This article needs additional citations for verification. (August 2013) (Learn how and when to remove this template message)
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.
Cloud analytics tools
AWS Analytics products:
Amazon Athena easily run interactive queries directly against data in Amazon S3.
Amazon EMR deploy popular open source, big data frameworks like Apache Hadoop, Spark, Presto, HBase, and Flink.
Google Cloud Analytics Products:
Google BigQuery Google's fully managed, low cost analytics data warehouse.
Google Cloud Dataflow unified programming model and a managed service for executing a wide range of data processing patterns including streaming analytics, ETL, and batch computation.
Google Cloud Dataproc managed Spark and Hadoop service, to easily process big datasets using the powerful and open tools in the Apache big data ecosystem.
Google Cloud Composer fully managed workflow orchestration service that empowers you to author, schedule, and monitor pipelines that span across clouds and on-premises data centers.
Google Cloud Datalab interactive notebook (based on Jupyter) to explore, collaborate, analyze and visualize data. Google Data Studio turns data into dashboards and reports that are easy to read, share, and customize.
Google Cloud Dataprep intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis.
Related Azure services and Microsoft products:
HDInsight provision cloud Hadoop, Spark, R Server, HBase, and Storm clusters.
Data Lake Analytics distributed analytics service that makes big data easy.