HemSök efter kurserBuilding Batch Data Analytics Solutions on AWS

Building Batch Data Analytics Solutions on AWS

In this 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.

This course is part of the Building Modern Data Analytics Solutions on AWS collection of four, one-day, intermediate-level classroom training courses.


Utbildningsformer
Remote

Längd
1 dag

Pris
9900 kr

Target Group

This course is intended for:

  • Data platform engineers
  • Architects and operators who build and manage data analytics pipelines

Goal

In this course, you will learn to:

  • Compare the features and benefits of data warehouses, data lakes, and modern data architectures
  • Design and implement a batch data analytics solution
  • Identify and apply appropriate techniques, including compression, to optimize data storage
  • Select and deploy appropriate options to ingest, transform, and store data
  • Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case
  • Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
  • Secure data at rest and in transit
  • Monitor analytics workloads to identify and remediate problems
  • Apply cost management best practices

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:

  • Completed either AWS Technical Essentials or Architecting on AWS
  • Completed either Building Data Lakes on AWS or Getting Started with AWS Glue

Buil­ding Batch Data Ana­ly­tics So­lu­tions on AWS - Cour­se out­li­ne

Mo­du­le A: Over­view of Data Ana­ly­tics and the Data Pi­pe­li­ne

  • Data analytics use cases
  • Using the data pipeline for analytics

Mo­du­le 1: Int­ro­duc­tion to Amazon EMR

  • Using Amazon EMR in analytics solutions
  • Amazon EMR cluster architecture
  • Interactive Demo 1: Launching an Amazon EMR cluster
  • Cost management strategies

Mo­du­le 2: Data Ana­ly­tics Pi­pe­li­ne Using Amazon EMR: In­ges­tion and Sto­ra­ge

  • Storage optimization with Amazon EMR
  • Data ingestion techniques

Mo­du­le 3: High-Per­for­mance Batch Data Ana­ly­tics Using Apac­he Spark on Amazon EMR

  • 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

Mo­du­le 4: Proces­sing and Ana­lyzing Batch Data with Amazon EMR and Apac­he Hive

  • 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

Mo­du­le 5: Ser­ver­less Data Proces­sing

  • 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

Mo­du­le 6: Secu­ri­ty and Mo­ni­to­ring of Amazon EMR Clus­ters

  • Securing EMR clusters
  • Interactive Demo 3: Client-side encryption with EMRFS
  • Monitoring and troubleshooting Amazon EMR clusters
  • Demo: Reviewing Apache Spark cluster history

Mo­du­le 7: De­sig­ning Batch Data Ana­ly­tics So­lu­tions

  • Batch data analytics use cases 
  • Activity: Designing a batch data analytics workflow


Mo­du­le B: De­ve­lo­ping Mo­dern Data Arc­hi­tec­tu­res on AWS

  • Modern data architectures

This course includes presentations, interactive demos, practice labs, discussions, and class exercises.