AWS Data Analytics Services

What are AWS Data Analytics Services?
Types of Amazon AWS Analytics Services / Tools
AWS Analytics Portfolio
Data collection / Ingestion 
Data Storage 
Process / Analyse
Visualize / Report

Managed analytics services empowers organizations to automate the process of turning data into meaningful presentation and insight to facilitate business goals achievement such as customer behaviour analysis using predictive modelling and 360 customer views to understand customer expectations and service improvements. Analytical tools help to remove silos of data across enterprise level and leverage all data sets for compliance, audit, security, mapping business objectives to IT to improvise reporting analytics. 

In this article we will learn more about one such analytical tool AWS services, its advantages, use cases and so on. 

What are AWS Data Analytics Services?

Today’s customers require better, faster and more relevant insights and meaningful representation of data to stay ahead in competition. But usage of data effectively demands a data architecture , where data can be effectively collected, categorized, and transformed into a meaningful purpose it will serve.

Data could reside in structured or unstructured format. More that 70% of data within organizations is in unstructured format such as emails, data residing in files and folders spread all across. Amazon provides a wide range of managed AWS data Analytics services along with a strong APN partner community which can help to build a scalable, secure, and cost-effective data repository. 

Types of Amazon AWS Data Analytics Services / Tools

AWS provides various types of analytics services as explained below:

  • Interactive Analytics – Using Amazon Athena knowledge research happens instantly, gets leads to seconds and pays just for the queries you run.
  • Big data processing – perform analytics on large volume of data using tools like EMR 
  • Data Warehousingrun and power complicated queries against big structured data using tools like Redshift
  • Real time data analysis – Analyse streaming knowledge like IoT measuring knowledge, application logs and website click streams. 
  • Operational Analytics  – Such as log analysis, click stream analysis using tools like ElasticSearch
  • Dashboards and Visualizations – to present data in a meaningful manner using tools like Quick sight.

AWS Analytics Portfolio

Data collection / Ingestion 

  • Amazon Kinesis – Amazon Kinesis is a feature of Amazon Web Services (AWS) that easily gathers or collects, processes, and analyses video and data streams in a real-time environment. It has four components namely – Video Stream, data stream, data fire hose and data analytics. Amazon Kinesis Data Analytics is a new ML introduced to detect “hotspots” in the streaming data. A real time processing engine to write and execute SQL queries to have meaningful information from the data and you only pay for processing of resources that your streaming application is using. 
  • AWS Import/Export – AWS Import/Export service accelerates transfer of large amounts of data into and out of AWS using physical storage appliances, bypassing the Internet. Data is copied to a device (At source) and shipped via standard shipping mechanisms, and finally copied to (Destination).
  • AWS direct connect – AWS Direct Connect links internal networks to an AWS direct Connect location over a standard Ethernet fibre-optic cable to achieve highly resilient network connections between Amazon Virtual Private Cloud (Amazon VPC) and their on-premises infrastructure.
  • AWS SQS – Amazon SQS is a web service which gives access to message queues that store messages waiting to be processed making applications more flexible and reliable.

Data Storage 

  • Amazon S3 – easy to use and cheap storage service and can be used by S3 to store any amount of data for a wide range of use cases such as web hosting, data archival , software delivery and so on.
  • Amazon DynamoDB – DynamoDB is a hosted NoSQL database offered by Amazon Web Services (AWS), reliable performance with scalability and managed experience.
  • Amazon Glacier – is a data archiving solution.
  • Amazon RDS – Relational Database Service which performs all these tasks (i.e., setup, operate, update) automatically

Process / Analyse 

  • Amazon EMR or Elastic MapReduce is based on Hadoop/HDFS clusters, it is easy to use and fully managed, tightly integrated with S3 
  • Amazon RedShift – is a columnar data warehouse, which is ANSI SQL compatible , fully managed and cost effective 
  • Amazon EC2 – is a web service that enables to launch and manage Linux /Unix and Windows server instances in Amazon data centres
  • AWS data pipeline – is a web service to automate the movement and transformation of data

Visualize / Report

The services/tools used to visualize or report are: Tableau, SAS, Informatica, MicroStrategy, SAP, Jaspersoft etc.

Interesting facts ! 

33.8 percent global market share worldwide 

50% less expensive than other cloud data warehouses.

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