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SQL for Data Analysis

Learn to effectively query and analyze data using SQL, the leading language for database management.

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Certificate :

After Completion

Start Date :

10-Jan-2025

Duration :

30 Days

Course fee :

$150

COURSE DESCRIPTION:

  1.  Learn to effectively query and analyze data using SQL, the leading language for database management.

  2. Gain skills in extracting valuable insights from intricate datasets and executing advanced queries.

  3. Understand how to utilize SQL for data cleaning, aggregation, and comprehensive reporting.

  4. Suitable for both beginners and those seeking to refine their existing skills.

  5. Prepare to tackle real-world data analysis challenges with assurance and expertise.

CERTIFICATION:

  1. Earn a Certified SQL Data Analyst credential to validate your expertise in using SQL for data analysis and reporting.

LEARNING OUTCOMES:

By the conclusion of the course, participants will possess the skills to:

  1. Grasp the basics of SQL, focusing on SELECT queries, WHERE conditions, and joins.

  2. Execute data aggregation, filtering, and sorting to derive valuable insights.

  3. Apply advanced SQL methods, including subqueries, window functions, and common table expressions (CTEs).

  4. Prepare and cleanse data by addressing duplicates, NULL values, and formatting challenges.

  5. Construct intricate queries for data manipulation and reporting purposes.

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Course Curriculum

Introduction to SQL and Data Analysis
  1. Understanding SQL
    • What is SQL? Its importance in data analysis.
    • Overview of relational databases and database management systems (DBMS).
  2. Getting Started
    • Setting up a database environment: MySQL, PostgreSQL, or SQLite.
    • Introduction to SQL tools (DBeaver, pgAdmin, MySQL Workbench).
SQL Basics
  1. Working with Tables
    • Understanding database schema.
    • Creating, modifying, and deleting tables.
  2. Data Retrieval
    • SELECT statements for querying data.
    • Filtering data with WHERE clauses.
    • Sorting results with ORDER BY.
Advanced Querying
  1. Aggregation and Grouping
    • Using functions like COUNT(), SUM(), AVG(), MIN(), and MAX().
    • Grouping data with GROUP BY.
    • Filtering grouped data with HAVING.
  2. Joins and Relationships
    • Inner, left, right, and full outer joins.
    • Combining data from multiple tables.
    • Understanding primary and foreign keys.
Data Manipulation
  1. Modifying Data
    • Inserting new records with INSERT.
    • Updating existing records with UPDATE.
    • Deleting records with DELETE.
  2. Subqueries
    • Writing subqueries for nested data retrieval.
    • Correlated subqueries for dynamic filtering.
Advanced SQL Features
  1. Window Functions
    • Using OVER() for ranking, running totals, and percentiles.
    • Applying ROW_NUMBER(), RANK(), and NTILE().
  2. Common Table Expressions (CTEs)
    • Creating reusable query blocks with WITH.
    • Recursive CTEs for hierarchical data.
  3. Set Operations
    • Using UNION, INTERSECT, and EXCEPT.
Data Cleaning with SQL
  1. Handling Missing Data
    • Using NULL functions like COALESCE() and ISNULL().
    • Filtering and replacing missing values.
  2. Text Manipulation
    • Using functions like CONCAT(), SUBSTRING(), and TRIM().
    • Regular expressions for pattern matching.
  3. Date and Time Functions
    • Working with DATE, TIME, and DATETIME types.
    • Using functions like DATEDIFF(), DATEADD(), and EXTRACT().
Performance Optimization
  1. Indexing
    • Understanding indexes and their impact on query performance.
    • Creating and managing indexes.
  2. Query Optimization
    • Analyzing query execution plans.
    • Writing efficient SQL queries.
  3. Partitioning
    • Partitioning tables for better performance.
    • Querying partitioned tables.
Capstone Project
  1. End-to-End Data Analysis
    • Designing and querying a relational database.
    • Cleaning, transforming, and analyzing data.
    • Generating insights and creating a final report.

Training Features

Real-World Scenarios

Analyze datasets like sales, customer behavior, or financial data.

Hands-On Practice

Extensive SQL exercises with datasets of varying complexity.

Advanced Techniques

Learn window functions, CTEs, and query optimization for large datasets.

Integration with Analytics Tools

Use SQL alongside BI and programming tools for enhanced analysis.

Project-Based Learning

Work on capstone projects to solidify your skills.

Certification

Earn a certificate of completion to showcase your SQL expertise.

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