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Building Batch Data Analytics Solutions on AWS

WGAC-AWS-BBDAS

Amazon Web Services
Guaranteed

Building Batch Data Analytics Solutions on AWS

06 Sep 2022 - 1 day

Italian

CET UTC+01:00

£510

Open

Building Batch Data Analytics Solutions on AWS

21 Sep 2022 - 1 day

English

GMT UTC+00:00

£700

Open

Building Batch Data Analytics Solutions on AWS

21 Dec 2022 - 1 day

English

GMT UTC+00:00

£700

Description

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Prerequisites & Audience

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

Course Benefits

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 Topics
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

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