Ementorhub

What you'll learn

Integrate and scale data pipelines using AWS Lambda and Glue for efficient data processing

Analyze real-time data streams with Kinesis Analytics and OpenSearch to gain actionable insights

Implement security measures and manage data workflows for high-performance analysis

Analyze real-time data streams with Kinesis Analytics and OpenSearch to gain actionable insights

Skills you'll gain

Apache Spark

Amazon Web Services

Scalability

Data Pipelines

Extract, Transform, Load

Serverless Computing

Performance Tuning

Data Processing

Real Time Data

Amazon S3

Amazon Redshift

Data Warehousing

AWS Kinesis

Apache Hive

Data Visualization

Apache Hadoop

There are 2 modules in this course

The course also delves into processing large datasets using Amazon EMR, where you’ll work with Apache Spark, Hive, and other tools in the Hadoop ecosystem. You’ll learn to optimize data processing with EMR, partition and store data efficiently, and integrate it with AWS services like Kinesis and Redshift. Exercises in Apache Spark will show you how to analyze data streams and deliver actionable insights in real time. Lastly, you'll focus on the analysis aspect using services like Kinesis Analytics, OpenSearch, and Athena. The course will guide you through setting up advanced analytics using Kinesis, creating real-time monitoring applications, and visualizing data using OpenSearch and QuickSight. By the end of this course, you’ll be well-equipped to build, process, and analyze data pipelines at scale using AWS’s powerful tools. This course is ideal for data engineers, IT professionals, and data analysts aiming to leverage AWS for data processing and analysis. Some familiarity with AWS services is recommended.

Domain 4: Analysis