AWS QuickSight

AWS QuickSight is the BI (business intelligence) tool from AWS that enables creating attractive visualizations and perform ad-hoc data analysis on business data with the added advantage of high speed and scalability. Created by the leading cloud provider, it fills the void of a business analytics tool, which is an important part of a data analytics ecosystem. AWS QuickSight is the perfect answer to fthe BI needs of Amazon’s massive customer base, which already stores massive amounts of data in various AWS services like Athena, Redshift, RDS, S3 and others. QuickSight also offers an app for iOS and Android devices.

SPICE

SPICE is AWS’s “Super-fast, Parallel, In-memory Calculation Engine,” built from scratch. QuickSight leverages SPICE to yield visualizations for large data sets for thousands of users in a matter of seconds. SPICE uses a combination of columnar storage, in-memory technology, machine code generation, and data compression to quickly run queries on large datasets. SPICE can ingest data from a variety of data sources such as Amazon Redshift, Amazon RDS, Amazon S3, 3rd party databases running on AWS or on the cloud. You can also optionally use Amazon RDS as the underlying query engine instead of SPICE by using the Direct Query mode.

Pricing

The other attractive feature of QuickSight is its low cost compared to established BI solutions. Amazon QuickSight starts at $9 per user per month and is offered in two service categories, Standard and Enterprise. Both editions provide a full set of features to create and share visualizations, and the enterprise edition provides additional encryption at rest and Active Directory integration to manage QuickSight users and administrators in your organization. Announced in preview mode in October 2015 and now generally available since November 2016, QuickSight is currently accessible in the US East (Northern Virginia), US West (Oregon) and Europe (Ireland) regions.

Tableau vs QuickSight

While QuickSight is perfect for AWS customers that already have their data stores on AWS, it is a not so attractive option for organizations with on-premise data sources today. Its visualizations are offered on the cloud only and lack the ability to embed in external applications. Tableau and Qlik score big in this area with their ready availability of integration with on-premise tools. QuickSight claims extreme ease of use where the user does not need to be an expert in data analytics and visualizations since the tool is capable of inferring data types and relationships between data. While QuickSight makes it incredibly easy for users to get started with creating sophisticated visualizations and dashboards, Tableau and Qlik are very advanced in their depth and scope of visualizations and analysis offered. Both Tableau and Qlik are categorized as leaders in the Gartner’s Magic quadrant for Business Intelligence and Analytics platforms. QuickSight may not pose a threat to Tableau and Qlik’s business due to its limitation to the cloud. Yet, QuickSight is an excellent addition to AWS suite of big data products and opens up enormous possibilities to take advantage of existing data stored in AWS and analyze to enhance business decisions.

AWS Big Data

A classic use case of big data is to capture streaming events from IoT devices, cleanse the data, validate the data, process it to extract features and ultimately apply analysis to extract insights. With the range of services offered under the AWS big data portfolio and the ability of QuickSight to integrate with AWS services like Athena, Redshift, RDS, and S3, IoT analytics becomes easily achievable with QuickSight. A sample architecture is shown in the diagram below.

awsquicksight-2

As depicted, IoT devices are able to connect to AWS IoT securely through the MQTT and HTTPs protocols. The IoT rules engine continuously processes incoming messages and with the help of pre-configured rules, routes the messages to other AWS services. In this case, an IoT rule is configured to capture all the messages and send them to Kinesis Firehose. Firehose is able to write the streaming messages in batches to objects stored in S3 after performing validation and filtering. Further data in S3 can be used to set up a table in Athena as per the business use case. QuickSight can then connect to Athena and create visuals that convey the business story in an effective manner. Thus integrating with AWS Big Data services, QuickSight can be utilized to deliver real-time business analytics in a highly scalable and durable manner.

Getting Started with QuickSight is simple: Log in to AWS and signup for a free trial of QuickSight to check it out.

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