AWS-BDAS - 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.

INR 15000 + tax

Date : 30 Jul 2024

Code: aws-bdas

Duration: 1.0 day

other dates

Schedule

Virtual ILT | 30 Jul 2024 - 30 Jul 2024
Virtual ILT | 20 Aug 2024 - 20 Aug 2024
Virtual ILT | 03 Sep 2024 - 03 Sep 2024
Virtual ILT | 15 Oct 2024 - 15 Oct 2024
Virtual ILT | 05 Nov 2024 - 05 Nov 2024
Virtual ILT | 10 Dec 2024 - 10 Dec 2024

Start learning today!

Click Hereto customize your Training

Objectives

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

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 architecture

Audience

This course is intended for:
  • Data platform engineers 
  • Architects and operators who build and manage data analytics pipelines

Prerequisites

Students with a minimum of 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:

Certification

product-certification

Course Benefits

product-benefits
  • Career growth
  • Broad Career opportunities
  • Worldwide recognition from leaders
  • Up-to Date technical skills
  • Popular Certification Badges

AWS Popular Courses

aws-ssds

In this course you will learn to use Amazon SageMaker Studio to boost productivity at every step of the ML lifecycle.

aws-coa

This course teaches systems operators, and anyone performing cloud operations functions how to manage and operate automatable and repeatable deployments of netw

aws-me

AWS Migrations Essentials is a comprehensive set of tools, services, and best practices offered by Amazon Web Services (AWS) to simplify and streamline the proc

aws-dev

In this course, you learn how to use the AWS SDK to develop secure and scalable cloud applications using multiple AWS services
Enquire Now
 
 
 
 
nklc9p
By clicking "Submit", I agree to the Terms Of Use and Privacy Policy