Skip to main content

AWS re:Invent 2015: Amazon QuickSight for business intelligence

There’s no question that Andy Jassy’s presentation at the AWS re:Invent 2015’s first keynote address covered a lot of ground across the spectrum of cloud technology. But his introduction of Amazon’s new cloud-based business intelligence solution, QuickSight, captured a lot of attention.
quicksight3QuickSight, by leveraging the integration of AWS data-oriented services, is built to reduce both the cost and complexity long associated with converting streams of data into useful business intelligence. In fact, Amazon claims that QuickSight can cut 90% off the cost of traditional solutions.
Part of the trick is capitalizing on the sheer volume of raw data your AWS-based operation might already have available. There’s a good chance that you’re already at least reasonably invested in storage (S3), data warehousing (DynamoDB, Redshift), streaming data (EMR, Kinesis), and big data analytics (Amazon Machine Learning): why not bring them all together to see what extra value you can access?
What might really help QuickSight take off, though, is the fact that Amazon has placed business intelligence squarely in the hands of the people who need the answers the most. You’ll get full functionality right from the browser interface without the need for data professionals (in fact, at this point there isn’t even an native API). Or, in Amazon’s own words:

Just log in, point to a data source, and create your first visualization in minutes

Slide stacks of visualizations – or “stories” as AWS calls them – can be saved and shared among colleagues, adding to the value of the insights.
QuickSight’s in-memory calculation engine (called SPICE, for “Super-fast Parallel In-memory Computation Engine”) can easily scale to smoothly deliver visualizations to hundreds of thousands of users in a particular organization.
Here are some notes based on the Q&A session:

  • Using SPICE as the main storage repository for your computational data is NOT recommended (even though SPICE data are archived and never automatically deleted).
  • You can mask data while generating reports, which will be a great feature for organizations with multiple security levels. Intelligent filters also allow you to open up access only to those parts of the dataset needed by a particular dashboard user.
  • You can incrementally import new data.
  • You can export XLS reports.
  • For best performance, feel free to import denormalized data from your DBMS. SPICE will generate all the needed views/tables and compress the dataset (up to 10x compression).
  • Use either Lambda functions or the dashboard to perform ETL! (Think: column or row level transformations using formulas and so on).

Still to come: support for streaming datasets for realtime and for GEO data, and ODBC/JDBC and Salesforce external data connections.
While Amazon QuickSight is not yet fully available, you can apply for access to the Preview version here.

Written by

Antonio is an IT Manager and a software and infrastructure Engineer with more than 10 years of experience designing, implementing and deploying complex webapps using the best available technologies.

Related Posts

— November 28, 2018

Two New EC2 Instance Types Announced at AWS re:Invent 2018 – Monday Night Live

Let’s look at what benefits these two new EC2 instance types offer and how these two new instances could be of benefit to you. Both of the new instance types are built on the AWS Nitro System. The AWS Nitro System improves the performance of processing in virtualized environments by...

Read more
  • AWS
  • EC2
  • re:Invent 2018
— November 21, 2018

Google Cloud Certification: Preparation and Prerequisites

Google Cloud Platform (GCP) has evolved from being a niche player to a serious competitor to Amazon Web Services and Microsoft Azure. In 2018, research firm Gartner placed Google in the Leaders quadrant in its Magic Quadrant for Cloud Infrastructure as a Service for the first time. In t...

Read more
  • AWS
  • Azure
  • Google Cloud
Khash Nakhostin
— November 13, 2018

Understanding AWS VPC Egress Filtering Methods

Security in AWS is governed by a shared responsibility model where both vendor and subscriber have various operational responsibilities. AWS assumes responsibility for the underlying infrastructure, hardware, virtualization layer, facilities, and staff while the subscriber organization ...

Read more
  • Aviatrix
  • AWS
  • VPC
— November 10, 2018

S3 FTP: Build a Reliable and Inexpensive FTP Server Using Amazon’s S3

Is it possible to create an S3 FTP file backup/transfer solution, minimizing associated file storage and capacity planning administration headache?FTP (File Transfer Protocol) is a fast and convenient way to transfer large files over the Internet. You might, at some point, have conf...

Read more
  • Amazon S3
  • AWS
— October 18, 2018

Microservices Architecture: Advantages and Drawbacks

Microservices are a way of breaking large software projects into loosely coupled modules, which communicate with each other through simple Application Programming Interfaces (APIs).Microservices have become increasingly popular over the past few years. The modular architectural style,...

Read more
  • AWS
  • Microservices
— October 2, 2018

What Are Best Practices for Tagging AWS Resources?

There are many use cases for tags, but what are the best practices for tagging AWS resources? In order for your organization to effectively manage resources (and your monthly AWS bill), you need to implement and adopt a thoughtful tagging strategy that makes sense for your business. The...

Read more
  • AWS
  • cost optimization
— September 26, 2018

How to Optimize Amazon S3 Performance

Amazon S3 is the most common storage options for many organizations, being object storage it is used for a wide variety of data types, from the smallest objects to huge datasets. All in all, Amazon S3 is a great service to store a wide scope of data types in a highly available and resil...

Read more
  • Amazon S3
  • AWS
— September 18, 2018

How to Optimize Cloud Costs with Spot Instances: New on Cloud Academy

One of the main promises of cloud computing is access to nearly endless capacity. However, it doesn’t come cheap. With the introduction of Spot Instances for Amazon Web Services’ Elastic Compute Cloud (AWS EC2) in 2009, spot instances have been a way for major cloud providers to sell sp...

Read more
  • AWS
  • Azure
  • Google Cloud
— August 23, 2018

What are the Benefits of Machine Learning in the Cloud?

A Comparison of Machine Learning Services on AWS, Azure, and Google CloudArtificial intelligence and machine learning are steadily making their way into enterprise applications in areas such as customer support, fraud detection, and business intelligence. There is every reason to beli...

Read more
  • AWS
  • Azure
  • Google Cloud
  • Machine Learning
— August 17, 2018

How to Use AWS CLI

The AWS Command Line Interface (CLI) is for managing your AWS services from a terminal session on your own client, allowing you to control and configure multiple AWS services.So you’ve been using AWS for awhile and finally feel comfortable clicking your way through all the services....

Read more
  • AWS
Albert Qian
— August 9, 2018

AWS Summit Chicago: New AWS Features Announced

Thousands of cloud practitioners descended on Chicago’s McCormick Place West last week to hear the latest updates around Amazon Web Services (AWS). While a typical hot and humid summer made its presence known outside, attendees inside basked in the comfort of air conditioning to hone th...

Read more
  • AWS
  • AWS Summits
— August 8, 2018

From Monolith to Serverless – The Evolving Cloudscape of Compute

Containers can help fragment monoliths into logical, easier to use workloads. The AWS Summit New York was held on July 17 and Cloud Academy sponsored my trip to the event. As someone who covers enterprise cloud technologies and services, the recent Amazon Web Services event was an insig...

Read more
  • AWS
  • AWS Summits
  • Containers
  • DevOps
  • serverless