel and Power BI, enhancing their ability to derive meaningful insights from data and create comprehensive analytical reports. By the end of the course, participants will have the skills and understanding to utilize advanced SQL techniques to manipulate and analyze data, enabling them to make data-driven decisions and effectively communicate insights using business intelligence tools.


• Proficiency in SQL fundamentals, including basic querying and data manipulation.

• Knowledge of database concepts, such as tables, relationships, and primary/foreign keys.

• Familiarity with advanced SQL topics, including subqueries, joins, and window functions.

• Awareness of cloud computing concepts and familiarity with cloud-based databases.


Advanced SQL Queries

Understand SQL query structure by applying Data Manipulation Language (DML) for performing operations such as INSERT, UPDATE, and DELETE. And Data Definition Language (DDL) for creating and modifying database structures. The topic will also cover subqueries, which are queries embedded within other queries to retrieve data from multiple tables.

Joins and Unions

Use Joins for combining data from multiple tables based on related columns. Apply types of joins, including INNER JOIN and OUTER JOIN, to retrieve data from the tables with matching records. The topic will also cover the UNION operator for combining the results of multiple SELECT queries into a single result set, with the option to include duplicates or not using UNION ALL.

Data Aggregation

Apply SQL functions like COUNT, SUM, AVG, MIN, and MAX for summarizing, analyzing and performing calculations on groups of data. Learn how to use the GROUP BY clause to group data based on specific criteria and the HAVING clause to filter aggregated results.

Window Functions

Window functions provide a way to perform calculations across a set of related rows. Leverage window functions to calculate moving averages, cumulative sums, and other analytics. Explore window frames to define the scope of window functions and control the rows included in calculations. Ranking data based on specific criteria will also be covered in this topic.

SQL and Business Intelligence Tools

Itegrate SQL with popular business intelligence tools like Excel and Power BI. Learn how to connect SQL databases to these tools to visualize and analyze data effectively. By using SQL as a data source, they will be able to leverage the power of these BI tools for data-driven decision-making.

Cloud Databases and Big Data Processing

Explore cloud-based databases like BigQuery and understand their advantages and use cases. Learn how to integrate and connect cloud-based databases with SQL for efficient data storage, retrieval, and analysis in the cloud environment.


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