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Key points about this course

Duration : 2 Days
Course Fee : RM2,599.00

HRD Corp Claimable Course

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AWS Certified Data Analytics Specialty
Exam Code : DAS-C01
  • Maximize your odds of passing the AWS Certified Data Analytics Specialty exam
  • Experienced technologists seeking certification in Big Data technologies on Amazon Web Services
  • Class is taught by AWS expert trainer

Live Virtual Class

Public Class

In-House Training

Private Class

Course Overview

The AWS Certified Data Analytics Specialty Exam is one of the most challenging certification exams you can take from Amazon. Passing it tells employers in no uncertain terms that your knowledge of big data systems is wide and deep. But, even experienced technologists need to prepare heavily for this exam. This course sets you up for success, by covering all of the big data technologies on the exam and how they fit together.

The world of data analytics on AWS includes a dizzying array of technologies and services. Just a sampling of the topics we cover in-depth are:

  • Streaming massive data with AWS Kinesis
  • Queuing messages with Simple Queue Service (SQS)
  • Wrangling the explosion data from the Internet of Things (IOT)
  • Transitioning from small to big data with the AWS Database Migration Service (DMS)
  • Storing massive data lakes with the Simple Storage Service (S3)
  • Optimizing transactional queries with DynamoDB
  • Tying your big data systems together with AWS Lambda
  • Making unstructured data query-able with AWS Glue
  • Processing data at unlimited scale with Elastic MapReduce, including Apache Spark, Hive, HBase, Presto, Zeppelin, Splunk, and Flume
  • Applying neural networks at massive scale with Deep Learning, MXNet, and Tensorflow
  • Applying advanced machine learning algorithms at scale with Amazon SageMaker
  • Analyzing streaming data in real-time with Kinesis Analytics
  • Searching and analyzing petabyte-scale data with Amazon Elasticsearch Service
  • Querying S3 data lakes with Amazon Athena
  • Hosting massive-scale data warehouses with Redshift and Redshift Spectrum
  • Integrating smaller data with your big data, using the Relational Database Service (RDS) and Aurora
  • Visualizing your data interactively with Quicksight
  • Keeping your data secure with encryption, KMS, HSM, IAM, Cognito, STS, and more

Throughout the course, you'll have lots of opportunities to reinforce your learning with hands-on exercises and quizzes. And when you're done, this course includes a practice exam that's very similar to the real exam in difficulty, length, and style - so you'll know if you're ready before you invest in taking it. We'll also arm you with some valuable test-taking tips and strategies along the way.

Data analytics is an advanced certification, and it's best tackled by students who have already obtained associate-level certification in AWS and have some real-world industry experience. This exam is not intended for AWS beginners.

Course Prerequisites
  • You must have an AWS account to follow along with the hands-on activities. The services used will cost a few dollars in AWS fees (it costs us $5 USD)
  • AWS recommends associate-level certification before attempting the AWS Data Analytics exam. It is an advanced and challenging exam.

Who this course is for

  • Experienced technologists seeking certification in Big Data technologies on Amazon Web Services.
Course Objectives
  • Maximize your odds of passing the AWS Certified Data Analytics Specialty exam
  • Move and transform massive data streams with Kinesis
  • Store big data with S3 and DynamoDB in a scalable, secure manner
  • Process big data with AWS Lambda and Glue ETL
  • Use the Hadoop ecosystem with AWS using Elastic MapReduce
  • Apply machine learning to massive data sets with Amazon ML, SageMaker, and deep learning
  • Analyze big data with Kinesis Analytics, Amazon Elasticsearch Service, Redshift, RDS, and Aurora
  • Visualize big data in the cloud using AWS QuickSight
Course Content

Introduction

Domain 1: Collections

  • Collection Section Introduction  
  • Kenesis Data Streams Overview
  • Kenesis Producers
  • Kinesis Consumers
  • Kinesis Enhanced Fan Out
  • Kinesis Scaling
  • Kinesis Security
  • Kinesis Data Firehouse
  • SQS Overview
  • Kinesis Data Streams vs SQS
  • IoT Overview
  • IoT Components Deep Dive
  • Database Migration Service (DMS)
  • Direct Connect
  • Snowball
  • MSK: Managed Streaming for Apache Kafka

Domain 2: Storage

  • S3 Overview
  • S3 Storage Tiers
  • S3 Lifecycle Rules
  • S3 Versioning
  • S3 Cross Region Replication
  • S3 ETags
  • S3 Performance
  • S3 Encrytion
  • S3 Security
  • Glacier & Vault Lock Policies
  • S3 & Glacier Select
  • DynamoDB Overview
  • DynamoDB RCU & WCU
  • DynamoDB Partitions
  • DynamoDB APIs
  • DynamoDB Indexes: LSI & GSI
  • DynamoDB DAX
  • DynamoDB Streams
  • DynamoDB TTL
  • DynamoDB Security
  • DynamoDB: Storing Large Objects
  • ElastiCache Overview

Domain 3: Processing

  • Introduction: Processing
  • What is AWS Lambda?
  • Lambda Integration
  • Lambda Costs, Promises, and Anti-Patterns
  • What is Glue? + Partitioning your Data Lake
  • Glue, Hive, and ETL
  • Glue ETL: Developer Endpoints, Running ETL Jobs with Bookmarks
  • Glue Costs and Anti-Patterns
  • Elastic MapReduce (EMR) Architecture and Usage
  • EMR, AWS integration, and Storage
  • EMR Promises; Intro to Hadoop
  • Intro to Apache Spark
  • Spark Integration with Kinesis and Redshift
  • Hive on EMR
  • Pig on EMR
  • HBase on EMR
  • Presto on EMR
  • Zeppelin and EMR Notebooks
  • Hue, Splunk, and Flume
  • S3DistCP and Other Services
  • EMR Security and Instance Types
  • AWS Data Pipeline
  • AWS Step Functions

Domain 4: Analysis

  • Introduction: Analysis
  • Intro to Kinesis Analytics
  • Kinesis Analytics Costs; RANDOM_CUT_FOREST
  • Intro to Elasticsearch
  • Amazon Elasticsearch Service
  • Intro to Athena
  • Intro to Athena
  • Redshift Intro and Architecture
  • Redshift Intro and Architecture
  • Redshift Intro and Architecture
  • Redshift Distribution Styles
  • Redshift Sort Keys
  • Redshift Data Flows and the COPY command
  • Redshift Integration / WLM / Vacuum / Anti-Patterns
  • Redshift Resizing (elastic vs. classic) and new Redshift features in 2020
  • Amazon Relational Database Service (RDS) and Aurora

Domain 5: Visualization

  • Section Introduction: Visualization
  • Intro to Amazon Quicksight
  • Quicksight Pricing and Dashboards; ML Insights
  • Choosing Visualization Types
  • Other Visualization Tools (HighCharts, D3, etc)

Domain 6: Security

  • Encryption 101
  • KMS Overview
  • Cloud HSM Overview
  • AWS Services Security Deep Dive
  • STS and Cross Account Access
  • Identity Federation
  • Policies - Advanced
  • CloudTrail
  • VPC Endpoints

Everything Else

  • AWS Services Integrations
  • Instance Types for Big Data
  • EC2 for Big Data

Preparing for the Exam

About the Certification

Format
Multiple choice, multiple answer

Type
Specialty

Delivery Method
Testing center or online proctored exam

Time
180 minutes to complete the exam

Cost
300 USD (Practice exam: 40 USD)

Language
Available in English, Japanese, Korean, and Simplified Chinese

  • AWS Certified Data Analytics Specialty

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