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Building Batch Data Analytics Solutions on AWS Course in Oman

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

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5725 EnrolledEnrolled Learners

Overview

What you will master with 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

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 optimisation 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

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.

Our Trainers

Learning Outcomes

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

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    Prerequisites

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

    • 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

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    Frequently asked questions

    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:

    • Introduction to Amazon EMR and Spark
    • Data Ingestion Methods with Apache Hive and HBase
    • Data Storage Optimization
    • Data Transformation using Apache Hive
    • Machine Learning with EMR Notebooks
    • Security Practices for EMR Cluster Environments
    • Cost and Performance Optimization for EMR
    • AWS Step Functions for Workflow Orchestration

    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:

    • Data Engineering: Creating and developing scalable data pipelines.
    • Cloud Solutions Architect: Designing cloud infrastructure for data processing.
    • Data Scientist: Developing machine learning models with AWS tools.
    • Big Data Analyst: Working with large-scale data in cloud environments.

    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.

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