Cloud analytics is a marketing term for businesses to carry out analysis using cloud computing. It uses a range of analytical tools and techniques to help companies extract information from massive data and present it in a way that is easily categorised and readily available via a web browser.[1]

Cloud analytics is term for a set of technological and analytical tools and techniques specifically designed to help clients extract information from massive data.[2]

Cloud analytics is designed to make official statistical data readily categorized and available via the users web browser.

Cloud analytics tools

AWS Analytics products:

  • Amazon Athena runs interactive queries directly against data in Amazon S3.[3]
  • Amazon EMR deploys open source, big data frameworks like Apache Hadoop, Spark, Presto, HBase, and Flink.
  • Amazon Redshift fully manages petabyte-scale data warehouse to run complex queries on collections of structured data.[4]

Google Cloud Analytics Products:

  • Google BigQuery Google's fully manages low cost analytics data warehouse.
  • Google Cloud Dataflow unifies programming models and manages services for executing a range of data processing patterns including streaming analytics, ETL, and batch computation.
  • Google Cloud Dataproc manages Spark and Hadoop service, to process big datasets using the open tools in the Apache big data ecosystem.
  • Google Cloud Composer fully manages workflow orchestration service to author, schedule, and monitor pipelines that span across clouds and on-premises data centers.
  • Google Cloud Datalab is an interactive notebook (based on Jupyter) to explore, collaborate, analyze and visualize data.
  • Google Data Studio turns data into dashboards and reports that can be read, shared, and customized.
  • Google Cloud Dataprep is a data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis.
  • Google Cloud Pub/Sub is a serverless, large-scale, real-time messaging service that allows you to send and receive messages between independent applications.[5]

Related Azure services and Microsoft products:

  • HDInsight provisions cloud Hadoop, Spark, R Server, HBase, and Storm clusters.
  • Data Lake Analytics distributes analytics service that makes big data easy.
  • Machine Learning Studio easily builds, deploys, and manages predictive analytics solutions.[6]

References

  1. ↑ What is Cloud Analytics?
  2. ↑ "Cloud Analytics | Booz Allen Hamilton". Archived from the original on 2014-08-12. Retrieved 2014-07-30.
  3. ↑ Spira, Elliott (19 August 2019). "Query your CloudTrail like a pro with Athena". GorillaStack.
  4. ↑ "Data Lakes and Analytics on AWS - Amazon Web Services".
  5. ↑ "Data Analytics Solutions".
  6. ↑ "Cloud-Scale Analytics | Microsoft Azure".
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