AWS Certified Data Analytics Specialty (2023) Hands-on [Video]
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Free ChapterIntroduction
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Domain 1: Collection
- Collection Section Introduction
- Kinesis Data Streams Overview
- Kinesis Producers
- Kinesis Consumers
- Kinesis Data Streams - Hands On
- Kinesis Enhanced Fan Out
- Kinesis Scaling
- Kinesis - Handling Duplicate Records
- Kinesis Security
- Kinesis Data Firehose
- CloudWatch Subscription Filters with Kinesis
- (Exercise) Kinesis Firehose, Part 1
- (Exercise) Kinesis Firehose, Part 2
- (Exercise) Kinesis Firehose, Part 3
- (Exercise) Kinesis Data Streams
- SQS Overview
- Kinesis Data Streams Versus SQS
- Database Migration Service (DMS)
- Direct Connect
- Snow Family
- MSK: Managed Streaming for Apache Kafka
- MSK Connect
- MSK Serverless
- Kinesis vs MSK
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Domain 2: Storage
- S3 Overview
- S3 Hands-On
- S3 Security: Bucket Policy
- S3 Security: Bucket Policy Hands-On
- S3 Versioning
- S3 Versioning - Hands On
- S3 Replication
- S3 Replication Notes
- S3 Replication – Hands-On
- S3 Storage Classes Overview
- S3 Storage Classes Hands-On
- S3 Lifecycle Rules (with S3 Analytics)
- S3 Lifecycle Rules – Hands-On
- S3 Event Notifications
- S3 Event Notifications – Hands-On
- S3 Performance
- S3 Select and Glacier Select
- S3 Encryption
- S3 Encryption – Hands-On
- S3 Default Encryption
- S3 Access Points
- S3 Object Lambda
- DynamoDB Overview
- DynamoDB Basics - Hands-On
- DynamoDB in Big Data
- DynamoDB RCU and WCU - Throughput
- DynamoDB RCU and WCU – Hands-On
- DynamoDB Basic APIs
- DynamoDB Basic APIs – Hands-On
- DynamoDB Indexes (GSI + LSI)
- DynamoDB Indexes (GSI + LSI) – Hands-On
- DynamoDB PartiQL
- DynamoDB DAX
- DynamoDB DAX - Hands-On
- DynamoDB Streams
- DynamoDB Streams – Hands-On
- DynamoDB TTL
- DynamoDB Patterns with S3
- DynamoDB Security
- (Exercise) DynamoDB
- ElastiCache Overview
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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 ETL
- Modifying the Glue Data Catalog from ETL Scripts
- Glue ETL: Developer Endpoints, Running ETL Jobs with Bookmarks
- Glue Costs and Anti-Patterns
- AWS Glue Studio
- AWS Glue Data Quality
- AWS Glue DataBrew
- AWS Lake Formation
- AWS Lake Security
- Elastic MapReduce (EMR) Architecture and Usage
- EMR, AWS integration, and Storage
- EMR Promises; Introduction to Hadoop
- EMR Serverless, EMR, and EKS
- Introduction to Apache Spark
- Spark Integration with Kinesis and Redshift
- Spark integration with Athena
- 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
- (Exercise) Elastic MapReduce, Part 1
- (Exercise) Elastic MapReduce, Part 2
- AWS Data Pipeline
- AWS Step Functions
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Domain 4: Analysis
- Section Introduction: Analysis
- Introduction to Kinesis Analytics
- Kinesis Analytics Costs; RANDOM_CUT_FOREST
- (Exercise) Kinesis Analytics, Part 1
- (Exercise) Kinesis Analytics, Part 2
- (Exercise) Kinesis Analytics, Part 3
- (Exercise) Kinesis Analytics, Part 4
- Introduction to OpenSearch (formerly Elasticsearch)
- Amazon OpenSearch Service
- OpenSearch Index Management and Designing for Stability
- Amazon OpenSearch Service Performance
- Amazon OpenSearch Serverless
- (Exercise) Amazon OpenSearch Service
- Introduction to Athena
- Athena and Glue, Costs, and Security
- Athena Performance
- Athena ACID Transactions
- (Exercise) AWS Glue and Athena
- Redshift Introduction and Architecture
- Redshift Spectrum and Performance Tuning
- Redshift Durability and Scaling
- Redshift Distribution Styles
- Redshift Sort Keys
- Redshift Data Flows and the COPY command
- Redshift Integration / WLM / Vacuum / Anti-Patterns
- Redshift Resizing (Elastic Versus Classic) and New Redshift Features in 2020
- Newer Redshift Features, AQUA
- Redshift Security Concerns
- Redshift Serverless
- (Exercise) Redshift Spectrum, Part 1
- (Exercise) Redshift Spectrum, Part 2
- Amazon Relational Database Service (RDS) and Aurora
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Domain 5: Visualization
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Domain 6: Security
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Everything Else
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Preparing for the Exam
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Appendix - Machine Learning Topics for the Legacy AWS Certified Big Data Exam
-
Wrapping Up
About this
video
In this course, you will learn 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, Glue ETL, Glue DataBrew, Glue Studio, and Lake Formation; processing data at an unlimited scale with Elastic MapReduce; 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 OpenSearch (formerly 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; and finally, keeping your data secure with encryption, KMS, HSM, IAM, Cognito, STS, and more.
By the end of this course, you will be well-versed in the essential concepts and major domains necessary to pass the AWS DAS-C01 exam.
- Publication date:
- May 2019
- Publisher
- Packt
- Duration
- 16 hours 33 minutes
- ISBN
- 9781838983383
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