Advanced SQL in Big Data Platforms
( 25 Modules )

Module #1
Introduction to Big Data and SQL
Overview of Big Data, SQL, and the importance of advanced SQL skills in Big Data platforms

Module #2
Big Data Platforms Overview
Introduction to popular Big Data platforms such as Hadoop, Spark, and NoSQL databases

Module #3
SQL Fundamentals Review
Review of basic SQL concepts, including data types, queries, and indexing

Module #4
Big Data SQL Dialects
Introduction to SQL dialects used in Big Data platforms, including Hive, Impala, and Spark SQL

Module #5
Setting Up a Big Data Development Environment
Guidelines for setting up a development environment for Big Data and SQL development

Module #6
Window Functions and Aggregate Analytics
In-depth exploration of window functions and aggregate analytics in Big Data SQL

Module #7
Common Table Expressions (CTEs) and Recursive Queries
Using CTEs and recursive queries to solve complex analytical problems

Module #8
Subqueries and Correlated Queries
Optimizing subqueries and correlated queries for better performance

Module #9
Data Encryption, Security, and Access Control
Securing sensitive data and controlling access in Big Data platforms

Module #10
Optimizing SQL Queries for Big Data
Techniques for optimizing SQL queries for performance and scalability in Big Data platforms

Module #11
Data Ingestion and Integration
Designing data ingestion pipelines and integrating data from various sources

Module #12
Data Transformation and Mapping
Using SQL to transform and map data for analytics and reporting

Module #13
Data Quality and Data Governance
Ensuring data quality and implementing data governance best practices

Module #14
Data Warehousing and Star Schema Design
Designing data warehouses and star schemas for analytics and reporting

Module #15
Real-Time Data Processing and Streaming
Using SQL for real-time data processing and streaming analytics

Module #16
Machine Learning and Predictive Analytics
Using SQL for machine learning and predictive analytics in Big Data platforms

Module #17
Graph Analytics and Network Analysis
Using SQL for graph analytics and network analysis

Module #18
Text Analytics and Natural Language Processing
Using SQL for text analytics and natural language processing

Module #19
Time Series Analysis and Forecasting
Using SQL for time series analysis and forecasting

Module #20
Spatial Analytics and Geospatial Analysis
Using SQL for spatial analytics and geospatial analysis

Module #21
Best Practices for Big Data SQL Development
Guidelines for writing efficient, scalable, and maintainable SQL code

Module #22
Case Study:Customer 360 Analytics
Real-world example of implementing customer 360 analytics using Big Data SQL

Module #23
Case Study:IoT and Sensor Analytics
Real-world example of implementing IoT and sensor analytics using Big Data SQL

Module #24
Case Study:Fraud Detection and Anomaly Analysis
Real-world example of implementing fraud detection and anomaly analysis using Big Data SQL

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Advanced SQL in Big Data Platforms career

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Advanced SQL in Big Data Platforms ( 25 Modules )

Advanced SQL in Big Data Platforms
( 25 Modules )