Over a million developers have joined DZone.

Interactive Business Intelligence for Faster Insights

DZone's Guide to

Interactive Business Intelligence for Faster Insights

A high-level introduction to AWS QuickSight for business intelligence needs.

· Big Data Zone ·
Free Resource

Learn how to operationalize machine learning and data science projects to monetize your AI initiatives. Download the Gartner report now.

This blog is the first in a series on AWS QuickSight. AWS QuickSight is a next generation Business Intelligence (BI) application that can help build interactive visualizations on top of various data sources hosted on Amazon cloud infrastructure. QuickSight delivers fast and responsive insights on Big Data, enables organizations to quickly democratize data visualizations and scales to hundreds of users at a fraction of the cost when compared to traditional BI tools.

Getting Started With AWS QuickSight

While enterprises have adopted Software as a Service (SAAS) service like Salesforce, the move for Big Data Analytics (BDA) as a service has been slower. This trend is about to change and Zaloni’s India Development Center (IDC) predicts that by 2020, 50% of business analytics software will incorporate predictive analytics based on cloud platforms. The Amazon Web Services team has been in the forefront of providing real solutions that are designed for massive scale.

QuickSight allows enterprises to get started in minutes. They can now access data from multiple sources, build interactive visuals, get answers quickly and tell a story with data. QuickSight is poised to become the leader in cloud-powered BI on the world’s most scalable cloud infrastructure at a fixed monthly cost per user per month.

Advanced Process Flow

Over the last 20 years, organizations have built and relied on reporting systems for day-to-day operations but have failed to provide true agility to business stakeholders. At a high level, building a BI dashboard involves the following steps:

  • Ingestion framework to collect data from source systems. These systems are typically files and relational databases.
  • Standardize, clean and build facts, dimensions, and aggregates based on key performance indicators requested by the business.
  • Build BI logical data models — typically stars or snowflakes based on various dashboard needs.
  • Build reports and dashboards on the web.
  • Publish and share results with data analysts and business stakeholders.

The above data flow is shown in the figure below and is primarily built by IT with regular consultation with data stewards and dashboard consumers.

Screen Shot 2017-01-25 at 2.03.24 PM.png

Traditional BI Process Flow

Amazon QuickSight was built to address the pain points of traditional BI tools, and provides IT and business teams with a fast, cloud powered BI service at one-tenth the cost of traditional BI software. Here are QuickSight's key features:

  • Empowers data analysts to build their reports quickly by pointing them to any data source without the need of a large IT team that traditionally has to build metadata in a BI tool before data analysts can use them.
  • QuickSight is priced at $9 per user per month and is a complete managed service which eliminates the need for software install and maintenance.
  • Accesses data from wide range of sources that Amazon already supports including EMR, RDS, DynamoDB, Kinesis, S3 and Redshift OR upload CSV, TSV, spreadsheet files, Salesforce cloud and on-premise databases.
  • Provides suggestions for best possible visualizations and has Smart Visualizations that infer data type.  Additionally, QuickSight suggests relationships between data sets.
  • Requires just a browser and also works great on mobile devices. Desktop software is not required to build metadata and/or reports.
  • Caches data in memory for super fast response times for reports and dashboards.
  • Allows end user to tell a story and easily share them with peers.
  • Planned Integration with a number of partner BI tools like Tibco, Domo, and Qlikview.

Screen Shot 2017-01-25 at 2.07.09 PM.pngProcess Flow from QuickSight

High Level Architecture of QuickSight

Screen Shot 2017-01-25 at 2.08.56 PM.png

Let’s review this architecture starting from bottom and going to top.

  • Source Systems: QuickSight can handle many data sources including Excel files, standard log files, Amazon EMR, Relational databases including RDS, DynamoDB, NoSQL databases and On-premise databases.
  • Data Lake: To combine various data sources in one layer, AWS suggests using Amazon S3 (file based) and/or Amazon Redshift as the data lake layer.  You can also complement your data lake with Software as a Service (SAAS) like Salesforce and directly consume that data to QuickSight.
  • Caching Layer: SPICE (Super-fast, Parallel, In-memory, Calculation Engine) is a in-memory columnar database with SQL like interface that provides quick responses to the queries made by the visualization layer.  SPICE has API’s and interfaces planned to integrate with partner products like TIBCO, Tableau and DOMO.
  • Visualization: QuickSight comes with intuitive visualizations with autograph based on automatic data type detection, native mobile user experience and ability to integrate third party visualization tools.

Amazon QuickSight is a very fast, cloud-powered business intelligence (BI) service that makes it easy for all employees to build visualizations, perform ad-hoc analysis, and quickly get business insights from their data. Amazon QuickSight uses a new Super-fast, Parallel, In-memory Calculation Engine (“SPICE”) to perform advanced calculations and render visualizations rapidly. In the next article, we will see how to create visualizations using QuickSight.

For further reading, you can pre-order my eBook: “Effective Business Intelligence with QuickSight” by Rajesh Nadipalli.

Bias comes in a variety of forms, all of them potentially damaging to the efficacy of your ML algorithm. Our Chief Data Scientist discusses the source of most headlines about AI failures here.

big data ,aws ,business intelligence ,AWS Quicksight

Published at DZone with permission of

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}