by Frank Kane | Released May 2019 | ISBN: 9781838983383

Prepare for the AWS DAS-C01 exam with the help of quizzes, exercises, and practice examsAbout This VideoPrepare for the AWS DAS-C01 exam with the help of quizzes, exercises, and practice examsApply machine learning to massive data sets with Amazon ML, SageMaker, and deep learningFind tips and techniques to analyze, visualize, and process big dataIn DetailThe AWS Certified Data Analytics - Specialty exam (AWS DAS-C01) is one of the most challenging certification exams by Amazon. Passing the exam will validate your knowledge of big data systems and even experienced technologists need to prepare extensively for this exam. This course sets you up for success by providing an overview of all the big data technologies and how they fit together.The course starts by highlighting the learning objectives. Moving forward, you will learn to stream and store data with Amazon Kinesis and simple storage service (S3), respectively. You will understand how to process big data with AWS Lambda and Apache Spark. Next, you will focus on how to analyze streaming data in real time with Amazon Kinesis analytics and visualize the data interactively with QuickSight. You will also grasp encryption techniques to secure your data and explore useful tips to pass the exam with confidence.By the end of this course, you will be well-versed with the essential concepts and major domains necessary for passing the AWS DAS-C01 exam. Show and hide more Publisher resources Download Example Code

1. Chapter 1 : Introduction
   • Course Overview
   • Introducing Hands-On Case Study: Cadabra.com
   • Cost of the Course and Amazon Web Services (AWS) Budget Setup
2. Chapter 2 : Domain 1: Collection
   • Collection Section Introduction
   • Amazon Kinesis Data Streams Overview
   • Kinesis Producers
   • Kinesis Consumers
   • Kinesis Enhanced Fan Out
   • Kinesis Scaling
   • Kinesis Security
   • Kinesis Data Firehose
   • [Exercise] Kinesis Firehose - Part 1
   • [Exercise] Kinesis Firehose - Part 2
   • [Exercise] Kinesis Firehose - Part 3
   • [Exercise] Amazon Kinesis Data Streams
   • Amazon Simple Queue Service (Amazon SQS) Overview
   • Kinesis Data Streams vs Amazon Simple Queue Service Amazon SQS
   • Internet of Things (IoT) Overview
   • Internet of Things (IoT) Components Deep Dive
   • Amazon Web Services (AWS) Database Migration Service (DMS)
   • Amazon Web Services (AWS) Direct Connect
   • Amazon Web Services (AWS) Snowball
   • Amazon MSK: Managed Streaming for Apache Kafka
3. Chapter 3 : Domain 2: Storage
   • Amazon Simple Storage Service (Amazon S3) Overview
   • Amazon Simple Storage Service (Amazon S3) Storage Classes
   • Amazon Simple Storage Service (Amazon S3) Lifecycle Rules
   • Amazon Simple Storage Service (Amazon S3) Versioning
   • Amazon Simple Storage Service (Amazon S3) Cross Region Replication
   • Amazon Simple Storage Service (Amazon S3) ETags
   • Amazon Simple Storage Service (Amazon S3) Performance
   • Amazon Simple Storage Service (Amazon S3) Encryption
   • Amazon Simple Storage Service (Amazon S3) Security
   • Amazon Simple Storage Service (Amazon S3) Glacier and Vault Lock Policies
   • Amazon Simple Storage Service (Amazon S3) and Glacier Select
   • Amazon DynamoDB Overview
   • Amazon DynamoDB Provisioned Throughput
   • Amazon DynamoDB Partitions
   • Amazon DynamoDB APIs
   • Amazon DynamoDB Indexes: Local Secondary Index (LSI) and Global Secondary Index (GSI)
   • Amazon DynamoDB Accelerator (DAX)
   • Amazon DynamoDB Streams
   • Amazon DynamoDB Time to Live (TTL)
   • Amazon DynamoDB Security
   • Amazon DynamoDB - Storing Large Objects
   • [Exercise] Amazon DynamoDB
   • Amazon ElastiCache Overview
4. Chapter 4 : Domain 3: Processing
   • Section Introduction: Processing
   • What is AWS Lambda?
   • Lambda Integration - Part 1
   • Lambda Integration - Part 2
   • Lambda Costs, Promises, and Anti-Patterns
   • [Exercise] AWS Lambda
   • What is Glue? + Partitioning your Data Lake
   • Glue, Hive, and Extract, Transform, and Load (ETL)
   • Glue ETL: Developer Endpoints, Running ETL Jobs with Bookmarks
   • Glue Costs and Anti-Patterns
   • Amazon Elastic MapReduce (EMR) Architecture and Usage
   • Amazon Elastic MapReduce (EMR), Amazon Web Services (AWS) Integration, and Storage
   • Amazon Elastic MapReduce (EMR) Promises and Intro to Hadoop
   • Introduction to Apache Spark
   • Spark Integration with Kinesis and Redshift
   • Hive on Amazon Elastic MapReduce (EMR)
   • Apache Pig on Amazon Elastic MapReduce (EMR)
   • Apache HBase on Amazon Elastic MapReduce (EMR)
   • Presto on Amazon Elastic MapReduce (EMR)
   • Apache Zeppelin and Amazon Elastic MapReduce (EMR) Notebooks
   • Hue, Splunk, and Flume
   • S3DistCp and Other Services
   • Amazon Elastic MapReduce (EMR) Security and Instance Types
   • [Exercise] Elastic MapReduce - Part 1
   • [Exercise] Elastic MapReduce - Part 2
   • Amazon Web Services (AWS) Data Pipeline
   • Amazon Web Services (AWS) Step Functions
5. Chapter 5 : Domain 4: Analysis
   • Section Introduction: Analysis
   • Introduction to Kinesis Analytics
   • Kinesis Analytics Costs and RANDOM_CUT_FOREST
   • [Exercise] Kinesis Analytics - Part 1
   • [Exercise] Kinesis Analytics - Part 2
   • Introduction to Amazon Elasticsearch
   • Amazon Elasticsearch Service
   • [Exercise] Amazon Elasticsearch Service - Part 1
   • [Exercise] Amazon Elasticsearch Service - Part 2
   • [Exercise] Amazon Elasticsearch Service - Part 3
   • Introduction to Amazon Athena
   • Athena and Glue, Costs, and Security
   • [Exercise] Amazon Web Services (AWS) Glue and Athena
   • Amazon Redshift Intro and Architecture
   • Redshift Spectrum and Performance Tuning
   • Amazon Redshift Durability and Scaling
   • Amazon Redshift Distribution Styles
   • Amazon Redshift Sort Keys
   • Amazon Redshift Data Flows and the COPY command
   • Amazon Redshift Integration/Workload Management (WLM)/Vacuum/Anti-Patterns
   • Amazon Redshift Resizing (Elastic vs. Classic) and new Redshift features in 2020
   • [Exercise] Redshift Spectrum - Part 1
   • [Exercise] Redshift Spectrum - Part 2
   • Amazon Relational Database Service (RDS) and Aurora
6. Chapter 6 : Domain 5: Visualization
   • Section Introduction: Visualization
   • Introduction to Amazon QuickSight
   • Amazon QuickSight Pricing and Dashboards
   • Choosing Visualization Types
   • [Exercise] Amazon QuickSight
   • Other Visualization Tools (HighCharts, D3, and so on)
7. Chapter 7 : Domain 6: Security
   • Encryption 101
   • S3 Encryption (Reminder)
   • Amazon Web Services Key Management Service (AWS KMS) Overview
   • Amazon Web Services (AWS) CloudHSM Overview
   • Amazon Web Services AWS Security Features Deep Dive - Part 1
   • Amazon Web Services AWS Security Features Deep Dive - Part 2
   • Amazon Web Services AWS Security Features Deep Dive - Part 3
   • Amazon Web Services Security Token Service (AWS STS) and Cross-Account Access
   • Identity Federation
   • Policies - Advanced
   • Amazon Web Services (AWS) CloudTrail
   • Virtual Private Cloud (VPC) Endpoints
8. Chapter 8 : Everything Else
   • Amazon Web Services (AWS) Service Integrations
   • Instance Types for Big Data
   • Amazon Elastic Compute Cloud (Amazon EC2) for Big Data
9. Chapter 9 : Preparing for the Exam
   • Exam Tips
   • State of Learning Checkpoint
10. Chapter 10 : Appendix - Machine Learning Topics for the Amazon Web Services (AWS) Certified Big Data Exam
    • Machine Learning 101
    • Classification Models
    • Amazon Machine Learning Service
    • Amazon SageMaker
    • Deep Learning 101
    • [Exercise] Amazon Machine Learning - Part 1
    • [Exercise] Amazon Machine Learning - Part 2
11. Chapter 11 : Wrapping Up
    • Congratulations! Now make sure you're ready
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