Building Modern Data Analytics Solutions on AWS Course in US

Master modern data architectures with hands-on AWS tools

32 hours of expert-led training sessions

Four intermediate-level AWS course options to explore

Learn from AWS-certified instructors with real-world expertise

Access to expert-led lessons, labs & case studies

Flexible learning options to fit your schedule & learning style

Various payment methods with instalment plans available

4.9/5

6096 EnrolledEnrolled Learners

4.9/5

6096 EnrolledEnrolled Learners

Overview

What you will master with us:

Manage data lakes using AWS Lake Formation
Develop analytics pipelines with Amazon EMR
Run batch data analysis via Apache Spark on EMR
Handle real-time data using Amazon Kinesis
Optimise Redshift security for data analytics
Use AWS Glue for scalable data storage
Design streaming solutions using Amazon MSK

Upcoming sessions

Curriculum

Introduction to Data Lakes

Data ingestion, cataloging and preparation

Building a Data Lake with AWS Lake formation

Data processing and analysis

Additional Lake formation configurations

Modern data architecture

Overview of Data Analytics and the Data Pipeline

Introduction to Amazon EMR

Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage

High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR

Processing and Analysing Batch Data with Amazon EMR and Apache Hive

Serverless Data Processing

Security and Monitoring of Amazon EMR Clusters

Designing Batch Data Analytics Solutions

Developing Modern Data Architectures on AWS

Overview of Data Analytics and the Data Pipeline

Using Amazon Redshift in the Data Analytics Pipeline

Introduction to Amazon Redshift

Ingestion and Storage

Processing and Optimizing Data

Security and Monitoring of Amazon Redshift Clusters

Designing Data Warehouse Analytics Solutions

Developing Modern Data Architectures on AWS

Overview of Data Analytics and the Data Pipeline

Using Streaming Services in the Data Analytics Pipeline

Introduction to AWS Streaming Services

Using Amazon Kinesis for Real-time Data Analytics

Securing, Monitoring and Optimizing Amazon Kinesis

Using Amazon MSK in Streaming Data Analytics Solutions

Securing, Monitoring and Optimizing Amazon MSK

Designing Streaming Data Analytics Solutions

Developing Modern Data Architectures on AWS

Meet your Trainer

Our Trainers

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.

Learning Outcomes

After you complete this training, you will be able to:

Learn AWS Lake Formation to create secure, scalable and well-governed cloud-based data lakes

Build efficient, high-performance data analytics pipelines utilising the full capabilities of Amazon EMR

Get practical experience using Apache Spark for processing large-scale batch data analytics workflows

Set up real-time data streaming and analytics applications using powerful Amazon Kinesis tools

Design robust and scalable data warehousing solutions with advanced features of Amazon Redshift

Enhance, secure and manage data storage and ETL workflows effectively using AWS Glue services

Ready to get started?

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 the Building Modern Data Analytics Solutions on AWS Course, we recommend that you fulfil these eligibility requirements:

Understanding of relational databases and data warehousing basics
Previous experience with data analytics tools and techniques
Hands-on knowledge of core AWS services like S3, EC2 and IAM
Basic skills in scripting languages, such as Python
Familiarity with ETL (Extract, Transform, Load) workflows and data preparation techniques
Knowing the basics of networking, including VPC, subnets and security groups

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Frequently asked questions

Professionals can design, implement, and manage safe, scalable analytics systems that leverage AWS cloud-native services with the support of the four primary AWS courses that comprise the Building Modern Data Analytics Systems on AWS course. In a modern data environment, we focus on efficient data collecting, archiving, processing, analysis, and visualization.

Cloud computing, e-commerce, finance, and tech companies make the most from experts trained in AWS data analytics. You can seek jobs in fields ranging from data engineering to business intelligence.

Before this course, you must have a general idea about data analytics tools, relational databases, and core AWS services like S3, EC2, and IAM. Some knowledge about Python scripting languages and general networking concepts would be helpful.

Although there are no specific academic requirements, relevant experience with cloud services or data analytics is preferred. If you have no AWS experience, we suggest gaining exposure to data analytics, cloud technologies, or ETL processes before joining this course.

The course is separated into four fundamental modules:

Building Data Lakes
Batch Data Analytics Solutions
Data Analytics using Amazon Redshift
Streaming Data Analytics Solutions

Each module consists of detailed topics like AWS Lake Formation, Amazon Kinesis, EMR, Apache Spark, and Redshift, with an emphasis on hands-on training.