Building Batch Data Analytics Solutions on AWS Course

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

4.9/5

5825 Enrolled

Overview

What will you learn from us:

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

Learning Outcomes

After completion of this course, you will be able to:

Gain expertise in designing and implementing batch data analytics solutions using Amazon EMR and Apache Spark

Use AWS Step Functions to coordinate and automate complex data processing workflows

Follow best practices to enhance security, performance and cost-efficiency within EMR environments

Integrate tools like Apache Hive, HBase and AWS Glue for smooth and scalable data processing operations

Improve storage efficiency and cluster performance in Amazon EMR to deliver cost-optimised solutions

Get hands-on experience working with Spark and Hadoop for real-time data analysis and insights

Ready to get started?

Prerequisites

To enrol in this Building Batch Data Analytics Solutions on AWS Course, candidates must fulfil these eligibility requirements:

A minimum one-year 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

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Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

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Related courses

Curriculum

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 optimization 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

Frequently asked questions

The Building Batch Data Analytics Solutions on AWS Course is designed to teach professionals how to design, build and manage scalable batch data processing solutions using various Amazon Web Services (AWS) tools. We focus on transforming raw data into data insights through automated, scheduled and event-driven processing workflows.

To enrol in this Building Batch Data Analytics Solutions on AWS Course, candidates must fulfil these eligibility requirements:

1. A minimum of one year of experience in managing open-source data frameworks such as Apache Spark or Apache Hadoop
2. Completed either AWS Technical Essentials or Architecting on AWS
3. Completed either Building Data Lakes on AWS or Getting Started with AWS Glue

Our training is structured to help you gain both conceptual understanding and hands-on expertise in creating scalable, automated batch data pipelines using AWS services. By the end of the course, you will learn these:

1. Design and implement batch data processing architectures using AWS best practices
2. Use AWS Glue to prepare and transform data at scale
3. Automate workflows using AWS Step Functions, Lambda and Amazon EventBridge
4. Store, catalog and query data using Amazon S3, AWS Glue Data Catalog and Amazon Athena
5. Run ETL jobs and analytics using Amazon EMR, AWS Glue and Amazon Redshift
6. Monitor, debug and optimise batch pipelines for performance and cost

During the AWS Training, you will gain several technical skills needed to design, develop and optimise batch data analytics pipelines using AWS services. The key skills you will learn are:

1. Designing Batch Data Architectures
2. Data Ingestion & Storage Management
3. Metadata Management & Data Cataloging
4. ETL Job Development with AWS Glue
5. Workflow Orchestration and Automation
6. Data Querying and Analysis

After completing this training program, you will be well-prepared for a variety of in-demand cloud and data engineering roles. Top career roles you can pursue are:

1. Data Engineer
2. Cloud Data Engineer
3. ETL Developer or Big Data Developer
4. Data Analytics Engineer
5. Data Platform Engineer
6. Solutions Architect

The Building Batch Data Analytics Solutions on AWS Training covers a set of core topics that guide you through designing, building and optimising batch data analytics pipelines using various AWS services. The main topics covered are:

1. Introduction to Batch Data Processing on AWS
2. Data Ingestion and Storage
3. Metadata and Data Cataloging
4. Data Transformation and ETL with AWS Glue
5. Workflow Orchestration and Automation
6. Data Querying and Analytics

No prior EMR experience is needed. This AWS course begins with an introduction to batch data processing on Amazon EMR and guides you through setup, configuration, and optimisation techniques. You get hands-on practice using EMR Notebooks, which support machine learning workflows too.