Training on Advanced SQL for Data Analytics

Course Objectives

By the end of this course, participants will be able to:

• Write complex SQL queries to perform in-depth data analysis.
• Utilize advanced SQL functions and techniques for data manipulation and transformation.
• Optimize SQL queries for performance and efficiency in large datasets.
• Implement window functions to perform advanced analytical calculations.
• Work with various SQL data types and convert between them effectively.
• Use SQL for data cleaning, aggregation, and reporting.
• Apply SQL in real-world data analysis scenarios.
• Create and manage indexes to improve query performance.
• Integrate SQL with other data analysis tools and platforms.
• Develop strategies for handling large datasets and optimizing storage in SQL databases.

Course Outline:

Module 1: SQL Performance Optimization

• Query execution plans and performance analysis
• Indexing strategies and techniques
• Query rewriting and simplification
• Partitioning and sharding for large datasets

Module 2: Advanced Data Modeling

• Dimensional and snowflake schemas
• Star and fact tables
• Data warehousing concepts
• Data modeling for analytics and reporting

Module 3: Window Functions and Analytical Queries

• Ranking and partitioning data
• Calculating running totals, moving averages, and cumulative sums
• Lead and lag functions for data analysis
• Advanced window functions for complex calculations

Module 4: Recursive Queries and Common Table Expressions (CTEs)

• Hierarchical data and recursive queries
• Creating and using CTEs for complex logic
• Recursive CTEs for tree-like structures

Module 5: Regular Expressions and Pattern Matching

• Regular expression syntax and functions
• Text mining and information extraction
• Data cleaning and standardization using regular expressions

Module 6: Advanced Joins and Set Operations

• Beyond inner and outer joins
• Full outer joins and self-joins
• Set operations (UNION, INTERSECT, EXCEPT)
• Advanced join optimization

Module 7: Subqueries and Correlated Subqueries

• Nested queries and correlated subqueries
• EXISTS and NOT EXISTS operators
• IN and ANY/ALL operators

Module 8: SQL for Data Analysis and Business Intelligence

• Creating reports and dashboards
• Data visualization with SQL
• Predictive analytics with SQL
• SQL for machine learning

Module 9: SQL for Big Data

• SQL on Hadoop and Spark
• Distributed SQL processing
• Handling large datasets with SQL

Module 10: Case Studies and Real-world Applications

• In-depth analysis of real-world datasets
• SQL for fraud detection, customer segmentation, and churn analysis
• Performance optimization case studies
• Data modeling and warehousing projects

Customized Training

This training can be tailored to your institution needs and delivered at a location of your choice upon request.

Requirements

Participants need to be proficient in English.

Training Fee

The fee covers tuition, training materials, refreshments, lunch, and study visits. Participants are responsible for their own travel, visa, insurance, and personal expenses.

Certification

A certificate from Ideal Sense & Workplace Solutions is awarded upon successful completion.

Accommodation

Accommodation can be arranged upon request. Contact via email for reservations.

Payment

Payment should be made before the training starts, with proof of payment sent to outreach@idealsense.org.
For further inquiries, please contact us on details below:

Email: outreach@idealsense.org

Mobile: +254759708394