aws data analytics

This class was created by Brainscape user Kate McKenzie. Visit their profile to learn more about the creator.

Decks in this class (5)

Collection: 18% (Kinesis Streams/Firehose, MSK, SQS, Data Pipeline, Snow, DMS, IoT Core)
Be able to: a) determine the operational characteristics of the collection system b) select a collection system that handles the frequency, volume and source of data
94  cards
Storage and Data Management: 22% (Redshift, S3, Lake Formation, Glue Data Catalog, HDFS, EMRFS)
Be able to: a) determine the operational characteristics of a storage solution for analytics b) determine data access and retrieval patterns c) select an appropriate data layout, schema, structure, and format d) define a data lifecycle based on usage patterns and business requirements e) determine an appropriate system for cataloging data and managing metadata
12  cards
Processing: 24% (EMR, Spark, Hive, Lambda, Glue, ECS)
Be able to: a) determine appropriate data processing solution requirements b) design a solution for transforming and preparing data for analysis c) automate and operationalize a data processing solution
3  cards
Analytics and Visualisations: 18% (ElasticSearch, CloudSearch, Athena, Presto, Kinesis Analytics, IoT Analytics, QuickSight)
Be able to: a) determine the operational characteristics of an  analysis and visualization solution b) select the appropriate data analysis solution for a given scenario c) select the appropriate data visualisation solution for a given scenario
6  cards
Security: 18% (KMS, Cognito)
Be able to: a) select appropriate authentication and authorization mechanisms b) apply data protection and encryption techniques c) apply data governance and compliance controls
1  cards

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aws data analytics

  • Class purpose General learning

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