AWS Certified Big Data Specialty Online Course
AWS Certified Big Data Specialty Online Course
The AWS Certified Big Data Specialty exam is one of the most challenging certification exams you can take from AWS. Achieving this certification validates your knowledge of big data systems. But even experienced technologists need to prepare thoroughly for this exam. This course sets you up for success by taking you through all the big data technologies covered in the exam and explaining how they fit together.
The world of big data on AWS includes a dizzying array of technologies and services. This course covers the following topics in-depth:
- Streaming massive data with AWS Kinesis
- Queuing messages with Simple Queue Service (SQS)
- Wrangling 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
- 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 large-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
Big data is an advanced certification, and it's best suited for anyone who has already obtained associate-level certification in AWS and has some data analytics experience.
What's Inside?
- 18 hours Learning videos with for all Course Objectives (100% Course Covered)
- Scenarios based Lab-Exercises
- Latest Updated content
- Unlimited Lifetime access
Course Structure
The AWS Certified Big Data Specialty Online Course covers the following topics -
Introduction
- Course Overview
- Introducing our Hands-On Case Study: Cadabra.com
- Cost of the Course + AWS Budget Setup
Domain 1: Collection
- Collection Section Introduction
- 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] Kinesis Data Streams
- SQS Overview
- Kinesis Data Streams vs SQS
- IoT Overview
- IoT Components Deep Dive
- Database Migration Service (DMS)
- Direct Connect
- Snowball
Domain 2: Storage
- S3 Overview
- S3 Storage Tiers
- S3 Lifecycle Rules
- S3 Versioning
- S3 Cross Region Replication
- S3 ETags
- S3 Performance
- S3 Encryption
- S3 Security
- Glacier & Vault Lock Policies
- DynamoDB Overview
- DynamoDB RCU & WCU
- DynamoDB Partitions
- DynamoDB APIs
- DynamoDB Indexes: LSI & GSI
- DynamoDB DAX
- DynamoDB Streams
- DynamoDB TTL
- DynamoDB Security
- [Exercise] DynamoDB
- ElastiCache Overview
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
- 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
- [Exercise] Elastic MapReduce, Part 1
- [Exercise] Elastic MapReduce, Part 2
- Machine Learning 101
- Classification Models
- Amazon ML Service
- SageMaker
- [Exercise] Amazon Machine Learning, Part 1
- [Exercise] Amazon Machine Learning, Part 2
- Deep Learning 101
- AWS Data Pipeline
Domain 4: Analysis
- Section Introduction: Analysis
- Intro to Kinesis Analytics
- Kinesis Analytics Costs; RANDOM_CUT_FOREST
- [Exercise] Kinesis Analytics, Part 1
- [Exercise] Kinesis Analytics, Part 2
- Intro to Elasticsearch
- Amazon Elasticsearch Service
- [Exercise] Amazon Elasticsearch Service, Part 1
- [Exercise] Amazon Elasticsearch Service, Part 2
- [Exercise] Amazon Elasticsearch Service, Part 3
- Intro to Athena
- Athena and Glue, Costs, and Security
- [Exercise] AWS Glue and Athena
- Redshift Intro and Architecture
- Redshift Spectrum and Performance Tuning
- Redshift Durability and Scaling
- Redshift Distribution Styles
- Redshift Sort Keys
- Redshift Data Flows
- Redshift Integration / WLM / Vacuum / Anti-Patterns
- [Exercise] Redshift Spectrum, Pt. 1
- [Exercise] Redshift Spectrum, Pt. 2
- Amazon Relational Database Service (RDS) and Aurora
Domain 5: Visualization
- Section Introduction: Visualization
- Intro to Amazon Quicksight
- Quicksight Pricing and Dashboards
- Choosing Visualization Types
- [Exercise] Amazon Quicksight
- Other Visualization Tools (HighCharts, D3, etc)
Domain 6: Security
- Encryption 101
- S3 Encryption (Reminder)
- KMS Overview
- Cloud HSM Overview
- AWS Services Security Deep Dive (1/3)
- AWS Services Security Deep Dive (2/3)
- AWS Services Security Deep Dive (3/3)
- 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
