Building Batch Data Analytics Solutions on AWS (BBDAS)

 

Course Overview

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.

Who should attend

This course is intended for:

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

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 recommend that attendees of this course have:

Course Objectives

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

Course Content

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

Prijs & Delivery methods

Online training

Duur
1 dag

Prijs
  • 795,– €
Beschikbare data
Vraag een datum aan
Klassikale training

Duur
1 dag

Prijs
  • Nederland: 795,– €
  • België: 795,– €
Beschikbare data
Vraag een datum aan

Beschikbare data

Fast Lane will carry out all guaranteed training regardless of the number of attendees, exempt from force majeure or other unexpected events, like e.g. accidents or illness of the trainer, which prevent the course from being conducted.
Instructor-led Online Training:   Dit is een Instructor-Led Online (ILO) training: een online training verzorgd door een trainer.
Dit is een FLEX-training: een training die zowel klassikaal als online gevolgd kan worden. Je kiest zelf de gewenste leervorm.

Engels

Tijdzone: Midden-Europese Tijd (MET)   ±1 uur

Online training Tijdzone: Greenwich Mean Time (GMT) Gegarandeerde doorgang
Online training Tijdzone: Greenwich Mean Time (GMT)
Online training Tijdzone: British Summer Time (BST)
Online training Tijdzone: British Summer Time (BST)
Online training Tijdzone: Greenwich Mean Time (GMT)
Dit is een FLEX-training: een training die zowel klassikaal als online gevolgd kan worden. Je kiest zelf de gewenste leervorm.

Europa

Zwitserland

 Zürich Dit is een FLEX-training.   Tijdzone: Midden-Europese Tijd (MET) boek direct:
de online FLEX-training
de klassikale FLEX-training
Zürich Dit is een FLEX-training.   Tijdzone: Midden-Europese Tijd (MET) boek direct:
de online FLEX-training
de klassikale FLEX-training
Zürich Dit is een FLEX-training.   Tijdzone: Midden-Europese Zomertijd (MEZT) boek direct:
de online FLEX-training
de klassikale FLEX-training
Zürich Dit is een FLEX-training.   Tijdzone: Midden-Europese Zomertijd (MEZT) boek direct:
de online FLEX-training
de klassikale FLEX-training
Zürich Dit is een FLEX-training.   Tijdzone: Midden-Europese Zomertijd (MEZT) boek direct:
de online FLEX-training
de klassikale FLEX-training