Data Analytics   AWS

AWS Data Analytics Solutions

 · 1 min read

AWS Data Analytics Solutions

Type of Analysis

Descriptive analysis (or data mining)

  • Determine what generated the data
  • Highest effort

Diagnostic analysis

  • Determine why data was generated
  • Understand root causes of events

Predictive analysis

  • Determine future outcomes
  • Uses descriptive and diagnostic to predict future trends

Prescriptive analysis

  • Determine action to take
  • Uses other three to predict and can be automated

Analytics Processing Methods

Identify analytics processing method based on data type collected and analysis type used

Batch analytics

  • Large volumes of raw data
  • Analytics process on a schedule, reports
  • Map-reduce type services: EMR

Interactive analytics

  • Complex queries on complex data at high speed
  • See query results immediately
  • Athena, Elasticsearch, Redshift

Streaming analytics

  • Analysis of data that has short shelf-life
  • Incrementally ingest data and update metrics
  • Kinesis

Analytics Solutions Patterns

Select the best option for a scenario based on the type of analytics and processing required

Analytics Solutions Patterns - EMR

Uses the map-reduce technique to reduce large processing problems into small jobs distributed across many nodes in a Hadoop cluster

  • On-Demand big data analyitcs
  • Event-driven ETL
  • Machine Learning predictive analytics
  • Clickstream analysis
  • Load data warehousees

Do not use for transactional processing or with small data sets

Analytics Solutions Patterns - Kinesis

Streams data to analytics processing solutions

  • Video analytics applications
  • Real-time analytics applications
  • Analyze IoT device data
  • Blog posts and article analytics
  • System and application log analytics

Do not use for small-scale throughput or with data with longer shelf-life

Analytics Solutions Patterns - Redshift

OLAP using BI tools

  • Near real-time analysis of millions of rows of manufacturing data generated by continous manufacturing equipment
  • Analyze events from mobile app to gain insight into how users use the application
  • Gain value and insights from large, complex, and dispersed datasets
  • Make live data generated by range of next-gen security solutions available to large numbers of organizations for analysis

Do not use for OLTP or with small data sets