Data Engineering

Data Engineering is crucial for managing and analyzing big data, supporting advanced analytics applications across various industries. This intensive 4-day workshop delves into the core aspects of data engineering, covering data architecture, ingestion, and storage on major big data platforms like Hadoop and Spark.

Participants will explore cloud technologies for big data and learn practical deployment techniques on AWS and Azure platforms.

Workshop Overview

Learning Outcomes

Gain a foundational understanding of big data platforms' architecture and components.
Acquire practical skills with data ingestion tools such as Kafka and Sqoop.
Explore and implement large-scale storage solutions including HDFS, HBase, and NoSQL databases.
Develop competency in managing and analyzing data with Spark and Hadoop.
Implement secure, scalable data solutions in diverse cloud environments.
Address key data security, compliance, and governance aspects within big data engineering.

Detailed Course Schedule

Day 1:
- Introduction to Big Data Platforms
- Cloud computing technologies
Day 2:
- Data Management and Analysis with Hadoop and Spark

Day 3:
- Security, Compliance, and Capstone Project Design

Targeted, concise lectures complemented by comprehensive digital resources.
Hands-on labs and practical exercises using industry-standard tools and platforms.
Collaborative group projects designed to simulate real-world problem-solving.
Focused discussions on deploying and securing data solutions in cloud environments.
Case studies that highlight practical challenges and solutions in data engineering.
A capstone project that integrates the skills learned, fostering a practical understanding of course materials.