Learn the differences betwen key AWS analytic tool types. Review a summary of detailed service differences, such as storage locations and compression types which factor into design decisions.
- It's interesting to see how Amazon is representing…their services around the data analytics architecture.…You can see that what they've shown here is that…there's three different layers in analytics.…The first is storage, then serverless compute,…then data processing.…And the primary location or service for storage…is not a database anymore, that's why I started…this course with S3 and Athena, it's a datalike.…Why? It's cheaper.…It's simpler to set up.…
S3 itself is serverless and now…we have Athena, which is serverless.…Working with serverless services allows you to be…much more flexible and it reduces costs.…The industry is moving there fast.…So in addition to S3, another serverless offering…is the AWS Glue Data Catalog, which is a centralized…storage location for the metadata for the files in S3.…In the next layer, we have serverless compute.…
We have the Kinesis Firehose,…we have serverless ETL with AWS Glue,…we have the very new serverless data warehouse queries…for archival data with Redshift Spectrum,…
- Explain the difference between files and databases.
- Identify examples of batching, micro-batching, and streaming.
- Prepare helpful data visualizations with QuickSight.
- Recognize the different types of analytics available in AWS.
- Demonstrate how to set up AWS CLI.
- Describe common analytics architecture patterns.
Skill Level Intermediate
Amazon Web Services for Data Sciencewith Lynn Langit3h 56m Intermediate
1. Analytics on AWS
2. Analytic Services
3. AWS Code Tools for Analytics
4. Advanced Analytics
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