SQL for Data Manipulation

Harness the Power of Structured Query Language
Why This Training?
Data drives the digital age, and SQL is the language that unlocks its potential. With the increasing demand for data manipulation and analysis, SQL stands as the pillar for extracting actionable insights. This course offers a comprehensive journey, from the foundational elements of SQL to its most advanced techniques.
Duration: 15 Hours (online / virtual live session)

 Who Is This For?

Data enthusiasts, business analysts, upcoming data scientists, and anyone eager to gain a robust understanding of SQL for data manipulation and analysis.

Course Breakdown

 Introduction to SQL's Significance: Traverse the evolution of relational databases and understand the pivotal role of SQL in modern data analytics.
 Database Fundamentals: Decode the architecture of databases, gaining clarity on essential concepts like DBMS, RDBMS, tables, and keys.
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 Basic SQL Queries: Dive into the heart of SQL by learning to extract and manipulate data with precision using the SELECT statement, functions, and more.
 Advanced Query Techniques: Master the art of sophisticated querying with joins, subqueries, and result-combining operations.
 Data Manipulation & Modification: Acquire skills to insert, update, delete, and modify the very structure of database tables.
 Data Transformation Techniques: Enhance your data manipulation prowess with advanced string functions, date-time operations, and conditional logic.
 Best Practices & Optimization: Write efficient and high-performing queries, understand their execution, and learn how to refine them for optimal results.
 Conclusion & Interactive Q&A: Solidify your learning, address queries, and discover avenues for advanced SQL exploration.

Training Highlights

 Expert-Led Sessions: Learn from industry veterans who bring real-world experience to the virtual classroom.
 Practical Engagement: Through hands-on exercises and case studies, ensure the application of theoretical concepts.
 Comprehensive Resources: Access to course materials, guides, and cheat sheets for post-training reference and practice.

Materials & Pre-requisites

Software Requirements
A working SQL environment, e.g., MySQL, PostgreSQL, etc.
Sample Databases
Real-world databases provided for practice, aiding in real-time application of concepts.
Passion to Learn
A zeal to delve deep into the world of structured data manipulation.
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Training Content

SQL for Data Manipulation

1. Introduction: The Significance of SQL in Data Analysis

Objective: Emphasize the importance and ubiquity of SQL in data-driven industries.
  • Brief history of relational databases and SQL.
  • Role of SQL in data extraction, transformation, and analysis.

2. Database Fundamentals

Objective: Lay the foundation by introducing databases and their structure.
2.1. What is a Database?
  • Definitions: Database, DBMS, RDBMS.
  • Examples: MySQL, PostgreSQL, Oracle, MS SQL Server.
2.2. Basic Components of a Database
  • Tables, records, fields.
  • Primary key, foreign key, indexes.

3. Basic SQL Queries

Objective: Introduce participants to the core of SQL – querying data.
3.1. SELECT Statement
  • Retrieving all columns vs. specific columns.
  • Using the WHERE clause for filtering.
3.2. Sorting and Limiting Results
  • ORDER BY clause.
  • LIMIT clause for large datasets.
3.3. Functions and Aggregation
  • Common functions: COUNT(), SUM(), AVG(), MIN(), MAX().
  • GROUP BY and HAVING clauses.

4. Advanced Query Techniques

Objective: Delve deeper into more complex querying techniques.
4.1. Joins
  • Joining on multiple criteria.
4.2. Subqueries and Nested Queries
  • Using subqueries in SELECT, FROM, and WHERE clauses.
  • Common pitfalls and best practices.
4.3. Combining Results

5. Data Manipulation and Modification

Objective: Teach participants how to modify datasets using SQL.
5.1. Inserting Data
  • INSERT INTO statement.
  • Adding single vs. multiple records.
5.2. Updating and Deleting Data
  • UPDATE statement with SET and WHERE clauses.
  • DELETE statement.
5.3. Altering Table Structures
  • ALTER TABLE for adding, modifying, and deleting columns.
  • Renaming tables.

6. Data Transformation Techniques

Objective: Explore advanced data manipulation techniques.
6.1. String Functions
6.2. Date and Time Functions
  • Handling different date and time formats.
6.3. Case Statements and Conditional Logic
  • Using CASE for dynamic output based on conditions.

7. Best Practices and Optimization

Objective: Highlight efficient query writing and optimization techniques.
7.1. Writing Efficient Queries
  • Importance of indexes.
  • Avoiding common pitfalls that slow down performance.
7.2. Query Analysis and Execution Plans
  • Understanding how a query is executed.
  • Analyzing bottlenecks and refining query structure.

8. Conclusion & Q&A Session

Objective: Summarize the training and address any questions.
  • Recap of SQL's power in data manipulation.
  • Addressing queries, fostering discussions, and pointing to further resources for deeper exploration.
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