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AWS Academy Data Analytics
AWS Academy Data Analytics is a foundational course for AWS Academy participants who plan to pursue careers in data analytics. The course helps learners develop skills with AWS services that are critical for conducting analysis of big data problems. The course consists of a series of labs that you can integrate with your existing courses on data mining, data analysis, or data science.
Lab. 1. Store Data in Amazon Simple Storage Service (Amazon S3)
In this lab you will practice using the AWS management console to create an Amazon S3 bucket, add an IAM user to a group that has full access to the Amazon S3 service, upload files to Amazon S3, and run simple queries on the data in Amazon S3.
Lab. 2. Query Data in Amazon Athena
In this lab, you will practice using the AWS Management Console to create an Athena application, define a database in Athena, create a table, define columns and data types, and run both simple and complex queries.
Lab. 3. Query Data in Amazon S3 with Amazon Athena and AWS Glue
In this lab, you will work with AWS Glue. You can direct AWS Glue to a data source, and it can infer a schema based on the data types that it discovers. AWS Glue builds a catalog that contains metadata about the various data sources.
Lab. 4. Analyze Data with Amazon Redshift
In this activity, you will practice using the AWS Management Console to create an Amazon Redshift cluster, load data from Amazon Simple Storage Service (Amazon S3) into an Amazon Redshift table, and query data in Amazon Redshift.
Lab.5.Analyze Data with Amazon Sagemaker
In this lab, you will create a Jupyter notebook in Amazon SageMaker based on data that is stored in Amazon Simple Storage Service (Amazon S3). Then, you will use the open source tool Bokeh to develop visualizations of your analysis.
Lab. 7. Analyze Streaming Data with Amazon Kinesis Firehose, Amazon Elasticsearch and Kibana
In this activity, you will practice using the AWS Management Console to create a Kinesis Data Firehose delivery stream. You will also integrate a Kinesis Data Firehose delivery stream with Amazon Elasticsearch and build visualizations with open source visualization tool Kibana.
補充
Business Intelligence with QuickSight
BI vs Redshift
1.S3_upload object to Bucket
2.Redshift_Create Cluster
3.Redshift_Create table
4.Redshift_import data from S3
5.Power BI connection with Redshift
5.Quicksight Connection with Redshift
6.Pause or Delete Redshift
範例及說明文件