Building Batch Data Analytics Solutions on AWS Course in Saudi Arabia
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
4.8/54511 EnrolledEnrolled Learners
4.8/54511 EnrolledEnrolled Learners
Overview
What you will learn:
- Develop large-scale batch data processing solutions with Amazon EMR
- Explore data ingestion methods using tools like Apache Hive and HBase
- Optimise data storage and management within Amazon EMR clusters
- Work with Apache Spark on EMR to analyse massive datasets
- Use Apache Hive to process and transform batch data workflows
- Get experience building machine learning models with EMR Notebooks
- Implement key security practices to protect Amazon EMR cluster environments
Upcoming sessions
Curriculum
1
Data analytics use cases
2
Using the data pipeline for analytics
1
Using Amazon EMR in analytics solutions
2
Amazon EMR cluster architecture
3
Interactive Demo 1: Launching an Amazon EMR cluster
4
Cost management strategies
1
Storage optimization with Amazon EMR
2
Data ingestion techniques
1
Apache Spark on Amazon EMR use cases
2
Why Apache Spark on Amazon EMR
3
Spark concepts
4
Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell
5
Transformation, processing, and analytics
6
Using notebooks with Amazon EMR
7
Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR
1
Using Amazon EMR with Hive to process batch data
2
Transformation, processing, and analytics
3
Practice Lab 2: Batch data processing using Amazon EMR with Hive
4
Introduction to Apache HBase on Amazon EMR
1
Serverless data processing, transformation, and analytics
2
Using AWS Glue with Amazon EMR workloads
3
Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions
1
Securing EMR clusters
2
Interactive Demo 3: Client-side encryption with EMRFS
3
Monitoring and troubleshooting Amazon EMR clusters
4
Demo: Reviewing Apache Spark cluster history
1
Batch data analytics use cases
2
Activity: Designing a batch data analytics workflow
1
Modern data architectures
Meet your Trainer
Our Trainers
We, at Learners Point, take immense pride in our teaching methods and instructors. Our instructors are some of the best experts in their fields and employ a practical approach to learning. Many of them are globally recognised and have a diverse set of experience in their field of expertise. You are always sure to have the best in the industry as your teachers who are ready to guide you at every step and make the experience informative yet enjoyable. Apart from the focus on learning your chosen course, our instructors also encourage students to develop communication skills and interpersonal skills necessary to excel in the practical world.
Our cutting edge teaching methods make every program an immersive and productive experience for the learners. Our learning methods are research-driven and are continuously updated to stay relevant to present times as well as the future. You will enjoy practical applications of everything learned through theory and regular mock examinations to help monitor your progress. Our courses are led by an instructor in a classroom setup and we do offer online high-quality sessions as well for individuals. We also monitor the training sessions with a progress tracker to maintain high standards of instruction & ethics.
Learning Outcomes
After you complete this training, you will be able to:
1
Design and implement batch data analytics solutions with Amazon EMR & 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 & cluster performance in Amazon EMR to deliver cost-optimised solutions
6
Efficiently work with Spark and Hadoop for real-time data analysis and insights
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
Prerequisites
To enrol in our Building Batch Data Analytics Solutions on AWS Course, you must fulfil these criteria:
- A minimum of one year of experience in managing open-source data frameworks such as Apache Spark or Apache Hadoop
- Completed either AWS Technical Essentials or Architecting on AWS
- Completed either Building Data Lakes on AWS or Getting Started with AWS Glue
Overall ratings by our students
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Frequently asked questions
Our Building Batch Data Analytics Solutions on AWS Course in KSA trains professionals to design, build and manage scalable batch data processing pipelines by using AWS services. This 8-hour course is perfect for IT professionals, data engineers, and cloud practitioners.
To enrol in our Building Batch Data Analytics Solutions on AWS Course, you must fulfil the following eligibility criteria:
- At least 1 year of experience in managing open-source data frameworks such as Apache Spark or Apache Hadoop
- Completed either Building Data Lakes on AWS or Getting Started with AWS Glue
- Completed either AWS Technical Essentials or Architecting on AWS
Our training focuses on both conceptual knowledge and practical expertise for creating scalable, automated batch data pipelines with AWS services. In this course, you will learn the following:
- Build and manage scalable data pipelines with Amazon EMR
- Use AWS Glue to prepare and transform data at scale
- Automate workflows with AWS Step Functions, Lambda & Amazon EventBridge
- Store, catalog and query data using Amazon S3, AWS Glue Data Catalog and Amazon Athena
- Run ETL jobs and analytics using Amazon EMR, AWS Glue and Amazon Redshift
In this AWS course, participants work with the most important AWS services needed for designing and managing batch data processing pipelines. These are:
- Amazon EMR
- AWS Glue
- AWS Step Functions
- Amazon S3
- Amazon RDS
- Amazon Redshift
- Amazon CloudWatch
After completing this AWS training, professionals can apply for career-rewarding job roles in Riyadh. Some of these are listed below:
- Cloud Data Architect
- Data Engineer
- AWS Solutions Architect
- Big Data Engineer
- Machine Learning Engineer
Yes, this course is perfect for transitioning your skills to the cloud. You learn how to build scalable pipelines on Amazon EMR, work with Apache Spark and Hive, and optimise storage and performance. We also help you gain hands-on experience with AWS Step Functions and Glue, preparing you for cloud-first roles.
Yes, our Building Batch Data Analytics Solutions on AWS Course in KSA is built around hands-on labs, including EMR Notebooks for machine learning tasks. You work with real datasets and AWS services, not just learn concepts. This helps you apply skills immediately in your role.
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