Master Data Queries:  SQL for Data Analysis Training Course!

Introduction

Unlock the power of data manipulation and extraction with our comprehensive training course on SQL for Data Analysis. This essential program equips individuals and teams with the fundamental skills to query, analyze, and transform data stored in relational databases. Our training course focuses on writing efficient SQL queries to retrieve specific information, perform calculations, join multiple tables, and generate insightful reports. Whether you're a data analyst, business intelligence professional, or anyone who works with databases, this training course provides the practical knowledge to extract meaningful insights and drive data-driven decision-making.

This SQL for Data Analysis training course emphasizes a hands-on approach, guiding participants through the process of writing and executing SQL queries using real-world datasets. You'll learn to master core SQL commands, understand database structures, and apply analytical functions to uncover trends and patterns. By the end of this impactful training course, you'll possess the core skills to confidently query databases, perform data analysis, and communicate your findings effectively, making you a valuable asset in any data-driven organization.

Target Audience

• Aspiring data analysts and business intelligence professionals
• Data scientists looking to enhance their data querying skills
• Business analysts needing to extract data for reporting and analysis
• Database administrators seeking to improve their query writing abilities
• Anyone who works with relational databases and needs to retrieve data
• Professionals seeking to improve their data-driven decision-making
• Teams aiming to leverage their database information for better insights

Duration:

• 5 Days

Course Objectives

1. Understand the fundamental concepts of relational databases and SQL.
2. Master the core SQL SELECT statement for querying data from single tables.
3. Learn to filter and sort data using the WHERE and ORDER BY clauses.
4. Gain proficiency in joining data from multiple tables using various JOIN types.
5. Learn to use aggregate functions to perform calculations on data.
6. Understand how to group and summarize data using the GROUP BY and HAVING clauses.
7. Develop skills in writing subqueries for complex data retrieval.
8. Learn to use window functions for advanced data analysis and ranking.

Course Content

1. Module: Introduction to SQL and Relational Databases

• Understanding the concepts of relational databases and tables in the module
• Introduction to Structured Query Language (SQL) and its importance for data analysis within the Python module
• Different types of SQL commands: DDL, DML, DCL in the module
• Overview of common database management systems (DBMS) like MySQL, PostgreSQL, SQL Server in the module
• Setting up a practice database environment for writing and executing SQL queries in the module

2. Module: Basic Data Retrieval with the SELECT Statement

• Understanding the basic syntax of the SQL SELECT statement in the module
• Selecting specific columns from a table within the Python module
• Selecting all columns from a table using the asterisk (*) in the module
• Using aliases for columns and tables to improve readability in the module
• Understanding and using the DISTINCT keyword to retrieve unique values in the module

3. Module: Filtering and Sorting Data

• Filtering data using the WHERE clause with comparison operators in the module
• Using logical operators (AND, OR, NOT) to create complex filter conditions within the Python module
• Filtering data using the IN, BETWEEN, LIKE, and IS NULL operators in the module
• Sorting retrieved data using the ORDER BY clause with ASC and DESC options in the module
• Combining filtering and sorting to retrieve specific ordered data in the module

4. Module: Joining Data from Multiple Tables

• Understanding the need for joining tables in relational databases in the module
• Performing INNER JOINs to retrieve matching rows from multiple tables within the Python module
• Using LEFT JOINs to retrieve all rows from the left table and matching rows from the right table in the module
• Understanding RIGHT JOINs and FULL OUTER JOINs for comprehensive data retrieval in the module
• Using aliases effectively when joining multiple tables in the module

5. Module: Aggregate Functions

• Understanding the purpose and syntax of aggregate functions in SQL in the module
• Using COUNT(), SUM(), AVG(), MIN(), and MAX() to perform calculations on data within the Python module
• Applying aggregate functions to specific columns in the module
• Understanding how aggregate functions interact with NULL values in the module
• Using aggregate functions in conjunction with other SQL clauses in the module

6. Module: Grouping and Summarizing Data

• Understanding the purpose of the GROUP BY clause for summarizing data in the module
• Grouping rows based on one or more columns within the Python module
• Applying aggregate functions to grouped data in the module
• Filtering grouped data using the HAVING clause in the module
• Understanding the order of operations for WHERE, GROUP BY, and HAVING clauses in the module

7. Module: Subqueries (Nested Queries)

• Understanding the concept of subqueries and their use cases in SQL in the module
• Writing subqueries in the WHERE clause to filter data based on the result of another query within the Python module
• Using subqueries in the SELECT clause to retrieve calculated values in the module
• Understanding correlated subqueries and their behavior in the module
• Using subqueries in the FROM clause to treat the result of a query as a table in the module

8. Module: Window Functions for Advanced Analysis

• Understanding the concept and benefits of window functions in SQL in the module
• Using ranking window functions (ROW_NUMBER(), RANK(), DENSE_RANK()) within the Python module
• Using aggregate window functions (SUM() OVER(), AVG() OVER()) for calculations within partitions in the module
• Using window functions for analytical tasks like moving averages and running totals in the module
• Understanding the PARTITION BY and ORDER BY clauses within window functions in the module

General remarks

• Customizable courses are available to address the specific needs of your organization.
• The participant must be conversant in English
• Participants who successfully complete this course will receive a certificate of completion from Lenol Development Center.
• The course fee for onsite training includes facilitation training materials, tea break and lunch.
• Accommodation and airport pick up are made upon request
• For any inquiries reach us through info@lenoldevelopmentcenter.com or +254 710 314 746
• Payment should be made to our bank