Learn about how to match the speed requirements to the possible methods of ingesting data—batched, interactive, or streaming. Learn about the practicalities of solutions which combine these methods.
- [Instructor] So, now let's pull these concepts together…and start tying them to the services…that Amazon has available.…In terms of deciding which analytics to use,…there are the considerations around batch,…interactive, and stream.…Batch analytics are often used for business situations…where you have data that need to be processed…within minutes or hours.…An example would be daily or weekly…or monthly business reports.…Interactive often is around data…that needs to be processed within seconds.…
An example of this is self-service dashboards.…For stream analytics,…the time requirements are pretty extreme,…often milliseconds or seconds,…and another example of this would be fraud alerts.…The Amazon Services for interactive…and batch analytics include the following.…The first is Amazon Athena.…This allows you to do sequel queries…on top of files that are stored in blob storage,…which is called S3.…Amazon called this serverless interactive queries,…and we'll see this in action in this course.…
Additionally, we have Amazon Redshift and 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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