Amazon QuickSight: 2019 in review

2019 has been an exciting year for Amazon QuickSight. We onboarded thousands of customers, expanded our global presence to 10 AWS Regions, and launched over 60 features—more than a feature a week! We are inspired by you—our customers, and all that you do with Amazon QuickSight. We are thankful for the time you spend with us across in-person meetings, conference calls, emails, discussion forums, and AWS summits. As we close this year, here’s a quick summary of the highlights.

re:Invent 2019

The Amazon QuickSight team was at re:Invent alongside customers such as Best Western, Capital One, and Club OS, who spoke about their experiences implementing and using Amazon QuickSight for their analytics needs. We also ran two hands-on workshops using the newly launched APIs.

ANT324: Deploy business analytics at enterprise scale with Amazon QuickSight

This session discussed how enterprises are rolling out Amazon QuickSight Enterprise Edition for all their users and using features such as Active Directory or Federated SSO (SAML/OpenID Connect) authentication, private connectivity to data in AWS, email reports, and embedded dashboards.

Best Western rolled out Amazon QuickSight for business reporting across tens of thousands of users, using it in conjunction with Amazon Redshift and AWS Glue. While their previous legacy reporting system took 18 months and over 7,000 staff hours to upgrade server software versions, they now benefit from Amazon QuickSight’s modern reporting infrastructure and constant feature updates, and do not need to manage any servers to report on this data.

Capital One has made Amazon QuickSight available internally to their BI community of over 25,000 users. Key benefits that the Capital One team sees from QuickSight include the ability to roll out new BI use cases without server setup or capacity planning, integrated machine learning (ML) capabilities, and the absence of a traditional software update cycle. All this is with PrivateLink connectivity to data in AWS (Snowflake, Presto, Amazon Redshift, and Amazon RDS), and pay-per-session pricing for consumption with a max charge of $5 per month, per reader.

ANT217: Embedding analytics into applications with Amazon QuickSight

This session dove into the latest features that allow you to integrate Amazon QuickSight dashboards into your software development lifecycle, including new APIs, theming capabilities, and dashboard embedding. The full session recording is available on YouTube.

As an Independent Software Vendor (ISV), Club OS uses Amazon QuickSight’s embedded capabilities to add analytics to their cloud-based Customer Relationship Management for fitness and wellness businesses. Amazon QuickSight’s serverless architecture lets Club OS focus on meeting actual customer needs without being burdened by operations and infrastructure management. This architecture also provides fast, consistent performance for end-users; the analytics dashboards are rolled out to over 40,000 users across 3,500 health and fitness locations. For more information, see the section of the talk on YouTube by Nicholas Hahn, VP of Product Club OS.

As an enterprise with tens of thousands of internal users, Capital One uses Amazon QuickSight’s embedded capabilities to add analytics to internal applications and portals. With no servers to set up, teams can set up embedded dashboards in their portals in as quickly as a week, whether they want to serve this to just a few users or thousands. Traditional BI approaches to such portals would require server setup and maintenance, and expensive licensing contracts. For more information, see the section of the talk on YouTube by Latha Govada, Senior Manager Analytics at Capital One.

ANT302 – Enhancing your applications with Amazon QuickSight dashboards

This hands-on workshop session guided users through setting up an Amazon QuickSight Enterprise Edition account, connecting to data, creating dashboards, and using APIs to add users, move assets across development and staging versions, and embedding dashboards in a web portal. For more information, see Dashboard Embedding & Operationalizing with Quicksight APIs. Try it out for yourself!

Embedding, theming, and APIs

We followed up on our launch of dashboard embedding for federated AWS identities at re:Invent 2018 (for more information about how the NFL uses embedded Amazon QuickSight dashboards for hundreds of stakeholders of Next Gen Stats, see the session video on YouTube). In 2019, we launched the following features:

• Embedded dashboards for all Amazon QuickSight-supported identity types, expanding beyond federated users supported initially.
• APIs for data (data sources, datasets, SPICE ingestion, and fine-grained access control over Amazon S3 and Amazon Athena data) and dashboards (dashboards and templates with versioning support). For more information, see Actions and Amazon QuickSight APIs on YouTube.
• Theming capabilities to customize dashboards to match applications where they are embedded, or corporate color and branding schemes. For more information, see Using Themes in Amazon QuickSight and Themes on YouTube.

Machine learning integrations

We added the following native ML integrations in Amazon QuickSight to help you make the most of your data in AWS and QuickSight:

• The ML Insights suite of features, which includes anomaly detection over billions of data points, identifying key contributors to a value, one-click ML-powered forecasting, and customizable, auto-created natural language summaries. We followed up with the ability to set up alerts to notify you whenever Amazon QuickSight detects anomalies in your metrics. For more information, see Amazon QuickSight – ML Insights Webinar on YouTube.
• The ability to augment data in Amazon QuickSight with ML models created and trained in Amazon SageMaker. Currently available in the N.Virginia, Ohio and Ireland regions only. For more information, see Add ML predictions using Amazon SageMaker models in Amazon Quicksight.

Visualizations and interactivity

We added the following support for new chart types, conditional formatting, QuickSight Actions, sheets in dashboards, and more:

• Gauge, Donut, and Word Cloud charts, along with the ability to add rich text through the insight editor. For more information, see Working with Visual Types in Amazon QuickSight.
• Conditional formatting support in tables, pivot tables, and KPI charts, with the ability to specify font color, background color, or icons. For more information, see Conditional Formatting on YouTube.
• QuickSight Actions providing advanced filtering capabilities through single point-and-click actions on dashboards. For more information, see QuickSight Actions on YouTube.
• Sheets within a dashboard to allow better organization of information across subject areas or topics. For more information, see QuickSight Multiple Sheets on Youtube.

Calculations and aggregations

We added the following new aggregation options, new functions, and more:

• Advanced table calculations such as window functions to compute moving aggregations, running functions to compute cumulative aggregations all at custom partition levels enabling enriched analysis.
• Level-aware aggregations to allow calculations irrespective of filters and aggregations are applied to your data. For more information, see Create advanced insights using Level Aware Aggregations in Amazon QuickSight.
• New aggregations, including percentile, variance, and standard deviation.
• New math functions, including exp, log, ln, and abs.

Data connectivity and security

We increased SPICE limits, provided finer control over data sources in QuickSight, enabled data source sharing, and more:

• SPICE datasets now accommodate up to 100 million rows of data in Enterprise Edition and 25 million rows for Standard Edition. For more information, see Data Source Limits.
• Fine-grained access control over S3 and Athena allows you to scope down access to these data sources to specific users or groups in Amazon QuickSight using IAM.
• Cross data source joins allow business analysts to perform joins across supported data sources without relying on data engineering teams to set up complex ETL processes.
• Shared data sources centralize credential management of data sources. This also allows shared ownership of data connections, allowing collaboration over SQL scripts that define custom SQL datasets.
• Connecting to Presto data sources in AWS without any public routing of data similar to Amazon Redshift, Snowflake, RDS, and others.
• Amazon QuickSight data sources connect to Amazon Athena, which you can tag against specific workgroups. This allows cost allocation of Athena queries by workgroup.

Mobile

We launched the new QuickSight Mobile app for iOS and Android, which allows you to access your dashboards and explore your data with drill-downs and filters. For more information, see New QuickSignt Mobile App on YouTube.

Geographic availability

We added the following new Regions and language support in Amazon QuickSight:

• Amazon QuickSight is now available in 10 AWS regions: US East (N. Virginia and Ohio), US West (Oregon), EU (Frankfurt, Ireland, and London), and Asia Pacific (Seoul, Singapore, Sydney, and Tokyo).
• The Amazon QuickSight interface is now available in 10 languages: English, German, Spanish, French, Portuguese, Italian, Japanese Korean, Simplified Chinese, and Traditional Chinese.

With all of our updates you can build dashboards like the ones below and integrate them into your applications and portals.

Looking ahead

To see the full list of 2019 launches, see What’s New in Amazon QuickSight or subscribe to the Amazon QuickSight YouTube channel for the latest training and feature walkthroughs. We have a packed roadmap for 2020, and continue to focus on enabling you with insights from all your data, sharing these with all your users, while not having to worry about operations and servers. Thank you for your support.

We wish you all the very best in the new year (and decade)!

About the authors

Jose Kunnackal John is a principal product manager for Amazon QuickSight.

Sahitya Pandiri is a senior technical program manager with Amazon Web Services. Sahitya has been in product/program management for 6 years now, and has built multiple products in the retail, healthcare, and analytics space.