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Building Batch Data Analytics Solutions on AWS

Duration: 1 Day (8 Hours)

Building Batch Data Analytics Solutions on AWS Course Overview:

In this Building Batch Data Analytics Solutions on AWS course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR.

Course level: Intermediate

Intended audience:

  • Data platform engineers
  • Architects and operators who build and manage data analytics pipelines
Module A: Overview of Data Analytics and the Data Pipeline
  • 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
    Module B: Developing Modern Data Architectures on AWS
  • Modern data architectures

Course Prerequisites :

Students with a minimum one-year experience managing open-source data frameworks such as Apache Spark or Apache Hadoop will benefit from this course.

We suggest the AWS Hadoop Fundamentals course for those that need a refresher on Apache Hadoop.
We recommend that attendees of this course have:

Q: What is Building Batch Data Analytics Solutions on AWS training?

A: The training is a comprehensive program designed to provide individuals with the knowledge and skills needed to design, implement, and optimize batch data analytics solutions using Amazon Web Services (AWS). It covers various aspects of batch data processing, data transformation, and analytics using AWS services such as AWS Glue, Amazon EMR, and Amazon S3.

A: This training is suitable for data engineers, data analysts, data scientists, and IT professionals who want to leverage AWS services for building scalable and efficient batch data analytics solutions. It is beneficial for those involved in data processing, data transformation, and performing analytics on large datasets.

A: The training covers a range of topics, including batch data processing concepts, data ingestion strategies, data transformation using AWS Glue, data analytics with Amazon EMR and Apache Spark, data storage and management with Amazon S3, and best practices for building scalable and cost-effective batch data analytics solutions on AWS.

Students with a minimum one-year experience managing open-source data frameworks such as Apache Spark or Apache Hadoop will benefit from this course.

We suggest the AWS Hadoop Fundamentals course for those that need a refresher on Apache Hadoop.
We recommend that attendees of this course have:

A: To prepare for the training, it is recommended to have a good understanding of data processing concepts, SQL queries, and programming languages like Python or Scala. Familiarizing yourself with AWS services like AWS Glue, Amazon EMR, and Amazon S3 will also be beneficial. Exploring AWS documentation and hands-on exercises related to batch data processing can enhance your preparation.

A: Yes, we offer online training options for Building Batch Data Analytics Solutions on AWS to provide flexibility for learners.

A: While Building Batch Data Analytics Solutions on AWS training provides valuable knowledge and skills in building batch data analytics solutions, it does not directly prepare you for specific AWS certifications. However, it lays a solid foundation for pursuing advanced certifications related to data analytics or AWS architecture.

Discover the perfect fit for your learning journey

Choose Learning Modality

Live Online

  • Convenience
  • Cost-effective
  • Self-paced learning
  • Scalability

Classroom

  • Interaction and collaboration
  • Networking opportunities
  • Real-time feedback
  • Personal attention

Onsite

  • Familiar environment
  • Confidentiality
  • Team building
  • Immediate application

Training Exclusives

This course comes with following benefits:

  • Practice Labs.
  • Get Trained by Certified Trainers.
  • Access to the recordings of your class sessions for 90 days.
  • Digital courseware
  • Experience 24*7 learner support.

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