Design batch data analytics solutions using Amazon EMR & Spark
8 hours of course duration
Includes nine extensive & well-structured modules
Grasp in-demand skills for data engineering roles
Receive guided sessions from expert instructors
Learn through practice labs and interactive demos
Easy-to-fit weekend sessions for your hectic calendar
Convenient payment options with monthly instalments
What you will master with us:
Upcoming sessions
Data analytics use cases
Using the data pipeline for analytics
Using Amazon EMR in analytics solutions
Amazon EMR cluster architecture
Interactive Demo 1: Launching an Amazon EMR cluster
Cost management strategies
Storage optimisation with Amazon EMR
Data ingestion techniques
Apache Spark on Amazon EMR use cases
Why Apache Spark on Amazon EMR
Spark concepts
Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell
Transformation, processing, and analytics
Using notebooks with Amazon EMR
Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR
Using Amazon EMR with Hive to process batch data
Transformation, processing, and analytics
Practice Lab 2: Batch data processing using Amazon EMR with Hive
Introduction to Apache HBase on Amazon EMR
Serverless data processing, transformation, and analytics
Using AWS Glue with Amazon EMR workloads
Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions
Securing EMR clusters
Interactive Demo 3: Client-side encryption with EMRFS
Monitoring and troubleshooting Amazon EMR clusters
Demo: Reviewing Apache Spark cluster history
Batch data analytics use cases
Activity: Designing a batch data analytics workflow
Modern data architectures
After completion of this course, you will be able to:
1
Gain expertise in designing and implementing batch data analytics solutions using Amazon EMR and Apache Spark
2
Use AWS Step Functions to coordinate and automate complex data processing workflows
3
Follow best practices to enhance security, performance and cost-efficiency within EMR environments
4
Integrate tools like Apache Hive, HBase and AWS Glue for smooth and scalable data processing operations
5
Improve storage efficiency and cluster performance in Amazon EMR to deliver cost-optimised solutions
To enrol in the Building Batch Data Analytics Solutions on AWS Course in Oman, candidates must fulfil these eligibility requirements:
Overall ratings by our students
Learn now, pay later
Dive into your course now and pay in installments


The goal of our Building Batch Data Analytics Solutions on AWS Course in Oman is to train professionals with the knowledge and abilities necessary to plan, create, and oversee scalable batch data processing pipelines utilizing essential AWS services. Data engineers, cloud practitioners, and IT specialists will find this course useful.
AWS Step Functions is a product that enables you to automate and manage the running of multiple AWS services and workflows. You'll see how to apply Step Functions to simplify data processing pipelines and maximize batch analytics automation in this course.
The course is divided into nine modules, covering:
As a Data Engineer in Oman, enrolling in our Building Batch Data Analytics Solutions on AWS course will improve your skills to a great extent to design, develop, and manage scalable data pipelines through Amazon EMR, Apache Spark, and Hadoop. You will become proficient at optimizing data storage, data transformation operations, and using AWS tools such as Apache Hive and AWS Glue for efficient data processing.
Our course teaches data ingestion with Apache Hive, HBase, and AWS Glue, and performance and cost optimization methods. These skills help optimise your present workflow as a professional in the data analytics or cloud engineering domain. Discover how to integrate Apache Spark with EMR for processing large data, apply security best practices, and automate workflows with AWS Step Functions.
Certified experts have the following career prospects:
Yes, this Building Batch Data Analytics Solutions on AWS training is ideal for your transition. It focuses on Amazon EMR, Apache Spark, and Hadoop for building scalable pipelines. We include hands-on work with Hive, HBase, and Step Functions, key tools in any modern cloud data stack.