Introduction
Scalable data solutions on AWS
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What you should know
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Use AWS Cloud services
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1. AWS Data Services Overview
Use Amazon Web Services (AWS) data services
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Why use AWS data storage services?
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Explore file and HDFS storage
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Explore AWS data storage
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Understand why AWS Cloud tools matter
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2. Storage and Files with S3 and More
Explore the core file storage choices
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Explore AWS S3
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Explore AWS S3 using AWS CLI
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Explore AWS Glacier storage
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Explore AWS EBS and EFS
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Understand file import dervices for AWS and compare file services
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Scenario: Use cloud file storage
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3. SQL Databases with RDS
Explore AWS RDS for managed RDBMS
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Explore AWS RDS MySQL
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Explore AWS RDS Aurora Serverless
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Use RDS query editor
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Scenario: Move on-premises relational data to AWS
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4. NoSQL Databases with DynamoDB and More
Explore NoSQL options in AWS
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Understand AWS ElastiCache
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Explore AWS DynamoDB
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Use AWS CLI with AWS DynamoDB
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Explore AWS DocumentDB
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Scenario: Work with caching and real-time data
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5. Data Warehouse and Pipelines with Redshift
Explore the AWS data warehouse options and Redshift
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Work with AWS Redshift
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Connect to AWS Redshift with AWS query editor
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Visualize data with AWS QuickSight
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Scenario: Build a data warehouse in the cloud
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6. Graph Databases and Ledgers with Neptune DB or QLDB
Explore AWS specialty databases including graph and ledger
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Explore graphs with AWS Neptune
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Explore ledgers with AWS QLDB
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Explore event databases including Amazon Timestream
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7. Hadoop and Spark with EMR
Explore Hadoop and Spark on AWS
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Understand Hadoop jobs and libraries
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Explore AWS EMR with Hadoop and Spark
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Run Spark job on a Jupyter Notebook on AWS EMR
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8. Data Lake with AWS Services
Understand a data lake pattern with AWS Lake Formation
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Explore AWS Athena
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Explore AWS Glue Data Catalog and Crawlers
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Use AWS Glue for ETL
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Explore a data lake pattern with AWS Lake Formation
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Scenario: Build for the Internet of Things with Hadoop
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Conclusion
Keep learning AWS services
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Ex_Files_Cloud_Hadoop_Apache_Spark.zip
(2.0 MB)