The SAS Technologies and Platforms for Big Data Processing is designed for software architects and software developers. This course provides a comprehensive exploration of the technologies and platforms that are essential for processing Big Data. Students will delve into the fundamental concepts, tools, and methodologies that enable efficient handling, analysis, and visualization of large-scale data. By the end of the course, participants will have a solid understanding of how to leverage Big Data technologies to derive actionable insights and support data-driven decision making.

OBJECTIVES

Understand Big Data Fundamentals

Explore Data Storage Solutions

Master Data Processing Frameworks

Analyze Data in Real-Time

Utilize Cloud Platforms

Develop Big Data Applications

PREREQUISITES

Knowledge of software engineering fundamentals and Python language.

PROGRAMME

Introduction to Docker

The Lambda Architecture

Optimized Storage Formats (Columnar DBs)

Think Functional - Scalar Functions

Think Functional – Collection

Think Fluent (Fluent programming)

Distributed File Systems (HDFS)

The MapReduce approach

Think Asynchronous (Event-based programming)

Analyze Big Data (Spark-Core)

Structured (Big) Data and ML (Spark-SQL and Spark-ML)

Rea-Time (Big) Data processing (Spark Window Function)

Cloud platforms for training and deployment of models.