Building Data Lakes on AWS Certification Training - CloudThat - Training

Course Overview

In this Building Data Lakes on AWS certification training course from CloudThat, candidates learn how to build an operational data lake to analyze both structured and unstructured data. Taking up this training on building Data Lakes on AWS, candidates are trained to use the various components and functionality of the services to create a data lake in AWS.

This Building Data Lakes on AWS certification training teaches candidates how to use AWS Glue to build a data catalog, AWS Lake Formation to build a data lake, and Amazon Athena to analyze data. The course comprises presentations, lectures, hands-on labs, and group exercises.

After completing this course, students will be able to:

  • Apply data lake methodologies in planning and designing a data lake
  • Articulate the components and services required for building an AWS data lake
  • Secure a data lake with appropriate permission
  • Ingest, store, and transform data in a data lake
  • Query, analyze, and visualize data within a data lake

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Key Features

  • Our Building Data Lakes on AWS training modules have 50% - 60% hands-on lab sessions to encourage Thinking-Based Learning (TBL).
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL).
  • AWS certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL).
  • Well-structured use-cases to simulate challenges encountered in a Real-World environment.
  • Being an authorized AWS Training Partner gives us an edge over competition.
  • Integrated teaching assistance and support through experts designed Learning Management System (LMS) and ExamReady platform.

Who Should Attend

  • Data platform engineers
  • Solutions architects
  • IT professionals

Prerequisites

We recommend that attendees of this building Data Lakes on AWS certification training course have:

  • Completed the AWS Technical Essentials classroom course
  • One year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals digital course

Course Outline Download Course Outline

  • Describe the value of data lakes
  • Compare data lakes and data warehouses
  • Describe the components of a data lake
  • Recognize common architectures built on data lakes

  • Describe the relationship between data lake storage and data ingestion
  • Describe AWS Glue crawlers and how they are used to create a data catalog
  • Identify data formatting, partitioning, and compression for efficient storage and query
  • Lab 1: Set up a simple data lake

  • Recognize how data processing applies to a data lake
  • Use AWS Glue to process data within a data lake
  • Describe how to use Amazon Athena to analyze data in a data lake

  • Describe the features and benefits of AWS Lake Formation
  • Use AWS Lake Formation to create a data lake
  • Understand the AWS Lake Formation security model
  • Lab 2: Build a data lake using AWS Lake Formation

  • Automate AWS Lake Formation using blueprints and workflows
  • Apply security and access controls to AWS Lake Formation
  • Match records with AWS Lake Formation FindMatches
  • Visualize data with Amazon QuickSight
  • Lab 3: Automate data lake creation using AWS Lake Formation blueprints
  • Lab 4: Data visualization using Amazon QuickSight

  • Post course knowledge check
  • Architecture review
  • Course review

Certification

    • By earning Building Data Lakes on AWS certification, you will show your future or current employer that you have knowledge of AWS Cloud concepts.
    • Building Data Lakes on AWS certification can be used to learn building operational data lake on AWS platforms.
    • On successful completion of Building Data Lakes on AWS certification training aspirants receive a Course Completion Certificate from us
    • By successfully clearing the Building Data Lakes on AWS certification exams, aspirants earn AWS Certification

Course Fee

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Course ID: 8534

Course Price at

₹ 19900 + 18% GST

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