Amazon Web Services launches Amazon QuickSight

Amazon Web Services has launched Amazon QuickSight, a very fast, cloud-powered business intelligence (BI) service that makes it easy for all employees, regardless of their technical skill, 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. Amazon QuickSight integrates automatically with AWS data services, enables organizations to scale to hundreds of thousands of users, and delivers fast and responsive query performance to them via SPICE’s query engine. Pricing for Amazon QuickSight starts at $9.00 per user, per month – one-tenth the cost of traditional BI solutions.

Too often, BI solutions require teams of data engineers to spend months building complex data models before ever generating a report, and these solutions lack interactive data exploration and visualization, limiting users to canned reports and pre-selected queries. On-premises BI tools also require companies to invest in complex and costly hardware and software, and then require them to invest in even more infrastructure to maintain fast query performance as database sizes grow. This cost and complexity makes it difficult for companies to make BI ubiquitous across their organizations.

Amazon QuickSight is built from the ground up to solve these problems by bringing the scale and flexibility of the AWS Cloud to BI. Getting started with Amazon QuickSight is simple and fast. When customers log in, Amazon QuickSight automatically discovers their data sets stored in AWS services such as Amazon Redshift, Amazon RDS (all engines), Amazon Simple Storage Service (Amazon S3), Amazon DynamoDB, Amazon Elastic MapReduce (Amazon EMR), and Amazon Kinesis. Customers can select any of the data sets discovered by Amazon QuickSight and get insights from this data in minutes. Amazon QuickSight formats the data and moves it to SPICE so it can be visualized in Amazon QuickSight, saving customers from having to manually Extract, Transform, and Load (ETL) the data, or invest in expensive ETL tools. Customers can choose for Amazon QuickSight to keep the data in SPICE up-to-date as the data in the underlying sources change. Customers pay a low monthly fee for each Amazon QuickSight user, eliminating the up-front costs of long-term licenses with annual maintenance. Amazon QuickSight provides a simple SQL-like interface to query the data stored in SPICE so that customers can continue using their existing BI tools from AWS partners like Domo, Qlik, Tableau, and TIBCO while benefiting from the faster performance delivered by SPICE.

“In a world increasingly dominated by connected devices and mobile users and where corporate data is moving to the cloud, our customers continue to collect and store massive amounts of their data across a wide range of AWS’s data services. These customers have been asking AWS for an analytics solution that can enable every one of their users to gain insights and make rapid decisions using this data,” said Raju Gulabani, Vice President of Database Services at Amazon Web Services. “And, after several years of development, we’re excited to bring Amazon QuickSight to our customers – a fast and easy-to-use BI service that addresses these needs at an affordable price. At the heart of Amazon QuickSight is the brand new SPICE in-memory calculation engine, which uses the power of the AWS Cloud to make queries run lightning fast on large datasets. We’re looking forward to our customers and partners being able to SPICE up their analytics.”

Built from the ground up for the cloud, SPICE uses a combination of columnar storage, in-memory technologies enabled through the latest hardware innovations, machine code generation, and data compression to allow users to run interactive queries on large datasets and get rapid responses. As users explore their data, Amazon QuickSight infers data types and relationships, issues optimal queries to extract relevant data, aggregates the results in the SPICE engine, and provides suggestions for the best possible visualizations of the data. SPICE supports rich calculations that help customers derive valuable insights from their analysis without ever having to worry about provisioning or managing infrastructure. SPICE automatically replicates data for high availability and also enables Amazon QuickSight to scale to thousands of users who can all simultaneously perform fast interactive analysis across a wide variety of AWS data sources. Users can also share their analysis with others in their organization using a StoryBoard feature.

“Nasdaq enables our customers to plan, optimize and execute their business vision with confidence, using proven technologies to provide transparency and insight for navigating today's global capital markets. Our technology powers more than 100 marketplaces, clearinghouses, and central securities depositories in 50 countries, and so generates a lot of data. We are always interested in new tools to analyze the data we have stored in Amazon Redshift, Amazon S3 and other sources,” said Nate Sammons, Principal Architect, Nasdaq, Inc. “Having super-fast performance as the data volumes and usage grows is critical to our users. Based on our preview of Amazon QuickSight, we found the SPICE in-memory calculation engine combined with an easy-to-use UI to be appealing for our use cases. We also like the ability to scale to very large data sets and many thousands of users with ease.”

“Intuit is a data-driven business. Our business users always ask for fast, intuitive access to data they can analyze at-will and get business insights instantly,” said Troy Otillio, Director, Public Cloud, Intuit. “Based on our initial preview of Amazon QuickSight, we think this service is going to challenge the status quo. It appears to be intuitive to our business users, particularly those in marketing who need an easy-to-use tool with super-fast performance. Plus, the ability to scale to very large datasets and many thousands of users with push button ease is attractive to us. We are looking forward to the pilot and to understanding how to better balance the cost and complexity of managing our software and infrastructure.”

AdRoll provides the world’s most widely used retargeting platform, helping businesses of any size to turn their customer data into high performance marketing. “At AdRoll, our mission is to help every marketer collect, analyze and use their data to deliver high-performance marketing campaigns,” says Valentino Volonghi, Chief Technology Officer, AdRoll. “Likewise, we are a data-driven company and we also want to make Big Data and Analytics accessible to everyone in our organization. Our employees have been asking for a BI solution that is easy to use and allows them to both access prebuilt dashboards as well as the capability to perform ad-hoc analysis on their data. The prospect of using Amazon QuickSight to analyze our large-scale data sets and make them readily available for our business users is promising. We are also excited about Amazon QuickSight’s ability to scale to a large number of users while providing super-fast response time for data visualization. These capabilities, coupled with the low entry price point makes Amazon QuickSight a promising solution to address our BI needs.”

RetailMeNot is the world’s largest marketplace platform for digital offers that helps retailers and brands connect with millions of active shoppers anytime, anywhere to drive engagement and sales. “In the last year, we migrated our data to Amazon S3 and Amazon Redshift and were able to simplify our operations, improve performance, and lower cost,” said Dale Smith, Senior Software Engineer at RetailMeNot. “As the volume of our data and the variety of types of data sets continue to grow, we need a solution that makes it easy for our BI, finance, and marketing teams to discover, access, and analyze these data sources. Amazon QuickSight’s intuitive and snappy web UI, and its ability to seamlessly scale to very large data sets make it a promising solution to address our BI challenges.”