amazon quicksight case study

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AWS Announces Five New Capabilities for Amazon QuickSight

New capabilities in Amazon QuickSight Q enable customers to forecast and to ask “why” questions

Automated data preparation makes it faster for customers to  start asking questions of their data using Amazon QuickSight Q

New paginated reporting feature makes it easy for customers to create and share business-critical operational reports using the familiar Amazon QuickSight interface

Amazon QuickSight’s in-memory engine now supports 1 billion rows of data, making it easier and faster to analyze and visualize large datasets

Customers can now programmatically create, manage, and edit Amazon QuickSight dashboards and reports to accelerate migrations from legacy systems

LAS VEGAS--( BUSINESS WIRE )--At AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced five new capabilities to help customers streamline business intelligence (BI) operations using Amazon QuickSight, the most popular serverless BI service built for the cloud. Today’s announcement expands QuickSight Q, a natural language querying capability, to support forecast and “why” questions and automate data preparation, making it easier and faster to start asking questions in natural language. Additionally, customers can now create and share paginated reports alongside interactive dashboards, quickly analyze and visualize billion-row datasets directly in QuickSight, and programmatically create and manage BI assets to accelerate migration from legacy systems. The new features announced today, combined with QuickSight’s scalability and pay-as-you-go pricing, enable customers to let users understand, visualize, and derive insights and predictions from data, regardless of technical expertise. To get started with QuickSight, visit  aws.amazon.com/quicksight .

“Organizations today are composed of numerous stakeholders with varying levels of technical expertise—all of whom need access to critical business insights to make better decisions and share knowledge,” said G2 Krishnamoorthy, vice president of Analytics at AWS. “That is why more than 100,000 customers use QuickSight to power their BI needs. Today’s announcement makes QuickSight even more intuitive, flexible, and accessible while streamlining BI operations with a comprehensive and fast service built for the cloud. Whether users want to forecast sales using natural language queries, distribute critical operational reports, embed analytics in high-traffic websites, or visually analyze massive datasets, we continue to innovate on behalf of our customers by providing advanced BI capabilities that support data-driven decisions at scale.”

Companies today gather unprecedented amounts of data that they want to use to make informed decisions, spot business trends, and increase efficiency. To help employees turn data into action, organizations must make this data accessible to a broad audience in formats ranging from natural language querying and paginated reports to interactive dashboards and embedded analytics. Amazon QuickSight, the most popular serverless BI service built for the cloud, makes this possible for customers including 3M, Best Western, Bristol-Myers Squibb, Capital One, Comcast, Experian, Guardian Life, McDonald’s, the National Football League, NTT DOCOMO, Siemens, and United Airlines. QuickSight has added more than 80 capabilities in the past year alone, making it easier for customers to deliver valuable business insights throughout their organizations, when and where needed. Today’s announcement builds on these advances to help customers migrate and consolidate their BI initiatives in the cloud.

• Support for forecast and "why" questions in Amazon QuickSight Q:  QuickSight Q uses machine learning to enable any user to ask questions about business data in natural language and receive accurate answers with relevant visualizations in seconds. QuickSight Q lets anyone explore historical trends and metrics without technical expertise, allowing users to derive new insights from the data that powers their dashboards and reports. For example, a sales user could ask, “Where did we sell the most items last year?” or a finance user could ask, “What is actual revenue compared to goal?” Many users want to dig even deeper to understand the underlying causes of different metrics or to model potential growth. With the new capabilities in QuickSight Q, business users can now ask forecast questions to project metrics if historical patterns hold and also ask "why" questions to see what historical data contributed to specific results. For example, a sales manager might ask to "Forecast sales for office chairs in California." QuickSight Q will provide a forecast of sales based on patterns of previous metrics that automatically account for seasonality and anomalous data. The sales manager might then ask, "Why did sales increase last month?" Within seconds, QuickSight Q summarizes the key drivers of that increase. That means business users can better understand underlying factors, and they can make more data-driven decisions that determine future outcomes. Support for forecast and “why” questions is available at no additional cost to all QuickSight Q customers.
• Automated data preparation for Amazon QuickSight Q :  A new capability in QuickSight Q automatically infers and adds semantic information to datasets, reducing the time BI teams spend prepping data for natural language querying from days to minutes. To prepare data for natural language queries, BI teams today must manually translate shorthand representations and abbreviations optimized for BI dashboards or SQL queries into commonly used business terms (e.g., cust_ID translates to Customer ID). The automated data preparation feature in QuickSight Q uses pretrained machine learning models and learnings from a customer’s existing assets (e.g., dashboards and reports) to preconfigure business terms in each new dataset in minutes, reducing the time it takes to start querying data. For example, a streaming service could use the QuickSight Q automated data preparation capability to preconfigure business terms for a dataset by using a preexisting dashboard that includes subscriber information by customer categories, customer IDs, and geographic locations. If a marketing manager is planning a launch campaign, they can ask, "How many premium subscribers do we have in Los Angeles?" and QuickSight Q will return precise results. Automated data preparation is available at no additional cost to all QuickSight Q customers.
• Paginated reporting built for the cloud:  Paginated reports provide a formatted, printable summary of data that organizations can use to broadly share critical operational information like daily transaction summaries and weekly updates with business users (e.g., executives, managers, and front-line workers). While many organizations have adopted modern BI products, those tools lack the ability to create and share paginated reports. This means customers often maintain multiple systems—one for modern BI needs and a separate legacy system for paginated reports. These on-premises systems can cost millions of dollars in infrastructure, have rigid license fees, and require dedicated resources to maintain, including replicating datasets across both systems. With Amazon QuickSight Paginated Reports, customers can now create, consume, and manage paginated reports in the cloud with the familiar QuickSight interface, eliminating the costs and complexity of a separate on-premises system. BI teams can use QuickSight’s point-and-click dashboard and report-authoring interface to create and publish reports in minutes, without learning a new tool or managing any infrastructure. Business users can access the reports alongside their interactive dashboards directly in QuickSight. QuickSight Paginated Reports is available as an add-on to all QuickSight Enterprise Edition customers.
• Simple and fast analysis for large datasets:  Amazon QuickSight’s Super-fast, Parallel, In-memory, Calculation Engine (SPICE) provides lightning-fast performance at scale, handling more than 100 million queries every week and processing an average of tens of trillions of records per hour. Today, SPICE enables thousands of users in an organization to perform fast, interactive analyses simultaneously without any infrastructure setup or management. While SPICE supports datasets of up to 500 million rows, customers who want to use QuickSight's rich visualizations to explore even larger datasets have previously had to rely on data engineers to manually orchestrate data between QuickSight and another data store (e.g., Amazon RDS, Amazon Redshift, or another data warehouse), which made it challenging to access and analyze very large datasets quickly. With billion-row support in SPICE, it’s easier to connect to data stores and ingest data into SPICE. Users now have greater autonomy to visually analyze large datasets directly in QuickSight, without coordinating with engineering teams to manually orchestrate data among services. Support for billion-row datasets is now available to all QuickSight Enterprise Edition customers.
• Faster, programmatic migration to the cloud :  QuickSight’s expanded application programming interface (API) capabilities now allow customers to create, manage, and edit their BI assets (e.g., dashboards, analysis, and reports) programmatically, helping accelerate and streamline migrations from on-premises legacy systems. Today’s BI tools lack full programmatic access to dashboards and reports, significantly complicating migration to a cloud-based BI offering. To move to the cloud, customers might need to re-create tens of thousands of dashboards and reports from scratch, which could take years. This barrier prevents many businesses from migrating away from legacy systems. API-based access to the underlying data models of dashboards and reports allows customers and partners to treat these assets like software source code, enabling fully programmatic deployments, peer code reviews, and auditability of all changes. Programmatic access to dashboards is available to all QuickSight Enterprise Edition customers at no additional cost.

Nasdaq is a global technology company serving the capital markets and other industries. “QuickSight Q has been a game changer in enabling executives, sales, and data engineering teams to get answers from data instantaneously. In many scenarios, our teams want to go beyond historical trends or current data snapshots to understand why something happened and forecast trends,” said Michael Weiss, product manager at Nasdaq North American Markets. “QuickSight Q’s new ‘why’ feature will help our users understand the top dimensions and values that contributed most to changes in key metrics, while forecasting will help our users explore forward-looking insights like future revenue and market share growth across market segments and customers. These new capabilities in QuickSight Q will help us accelerate BI adoption by fully automating complex data analyses and helping end users self-serve without the need for analyst-built models and analyses.”

Siemens is a global leader in electrification, automation, and digitalization. “At Siemens we power some of the largest manufacturing organizations in the world with our software-as-a-service solutions. Operational reporting has been a key requirement to ensure all of our customers receive detailed visibility into their organizational activities. While we have tried different solutions over the years, we consistently face challenges with reliability, stability, and ease-of-use,” said Massimilliano Ponticelli, product manager at Siemens. “We are excited that QuickSight now has paginated reporting capabilities built in, so we can use a single interface for both interactive dashboards and operational reports. This will help us further streamline our operations and ensure our customers have full visibility into every aspect of their business.”

Capital One is a leading financial institution specializing in credit cards, auto loans, banking, and savings accounts. “Many of our teams across all our lines of business rely on QuickSight to ensure users can access timely insights to make data-driven decisions, whether directly in QuickSight or embedded in line-of-business applications,” said Latha Govada, director of Enterprise Data Consumption Platforms at Capital One. “We are excited about QuickSight Paginated Reports, as it will give our users a greater choice of how they consume the data they need, without having to use a separate product. The ability to programmatically create and manage dashboards will also allow us to further automate and strengthen our BI operations. We love the pace of QuickSight innovation, which lets our teams be more agile with every release.”

Best Western Hotels & Resorts is an award-winning global family of hotels located in nearly 100 countries and territories that offers accommodations for all types of travelers. “We are a large and complex organization with 18 brands and varied ownership structures across geographies. Moving to QuickSight from legacy BI has helped us expand to over 23,000 users and reduce our costs by 30%. With QuickSight, we were able to consolidate multiple BI solutions and data sources to enable faster, more holistic insights,” said Joseph Landucci, director of Technology Management at Best Western. “The expansion of QuickSight’s SPICE capability to accommodate billion row datasets will provide us with continued performance at scale across a wide range of use cases, including marketing statistics, advance booking patterns, daily occupancy rates, and loyalty program information. Additionally, QuickSight Paginated Reports will allow us to bring to the fold users who prefer to have highly-formatted reports shared directly with them when needed, helping further our mission to democratize data across our organization.”

NISSAN is an international automotive company which sells vehicles under the Nissan, Infiniti, and Datsun brands. “As we scale the use of dashboards and reports to share data-driven insights on connected car data across our organization, it is becoming increasingly difficult to rely on the time-consuming and error-prone process of manually deploying BI assets,” said Daisuke Hyodo, deputy general manager of Research and Development, Data Science, and Global IT at NISSAN. “As an agile data and analytics team, we are excited to use QuickSight’s expanded API capabilities to programmatically manage analyses and dashboard assets in our DevOps pipeline. This will allow us to promote changes faster and quickly share valuable insights with our end users.”

Traeger Grills is a leading provider of smokers, grills, and barbeque products. “Our operations team uses QuickSight to deliver fast, accurate information and solutions to our customers and partners. It has helped us realize a 90% reduction in our BI costs while serving over 700 users across a variety of use cases, from distribution center forecasts to reporting Amazon Connect call center metrics. It has also allowed us to enable augmented self-service by allowing users to ask questions in natural language directly in QuickSight Q without having to wait for an analyst, and to ensure consistent high performance with QuickSight's SPICE data engine,” said Corey Savory-Venzke, vice president of Customer Experience at Traeger. “We are excited about the new forecast and ‘why’ capabilities in QuickSight Q, which will help our users gain a deeper understanding of their data. As our usage and datasets grow, SPICE's ability to handle 1 billion row datasets will also be critical in ensuring consistent high-performance for all our users.”

Anthology provides a holistic ecosystem of EdTech solutions for over 150 million learners, educators, and administrators in over 80 countries. “Sharing business insights from across our EdTech platform is a critical part of our mission to provide dynamic, data-informed experiences to the global education community. While almost everyone would benefit from these insights, not everyone wants to fetch information from a dashboard,” said Steve Bailey, director of Product Management, Data, and Analytics at Anthology. “We are excited about QuickSight Paginated Reports, which will help our end-users access business-critical insights in a consumable format delivered directly to them, while also making it significantly easier for our developers to create and schedule reports in minutes using the familiar QuickSight interface.”

Showpad is a sales enablement platform helping B2B sales teams globally maximize impact. “At Showpad, we embed QuickSight dashboards within our customer facing applications to improve sales and marketing effectiveness. We've also introduced QuickSight Q so users can ask business questions that go beyond existing dashboards. As a fully SaaS based product, we continuously deliver product updates to our customers following DevOps practices,” said Jeroen Minnaert, head of Data at Showpad. “We are excited to use QuickSight’s expanded API capabilities to allow programmatic creation and management of dashboards. This will allow us to treat QuickSight assets as software components and promote our analyses and dashboards automatically from development to staging to production even faster than before. The introduction of forecast and ‘why’ questions in QuickSight Q will help us further enhance customer value by enabling users to uncover key contributors to changes in the metrics that matter and forecast adoption without the need for technical analysts.”

About Amazon Web Services

For over 15 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud offering. AWS has been continually expanding its services to support virtually any cloud workload, and it now has more than 200 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 96 Availability Zones within 30 geographic regions, with announced plans for 15 more Availability Zones and five more AWS Regions in Australia, Canada, Israel, New Zealand, and Thailand. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs. To learn more about AWS, visit  aws.amazon.com .

About Amazon

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s Most Customer-Centric Company, Earth’s Best Employer, and Earth’s Safest Place to Work. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, Amazon Studios, and The Climate Pledge are some of the things pioneered by Amazon. For more information, visit  amazon.com/about  and follow @AmazonNews.

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Introducing new analysis experience on Amazon QuickSight

Amazon QuickSight is a scalable, serverless, embeddable, machine learning (ML)-powered business intelligence (BI) service built for the cloud. It enables you to create and publish interactive dashboards and highly formatted reports accessible through web browsers or mobile devices. On November 16, 2023 – QuickSight has launched a new analysis experience, enabling a more intuitive and efficient way for you to author dashboards on QuickSight. In this post, we will walk you through the key experiences of this redesign and explore the enhanced workflows that empowers authors to create beautiful dashboards and reports.

With the new experience, we have redesigned the core authoring workflows to be more intuitive, scalable, and efficient. This post outlines the key elements and the core authoring workflows that has been redesigned.

Key experiences

QuickSight offers the following key experiences with this redesign:

The following shows how the core authoring workflows are redesigned to streamline the creation process:

Navigating the the new experience: While most changes we have introduced are designed to be intuitive, we are also introducing the ability for authors to search any analysis action to resolve the challenges of discovering features and workflows. Integrated within the Analysis menu, quick search significantly eases the task of locating any feature within the analysis experience. With search results refined with each keystroke, quick search makes finding specific features effortless. You can navigate to desired features, while boosting productivity in dashboard creation tasks.

Opting out of the beta experience – If you want to return to the previous experience, you can do so until January 31, 2024. To opt out, click New Look in the top right of the toolbar, then select Switch back . You can always revisit this option to switch back to the new look when you’re ready.

Console Embedding Experience

Starting December 20, 2023 – the new experience will also be available for authors and customers using the analysis experience in an embedded mode.

In this post, we showed how the redesigned analysis experience further enables QuickSight to serve as a robust, flexible, and secure BI platform suitable for a wide range of data analytics requirements. The new analysis experience is already available in Amazon QuickSight Standard and Enterprise Editions. For console embedding customers the new experience will be available starting December 20, 2023.

For more information, refer to Amazon QuickSight and the What’s New Feed for QuickSight . If you have any questions or feedback, please leave a comment.

For additional discussions and help getting answers to your questions, check out the QuickSight Community .

About the author

Amazon Quicksight: Overview and Review

The top 5 things to know about Amazon QuickSight:

Amazon QuickSight is an AWS business intelligence tool.

Amazon powers the QuickSight SPICE, a fast, parallel, in-memory calculation engine.

QuickSight allows users without coding knowledge to explore data and extract different insights.

The QuickSight platform integrates with a wide range of data sources (Amazon Redshift, Amazon Athena, local Excel files, and more).

QuickSight can handle multiple business domains while independently measuring business metrics.

Having the right information at your fingertips is the key to making sound business decisions. But your ability to interpret that information — and the speed at which you can access it — is equally essential. That's where Amazon QuickSight comes in.

According to the AWS website , Amazon QuickSight is "a fast, cloud-powered business intelligence service that makes it easy to deliver insights to everyone in your organization." The platform does this with stunning visuals and interactive dashboards that present real-time, machine learning (ML) insights to your company's decision-makers.

The problem is that Amazon QuickSight has a lot of cutting-edge competitors in the BI space, such as Tableau, Microsoft Power BI, and other top BI tools . Therefore, it's important to fully understand what QuickSight has to offer in comparison.

This Amazon QuickSight overview and review will outline everything you need to know about its BI capabilities, from visual presentations to advantages and disadvantages to cost, pricing, and alternatives. In addition, this article will highlight Amazon QuickSight's BI capabilities and how these capabilities can be aided through the use of a data integration platform like Integrate.io. 

Integrate.io is a new ETL platform that possesses Reverse ETL, CDC, and other data integration capabilities that allow companies to better handle their valuable data and easily retrieve it from multiple sources. Read on to learn more about Amazon QuickSight in this Amazon Quicksight overview and review, or simply schedule a call with Integrate.io today!

Table of Contents

What is amazon quicksight, visual presentations , advantages and disadvantages, cost, pricing, and alternatives , is amazon quicksight right for your company.

Let Integrate.io Help With All Your Data Integration Needs 

Let's dive into this Amazon QuickSight overview and review. The first thing to know is that Amazon QuickSight is a business intelligence tool under the umbrella of the Amazon Web Services (AWS) platform. In addition, QuickSight features stunning visualizations, interactive dashboards, and accurate machine learning insights.

Speed is another selling point. Amazon powers the QuickSight platform with its Super-fast, Parallel, In-memory Calculation Engine, or SPICE. According to Amazon :

“SPICE is … designed specifically for fast, ad hoc data visualization. SPICE stores your data in a system architected for high availability, where it is saved until you choose to delete it. You can improve the performance of database data sets by importing the data into SPICE instead of using a direct query to the database.”

Once your BI team sets up the dashboards and visuals in QuickSight, company decision-makers can fine-tune them to display the machine learning analysis and real-time data they're looking for. Moreover, they can access their dashboards from any computer, web browser, or internet-connected iPhone or iPad device.

QuickSight is all about the visuals. Although more expensive BI solutions — like Tableau — have additional visualization options in terms of quantity, the basic visual presentations QuickSight offers are more stunning. That offers a tremendous advantage when meeting with clients and customers.

A typical visual presentation on the QuickSight platform features the following components:

Analyses: QuickSight calls the workspace where you create and interact with visuals an “analysis.” In this analysis, you can arrange and calibrate a number of graphical data presentations, like interactive graphs and charts relating to performance metrics, sales analyses, or cost analyses. You can also include a “story” (see the definition of “stories” in the final section below).

Visuals: A visual is a graphical presentation of data. It could be a chart, table, graph, or diagram. Newly created visuals start in the “AutoGraph” mode. AutoGraph uses an algorithm to automatically choose visual presentations for the data you select. You can then pick your own visualizations from selections like heat maps, treemaps, combination charts, pivot tables, and more. You can also change the colors, apply filters, and reorganize their positions.

Insights : Insights offer valuable interpretations of the data in your “analyses.” QuickSight’s Enterprise Edition will automatically suggest appropriate machine learning insights — and data presentations — after analyzing your data.

Sheets: Sheets are groups of visuals that appear on a single page. While setting up an analysis, you’ll put the selected visuals into the sheet, like the front page of a newspaper. Your analysis can include more than one sheet, each with its respective visualizations working together or separately.

Stories: A story allows you to capture multiple visuals or “scenes” that you present on the sheet, like a slideshow. Users can scroll through the scenes in the story to see different aspects of the analysis. The scenes aren’t static — they update in real-time like all the other graphs, charts, and datasets on the dashboard. 

Together, the above features allow your BI team to create beautiful, interactive data presentations to assist in diverse business areas:

Managers can use them to inform their leadership decisions.

Sales personnel can use them during client presentations.

Marketing teams can use them to track the results of advertising campaigns.

Accountants can use them to monitor key financial metrics. 

After evaluating the QuickSight platform and finding out what real users think, we identified the following advantages of Amazon QuickSight:

Key Advantages of Amazon QuickSight 

Quick Setup and Easy to Use

Your BI team can activate the SPICE engine, integrate data, and start using the QuickSight platform much faster than other BI platforms. According to this user : “It takes less than one hour to set up.”

Another user says: “Easy and intuitive user interface… Less learning curve.”

Highly Compatible with Different Data Sources

Integrating QuickSight with different data sources is easy. The platform integrates with data sources like Amazon Redshift, Amazon Athena, Amazon S3, Amazon Aurora, Apache Spark, Presto, SQL servers, local Excel files, and more. It also supports information from services like Salesforce and Tableau.

As this user states: “You are able to choose your data source. It can be integrated with the popular BI tools and much more.”

This user said: “I loved that it has support for other services such as Salesforce, Tableau, etc., to import data.”

Access Dashboards on Any Web Browser or iOS Device

Most users will access QuickSight dashboards and insights through a web browser . According to QuickSight, “Amazon QuickSight supports the latest versions of Mozilla Firefox, Chrome, Safari, Internet Explorer version 10 and above, and Edge.” iPhone and iPad users can also access and interact with the dashboard via their internet-connected iOS devices.

A Quicksight Dashboard

Stunning Visualizations

Compared to other solutions like Tableau, most users agree that the quality and presentation of QuickSight’s visualizations are superior. In addition, QuickSight’s “AutoGraph” feature applies a set of algorithms to learn about your data. Then it recommends suitable graphics to make sure you’re selecting the best visuals and analytics for the situation.

Get Insights Without Needing to Code

The interactive nature of QuickSight dashboards allows users without coding knowledge to explore data and extract different insights. This empowers everyone to access the vital stats they need.

Cost-Friendly Payment Options

In comparison to older or more-developed BI solutions like Tableau Server and Microsoft Power BI, Amazon Quicksight is a more cost-friendly solution at both the individual level and for enterprises as a whole. 

Here’s what users say about QuickSight pricing:

“We chose them mainly because of the pay per session feature that they have. This allows us to only have to pay for what we actually use. With no upfront costs and no annual fee, these guys are hard to beat.”

“The cost is very low compared to other solutions.”

“The cost can’t be beaten. While the package lacks many of the bells and whistles that are in Tableau or Looker, it has all the basics and gets the job done for 90% of our users.”

Impressive Scalability

QuickSight can handle multiple business domains while independently measuring business metrics. Tens of thousands of users can work on the platform simultaneously with access to all sources of data at the same time. In addition, QuickSight’s cutting-edge data engine technology frees up users to explore gigantic datasets.

Excellent iOS App for Mobile Access

The app for Amazon QuickSight ( for iOS and Android ) delivers on-the-go access to data, so decision-makers can view stories, insights, analyses, and dashboards wherever they are.

Key Disadvantages of Amazon QuickSight 

Amazon QuickSight is not without its disadvantages. After using this platform and finding out what real users think, we identified the following setbacks:

Limited Options for Charts and Graphs

Users complain that the options for charts and graphs — although visually stunning — are limited compared to other flagship BI solutions. This is the most frequently cited disadvantage of QuickSight. As this G2Crowd reviewer states: “Compared to Tableau or other focused solutions, Amazon QuickSight still lacks a lot of customization features. Limited data visualization types (only a few simple and popular charts)…”

One more user says: “It lacks some useful visualization capabilities found in competing tools.”

This user provides more detail:

“There is a severe lack of ability to make custom fields, group bys, and other features that other BI solutions excel at. For example, I wish I could have the functionality to really customize some level of detail expressions as well as more control over the colors and styles of the visualizations. Currently, it is not flexible enough to meet most of my customer’s needs. For example, my customers will not only want high-level looks but also want to drill down and pull out tables of data which seems like it is implemented but is not robust enough.”

In response to these criticisms, it’s important to note that Amazon is still developing QuickSight — and the platform will continue to evolve with new features over time. As of May 2022, Amazon QuickSight has achieved a 4 out of 5-star rating from 157 user reviews on G2. 

Still New to the BI Scene

QuickSight is new to the BI scene and requires further development to reach parity with popular BI solutions like Tableau and Microsoft Power BI. That’s a fact. Nevertheless, the pay-per-session pricing makes QuickSight one of the most cost-effective BI solutions available. However, larger enterprises may choose to go with one of the more established BI solutions as they tend to have better administrative features.

Amazon QuickSight: Cost and Pricing 

When it comes to BI tools, Amazon QuickSight is a cost-effective solution at both the standard and enterprise levels. In addition, Amazon QuickSight has two pricing structures at the enterprise level, which include both readers and authors. 

Amazon QuickSight Standard Edition Pricing (Authors)

At the standard edition level, authors can create and publish interactive dashboards for just $9 per month with an annual subscription that requires a one-time yearly payment of $108. 

If authors would rather choose a month-to-month plan with the opportunity to cancel at any time, they will have to pay $12 per month. 

Both of these payment options come with 10 GB of SPICE per author. 

Authors can pay $0.25 per GB for additional capacity if more SPICE capacity is needed. 

Amazon QuickSight Enterprise Level Pricing (Authors and Readers)

Authors can create and share dashboards with other users in the account for $18 per month with an annual subscription that will require a one-time payment of $216. 

Authors can also choose a month-to-month plan for $24 per month with the ability to cancel at any time. 

Authors with Q can explore their data simply by asking questions, setting verified answers, and fine-tuning Q to better align with business domains for $28 per month with an annual subscription that will require a one-time payment of $336. 

Authors with Q can also choose a month-to-month plan for $34 per month with the ability to cancel at any time. 

Readers with the user pricing can explore interactive dashboards, receive email reports, and download data for $0.30 per session up to $5 max per month.

Readers with the capacity pricing can purchase reader sessions or Q sessions in bulk without having to provision individual readers. 

Plans are based on capacity, with the lowest monthly capacity plan being 500 sessions per month for $250 per month. 

The lowest annual capacity plan is 50,000 sessions per year for $20,000 annually. 

More pricing options can be found on AWS.Amazon .

Readers with Q with the user pricing can explore topics shared with them by simply asking questions for $0.30 per session up to $10 max per month.

In addition, accounts enabled with Q are charged $250 per month for a Q base fee. 

There are two options for authors at the enterprise level, which include Authors and Authors Q. 

Authors with Q

Additionally, there are two options for readers at the enterprise level, which include Readers and Readers with Q. Plus, there is a user pricing plan and a capacity pricing plan. 

Readers with Q

Alternatives to Amazon QuickSight 

While Amazon QuickSight offers its users access to some top-tier BI tools, they face some steep competition in the business intelligence space. Let’s compare some of Amazon QuickSight’s top competitors. 

Tableau Server 

As of May 2022, Tableau Server has achieved a 4.2-star rating out of 5 stars on G2 from 424 users. In comparison, Amazon QuickSight has received 4 out of 5 stars from 157 users.

Reviewers of the two platforms noted that Tableau Server is easier to administer, but Amazon QuickSight is easier to use and set up. 

Tableau Creator is available for $70 per month, which is billed as $840 annually. In comparison, enterprise users can get started on Amazon QuickSight for just $18 per month, which is billed as $216 annually. 

Related Reading: The Best Tools for Visualizing E-Commerce Data

Microsoft Power BI

Power BI Pro provides individual users with self-service analytics for $9.99 per month. 

Power BI Premium provides individual users with advanced self-service analytics and data management for $20 per month. 

Power BI Premium per capacity is available for organizations starting at $4,995 per capacity per month. 

As of May 2022, Microsoft Power BI has achieved a 4.4-star rating out of 5 stars on G2 from 792 reviews. 

Reviewers noted that both Microsoft Power BI and Amazon QuickSight were easy to use and set up. However, the average reviewer preferred the administration ease offered by Microsoft Power BI.  

Microsoft Power BI has a variety of pricing options .

Related Reading: How to Prepare Data for Microsoft Power BI

Amazon QuickSight customers praise the platform’s speed, ease of use, and sound data analytics. They laud the visual appearance of its interactive dashboards. And they appreciate saving money with its pay-per-session pricing. Moreover, you’ll be in good company if you decide to be a QuickSight customer. Their client list includes prestigious names like:

The National Football League (NFL)

Best Western

MLB Advanced Media

Ultimately, QuickSight is a quality BI solution without complexity. Choosing this cost-friendly business intelligence platform from Amazon means that you will be in good hands.

Related Reading: How to Build a Business Intelligence Strategy

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Hopefully, this Amazon QuickSight overview and review has given you a deeper insight into what this BI solution has to offer your organization. So, are you ready to employ Amazon QuickSight as your new business intelligence solution? Here’s one thing to know: the process of integrating large volumes of data from multiple sources with a new BI solution can be time-consuming and headache-inducing.

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Important: We've redesigned the Amazon QuickSight analysis workspace. You might encounter screenshots or procedural text that doesn't reflect the new look in the QuickSight console. We're in the process of updating screenshots and procedural text.

To find a feature or item, use the Quick search bar .

For more information on QuickSight's new look, see Introducing new analysis experience on Amazon QuickSight .

Working with insights in Amazon QuickSight

In Amazon QuickSight, you can add ready-to-use analytical computations to your analysis as widgets. You can work with insights in two ways:

Suggested insights

Amazon QuickSight creates a list of suggested insights based on its interpretation of the data you put into your visuals. The list changes based on context. In other words, you can see different suggestions depending on what fields you add to your visual and what type of visual you choose. For example, if you have a time-series visualization, your insights might include period-over-period changes, anomalies, and forecasts. As you add more visualizations to your analysis, you generate more suggested insights.

Custom insights

Custom insights enable you to create your own computation, using your own words to give context to the fields that appear in the widget. When you create a custom insight, you add it to the analysis, and then choose what type of calculation that you want to use. Then, you can add text and formatting to make it look how you want. You can also add more fields, calculations, and parameters.

You can add any combination of suggested and custom insights to your analysis, to create the decision-making environment that best serves your purposes.

• Adding suggested insights
• Adding custom insights to your analysis

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Choosing the Right BI Tool: A Comparison of Power BI and Amazon QuickSight

Discover the perfect Business Intelligence (BI) tool for your business with Metal Toad's expert comparison of Power BI and Amazon QuickSight.

Introduction:

Welcome to the Metal Toad blog, your go-to source for insights into AWS machine learning and cutting-edge technologies. In today's post, we'll dive into the comparison of two powerful Business Intelligence (BI) tools — Power BI and Amazon QuickSight. As Metal Toad stands as the #1 AWS Machine Learning specialist in the Pacific Northwest, we're dedicated to providing expert guidance on choosing the right tools for your business needs.

Microsoft’s Power BI:

Developed by Microsoft, Power BI stands out for its robust capabilities in data visualization, reporting, and analytics. Seamlessly integrating with other Microsoft products like Excel and Office 365, Power BI boasts an extensive range of data connectors, facilitating easy integration with various data sources.

Key Features of Power BI:

• Advanced-Data Visualization
• Interactive Dashboards
• AI-Powered Analytics
• Comprehensive Reporting Tools
• Wide Array of Data Connectors
• Effective Handling of Large Datasets

Scalability:

Power BI is suitable for both small businesses and large enterprises, offering scalability that grows alongside your business needs. Its desktop and cloud-based versions provide flexibility for users of all levels.

Amazon QuickSight: Navigating BI in the AWS Ecosystem

As Amazon's BI tool designed for AWS, QuickSight shines with its seamless integration with AWS services and databases. Operating on a pay-per-session pricing model, QuickSight can be particularly attractive for businesses with variable usage patterns.

Key Features of QuickSight:

• Easy Data Visualization and Analysis
• Integration with Various AWS Services
• ML-Powered Anomaly Detection
• Integration with AWS Data Services (Redshift, S3, and more)

Ease of Use:

QuickSight offers a user-friendly interface and is straightforward to set up and use, especially for businesses already immersed in the AWS ecosystem.

Choosing Between Power BI and QuickSight: 

The choice between Power BI and QuickSight often comes down to your business ecosystem. If your operations heavily rely on AWS services, QuickSight's integration with the AWS ecosystem is a practical choice. Conversely, if your business operates within the Microsoft ecosystem, Power BI might seamlessly align with your existing tools.

Considerations:

• Existing Technology and Integration Needs
• Desired Features
• Ease of Use
• Cost Considerations

Conclusion: Elevating Your BI Experience with Metal Toad and Amazon QuickSight

In conclusion, the decision between Power BI and QuickSight is a crucial one, influenced by various factors. For businesses deeply embedded in the AWS ecosystem, the seamless integration and robust features of Amazon QuickSight make it a compelling choice. As the #1 AWS Machine Learning specialist in the Pacific Northwest, Metal Toad stands ready to guide you through the implementation of QuickSight for unparalleled business intelligence.

Why Choose Metal Toad for QuickSight Implementation?

• Expertise: Our team comprises certified AWS machine learning experts with a wealth of experience in application development, architecture, migration, and DevOps.
• Support: Backed by 24x7 support, Metal Toad ensures a smooth and reliable QuickSight implementation, addressing any concerns or challenges promptly.
• Scalability: As your business grows, Metal Toad's QuickSight solutions scale alongside, providing the flexibility and power your evolving needs demand.
• Seamless Integration: Metal Toad specializes in integrating AWS services, making the transition to QuickSight a seamless and efficient process.

For a personalized consultation on how Metal Toad can elevate your business intelligence with Amazon QuickSight, contact us today. Explore the possibilities of data visualization, analysis, and ML-powered insights with Metal Toad—the trusted partner for AWS machine learning solutions in the Pacific Northwest. Your journey to optimized business intelligence starts here.

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AWS QuickSight vs Power BI: Top Differences & Similarities

Home Blog Business intelligence and Visualization AWS QuickSight vs Power BI: Top Differences & Similarities

Data visualization helps bridge the gap between numbers and the number of words required to convey the information. Compelling storytelling using data can convert data points into insights and insights into decision-making for the business. In this scenario, it is important to choose the most suitable tool from an array of available options in the market to perform this action effectively. AWS QuickSight and Microsoft Power BI are two powerful tools in this space that have redefined data visualization.

Quicksight and Tableau are tools like Power BI but with their own specific uses and different user categories. In this article, we will focus on the major use cases and differences between these two tools, Amazon QuickSight vs Power BI . We will also discuss a few similarities and help students decide which tool to take based on their specific needs. In today’s scenario, aspiring analysts and data scientists must skill up using Power BI Certification from Microsoft to sharpen skills and gain an edge over their peers. Now let’s dive in to know more!

AWS QuickSight Vs Power BI [Head-to-Head Comparison]

Difference between aws quicksight and power bi.

In thi section, let’s discuss the above differences in detail for better understanding:

1. AWS QuickSight vs Power BI: Performance

• Amazon QuickSight : QuickSight is a software similar to Power BI. It uses an advanced in-memory calculation engine called SPICE (Super-fast, Parallel, In-Memory Calculation Engine).
• Example: Imagine that your team is analyzing sales data for an internet consumer company with millions of transactions that happen weekly. QuickSight's SPICE engine stores the aggregated data in memory, allowing very fast query response times. Your team could interact and filter the data by region, product, or time period, and QuickSight would instantly refresh the data visualization dashboard
• Microsoft Power BI:  Emphasizes overall performance through its DAX (Data Analysis Expressions) language. This technique allows to perform complex calculations seamlessly. Example: Imagine that your product team is analyzing financial data and has to calculate growth rates for the quarter. These are millions of data points that you’re analyzing to get insights. Power BI's DAX expressions can easily perform such calculations, but some more complex DAX calculations might affect dashboard performance and refresh date.

2. AWS QuickSight vs Power BI: Visualization

• Amazon QuickSight:  Offers an extensive array of visualizations that are suitable for various data types . Example: Assume your growth team is studying survey results. The team can utilize QuickSight to produce dynamic bar charts, pie charts, and even location maps that display survey responses by location. These interactive images allow consumers to drill down into specific categories for deeper insights.
• Microsoft Power BI : Enables customization of almost any data type that is used in the data industry from tables to JSONs. Example: Assume your marketing team is reviewing the efficacy of a marketing campaign. With Power BI, the team can generate complex funnel visualizations to show the rate of conversion at every phase of the customer experience. Product managers can interact with these visuals, enhancing involvement and understanding, and giving them a bird’s eye view of the business metrics.

3. AWS QuickSight vs Power BI: Customization

• Amazon QuickSight:  Prioritizes simplicity, it contains a few fundamental options for customizing. Example, you can change the color schemes and styles to reflect your brand's identity. To geta cohesive view while tracking social media interaction, you are free to choose shades that match your business's emblem.
• Microsoft Power BI : Specializes at customization, which include features such as bespoke themes and elaborate formatting for better user interaction. Example: You are creating a financial dashboard. Power BI helps you to customize each component of the dashboard, from colors to data labels and corresponding positions, to make sure that it adheres to the company's design guidelines and principles.

4. AWS QuickSight vs Power BI: Speed

• Amazon QuickSight : The SPICE engines speed up retrieval of data and analysis. Example: if your growth team is measuring traffic to your website, QuickSight's in-memory processing ensures that even when the team deals with enormous data sets, it is possible to quickly visualize trends, clicks, and user activity.
• Microsoft Power BI : Increases the query efficiency by employing caching technology. Example: Your business team is looking at figures for sales by region for a quick root cause analysis. Power BI efficiently caches this data, which enables the dashboard to load quickly when switching between regions, by following the cached information with the help of RAM. But, when the team performs complicated computations on huge data sets like sub-region levels, the level of detail of those calculations could influence the rate of execution. There are not many similar tools like Power BI that offer such a level of performance.

5. AWS QuickSight vs Power BI: Big Data Support

• Amazon QuickSight:  The SPICE engine employed by QuicSight is an excellent tool for managing huge datasets. Imagine the following scenario: You are the lead analyst studying sensor data from your industry’s manufacturing equipment array. The ability of QuickSight to load and assess tens of millions of readings from IOT devices in memory allows your team to find anomalies and configurations in real time. This will help your business to take corrective actions in a timely manner.
• Microsoft Power BI : The combination of BI and Azure Data Lake Storage is advantageous in big-data configurations. Imagine your team which looks at customer behavior across multiple channels. The Azure Data Lake link in Power BI allows you to explore both organized and unorganized information, and provides an exhaustive view of customer interactions, which can help make holistic business decisions.

6. AWS QuickSight vs Power BI: Scalability 

• Amazon QuickSight:  AWS enables seamless scalability by making use of excellent hardware infrastructure and acknowledging cstomer data needs. Imagine that your company arranges a virtual event, resulting in a spike in dashboard access. In this scenario, QuickSight automatically scales up in response to rising user demand and delivers an uninterrupted experience.
• Microsoft Power BI : Uses existing infrastructure that is employed in Microsoft Azure cloud. Imagine you, as a product manager releasing a new product and your team expects an uptick in dashboard usage post the release. Because of Power BI's connectivity with Azure, your team can dedicate additional resources adequately to handle increasing traffic while maintaining performance and speed.

7. AWS QuickSight vs Power BI: Overall Cost

• Amazon QuickSight: Quicksight operates as a pay-per-session service. Consider the following scenario: your business wants to share quarterly revenue numbers with stakeholders. QuickSight's pricing model charges you only when users actually use the dashboard, making it suitable in cases where a regular look at the dashboard is not within business requirements as per stakeholders.
• Microsoft Power BI : It comes in multiple pricing categories, allowing users to choose plans as per their needs. Assume you have a team of analysts who regularly create and distribute analyses. In this case, the premium edition of Power BI may be ideal because it offers limitless sharing without paying any extra amount per user. It essential to take into account your organization's pattern of consumption to be able to pick the most cost-effective choice.

How Are They Similar?

Now that we've explored the differences between these two tools, it's equally important to recognize that AWS QuickSight and Microsoft Power BI share some commonalities. Let's delve into the ways in which these powerful data visualization tools are similar.

• User-Friendly Interface:  Both QuickSight and Power BI have intuitive user interfaces that enable for simple navigation and data analysis for individuals with various technical skills.
• Interactive dashboard:  QuickSight and Power BI both allow users to create interactive and dynamic dashboards. These tools let users build intriguing visualizations, examine data, and capture actionable insights, improve data-driven association to promote better decision-making within organizations. Even though tools can help analysts with reporting and storytelling, they have to be in the top of their game in deriving meaningful value, Business Intelligence courses  can help them upskill in this regard.
• Data Source Compatibility : QuickSight and Power BI both can connect to a wide range of data sources like spreadsheets, databases, cloud services, and APIs, with flexibility. This compatibility enables data integration simpler for newcomers, allowing individuals to interpret data from multiple sources with limited technical expertise.

What Should You Choose Between AWS QuickSight and Power BI?

The choice you make is influenced by factors such as currently available tools, database complexity, available funds, and reporting tools like Power BI. If you are in a corporate setting, then the company’s budget for analytics, including tools like AWS BI reporting and similar tools like Power BI, plays a role. QuickSight is excellent for AWS users who require integrated analytics using the existing compatible systems. Power BI supports significant customization, making it suited for Microsoft-centric work environments. To make the most suitable choice, consider the performance, design, and scalability requirements of your project. Acquiring the skillset and conceptual industry knowledge by using KnowledgeHut Power BI certification from microsoft certificates can help you venture in this area with confidence. 

In A Nutshell

Amazon QuickSight and Microsoft Power BI have emerged as strong competitors in the world of data visualization and reporting. QuickSight excels at AWS integration, while Power BI excels at customization. It is essential to analyze performance, visualization capabilities, and scalability as per the project requirements. Your selection should be consistent with your setting, data complexity, and purpose. There are many Power BI like tools in the market similar to Quicksight that you can explore. Lastly, regardless of their differences, both tools empower users to transform raw data into valuable insights, and enable important stakeholders to take action at the right time.

Frequently Asked Questions (FAQs)

Depending on usage patterns, both QuickSight and Power BI offer cost-effective options to choose from. QuickSight's pay-per-session model is suitable for infrequent use, but Power BI's various pricing tiers cater to a wide range of demands.

Yes, both QuickSight and Power BI can connect to many different data sources, such as spreadsheets, databases, cloud-based services, and APIs, which makes them flexible for data integration and data analysis.

Power BI and AWS QuickSight are both user-friendly, with intuitive user interfaces for visualizing data. The choice is decided by familiarity with the Microsoft or AWS environments, and also by each user's convenience.

QuickSight and Power BI both possess great data visualization features, but Power BI's broad library and customization potential make it an excellent tool for those who require complicated and highly tailored visualizations. QuickSight has powerful AWS integration which means scalability is great.

Abhishek Venugopal

Hi, I am Abhishek. After graduating from IIT Madras, I joined Accenture AI as a data science analyst, where I worked for more than a year, before joining Swiggy (Instamart business) as a business analyst. I enjoy sharing knowledge and technical writing is one of my core areas of interest where I contribute to the community through Medium and KnowledgeHut Upgrad.

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Power BI vs Amazon QuickSight: 5 Key Areas Compared

• Business Intelligence

In this post, we compare two popular BI tools: Microsoft Power BI and Amazon QuickSight. We’ll discuss the key differences between the two platforms and give recommendations, including their data source compatibility, data visualizations, collaborations, pricing, and advanced features.

Both tools offer powerful data visualization and analysis capabilities, so it ultimately comes down to which one better fits your needs and budget.

In this post, we’ll compare Microsoft Power BI and Amazon QuickSight to help you choose the right tool.

Power BI vs Amazon QuickSight: Overview Comparison

What is microsoft power bi.

Microsoft Power BI is a business intelligence tool that helps you analyze and visualize your data in a user-friendly way. It lets you connect to different data sources, transform and clean the data, and create interactive dashboards, reports, and visualizations that you can share with others.

Image source: Microsoft Power BI

Real world examples of Power BI is for example, NBA team the Miami Heat use business intelligence to transform their customer interactions and business operations  or the Carnegie Mellon University use Power BI to optimize energy and operational efficiency in buildings

What is Amazon QuickSight?

Amazon QuickSight offers a range of features to help you analyze your data, including data preparation, data analysis, and data visualization tools . With QuickSight, you can easily connect to various data sources, create dashboards and reports, and share insights with others.

  Amazon QuickSight is a powerful tool for business intelligence professionals that offers a range of features to help you analyze and visualize your data. 

Image source: Amazon QuickSight

Business Intelligence tools are types of software used to gather, process, analyze, and visualize large volumes of past, current, and future data in order to generate actionable business insights, create interactive reports, and simplify the decision-making processes.

1. Power BI vs Amazon QuickSight: Data Sources and Connectivity

Data integration is the process of combining data from multiple sources , often with the help of a data warehouse , into one unified view, which enables users to analyze the data holistically. 

How does data integration work in Microsoft Power BI?

With Power BI, you can connect to various types of data sources, including Excel spreadsheets, cloud-based and on-premises data warehouses, and more. 

Once the data sources are connected, you can create visualizations that display the data in an interactive and immersive way. These visuals can be sliced, filtered, highlighted, and drilled into to explore the data in more detail

Image source: Microsoft Documentation Power BI

Data Source Types

Power BI can connect to a wide range of data sources, including spreadsheets, databases, and cloud-based systems. With Power BI, you can access data from various sources such as 

• Google Sheets
• And many more.. 

And cloud databases such as 

• Microsoft Azure
• Amazon Web Services (AWS)
• Google Cloud
• Several others ..

Additionally, Power BI can connect to a variety of popular database management systems like MySQL, Oracle, and SQL Server, as well as Hadoop and NoSQL databases like Apache Cassandra and MongoDB.

Power BI also supports direct connectivity to cloud-based data sources such as Salesforce and Google Analytics, making it easy to analyze data from various sources in one place.

For a complete view on data sources, see the Microsoft documentation on Power BI data sources

How does data integration work in Amazon QuickSight?

Amazon QuickSight offers native connectivity to a range of data sources, including AWS services, databases, and third-party applications. You can easily connect to your data and start analyzing it in minutes.

In Amazon QuickSight, data integration works by allowing you to connect to multiple data sources, such as Amazon S3, Redshift, and RDS databases, as well as third-party data sources like Salesforce and Google Analytics.

Once the data sources are connected, users can perform data transformations , such as filtering, merging, and aggregating , to prepare the data for analysis. Amazon QuickSight also provides a range of data preparation features , such as data profiling, data cleaning , and data modeling, which help users to identify and address any data quality issues before performing analysis.

Below is an example of a workflow in Quicksight. Notice the first step, connect your data

Image source: Amazon QuickSight Documentation

Amazon QuickSight can connect to many different types of data sources. This includes data sources such as databases (such as Amazon Redshift, MySQL, and PostgreSQL), cloud-based data sources (such as Amazon S3, Amazon Athena, and Salesforce), and even files (such as CSV, Excel, and JSON). 

QuickSight also has built-in connectors for certain popular services like Google Analytics and AWS services like Amazon Aurora and Amazon RDS.

Summary: Data Sources for Microsoft Power BI vs Amazon QuickSight

Recommendation: aws quicksight vs powre bi for data integration and sources.

Generally speaking, I would recommend Microsoft Power BI for data integration and sources. Power BI has a wide range of data connectors that make it easy to connect to various data sources, both cloud-based and on-premises. 

In addition, Power BI has robust ETL (extract, transform, load) capabilities, allowing you to manipulate and transform data before loading it into your visualizations. Power BI also provides data modeling features that enable users to create complex data models and relationships. 

These features make it easier to handle large volumes of data, reducing the time and effort required for data preparation.

Amazon QuickSight, on the other hand, has limited data connectors and is mostly geared towards cloud-based data sources. While it does provide ETL capabilities, they are not as robust as those of Power BI. 

QuickSight’s data modeling capabilities are also limited compared to Power BI, which may be a challenge for more complex data integration scenarios.

Overall, from my experience, Microsoft Power BI is the better choice for data integration and sources due to its wide range of connectors, robust ETL capabilities, and powerful data modeling features.

2. Power BI vs Amazon QuickSight: Data Visualization and Reporting

Data visualization is the graphical representation of information and data.

Like dashboards, data visualization is synonymous with business intelligence . Data visualization is the practice of representing information graphically to communicate and contextualize data. It highlights important changes, patterns and trends using a visual format, such as charts, graphs, maps and plots, to help make data easier to understand.

How is data visualization and reporting handled in Microsoft Power BI?

In Microsoft Power BI, data visualization and reporting is a key feature that allows users to create powerful visualizations and reports that can convey complex information in an easy-to-understand format. 

With Power BI, you can use charts, graphs, tables, and maps to display data and communicate insights. The platform also provides a range of tools and features to help you create interactive reports and dashboards that can be shared with others.

Additionally, the Power Bi has built-in AI-powered insights that can help you identify patterns and trends in your data, even if you don’t have any data science expertise.

Image source: Power BI

If you want to get some inspiration of amazing visualizations you can make with Power Bi, check out: Microsoft Power BI Community: Data Stories Gallery

How is data visualization and reporting handled in Amazon QuickSight?

QuickSight offers a range of visualization tools, including bar charts, line charts, scatter plots, pie charts, and tables, that allow users to create custom visualizations that best suit your needs. 

QuickSight also provides a range of reporting features, including the ability to create dashboards, which are interactive reports that display multiple visualizations in a single view, making it easier for users to compare and contrast data. 

Additionally, QuickSight allows users to share their visualizations and reports with others, either through email or by embedding them in other applications, so that everyone can have access to the same data-driven insights

Recommendation: Power BI vs AWS QuickSight for Data Visualization and Reporting

I would recommend Microsoft Power BI for data visualization and reporting. Power BI offers a wide range of features and tools to create interactive visualizations and reports, including custom visualizations and the ability to incorporate external data. 

It also has a user-friendly interface and a robust community of users and developers (https://community.powerbi.com/), which makes it easier to find support and resources. Additionally, Power BI integrates well with other Microsoft products like Excel and SharePoint. 

While Amazon QuickSight also has some powerful visualization and reporting capabilities, it is generally less feature-rich and more limited in its integrations compared to Power BI.

3. Power BI vs Amazon QuickSight: Machine Learning Capabilities and Integration

The use of business intelligence with machine learning can really help us make better and more efficient use of your data. By automating data processing and analysis , identifying patterns and trends, and predicting future outcomes, you can gain a competitive advantage with machine learning . 

How does machine learning work in Microsoft Power BI?

Power BI has built-in machine learning capabilities that allow users to create predictive models based on their data. These models can be used to forecast future trends, detect anomalies or outliers, and classify data into different categories. Power BI also has pre-built machine learning models that can be easily integrated into reports and dashboards.

To use machine learning in Power BI, users first need to connect their data sources and import the data into the tool. They can then use the built-in machine learning features to create models and analyze the data. 

Power BI also supports popular machine learning languages and frameworks such as Python and R, which can be used to create custom models and integrate them into Power BI reports.

Machine Learning in Power BI is something Microsoft is investing and focusing on so this offering will only get better and be a more and more natural part of the Power BI.

Below is an example of Purchase Intent Prediction model

Image source: Microsoft Power BI Learn

How does machine learning work in Amazon QuickSight?

Amazon QuickSight integrates with Amazon SageMaker to provide machine learning-powered insights. With SageMaker integration, you can easily build and deploy machine learning models to analyze your data and generate insights. 

Amazon QuickSight uses machine learning (ML) to help users make data-driven decisions . Specifically, it applies ML algorithms to large amounts of data to identify patterns, predict future outcomes, and recommend actions based on the data. 

This allows QuickSight users to go beyond basic descriptive and diagnostic analysis and move into forecasting and decision-making with confidence. QuickSight’s ML capabilities include natural language processing, anomaly detection, and forecasting, among others.

By leveraging machine learning, Amazon QuickSight makes it easier for users to understand their data and make more informed decisions.

Image source: Amazon Web Services (AWS) Machine Learning

Recommendation: Power BI vs AWS QuickSight for using Machine Learning in BI 

My recommendation for machine learning integration and tools would be Microsoft Power BI. Power BI has a more advanced machine learning integration than Amazon QuickSight, providing a wide range of machine learning algorithms and techniques for advanced analytics .

With Power BI, you can use Azure Machine Learning to create and train models that can be used within Power BI for data analysis and prediction. Power BI also offers advanced analytics features, including R and Python scripting, which allow for more complex data manipulation and analysis.

Overall, both Amazon Quicksight and Microsoft Power BI are great options for business intelligence with machine learning, but in my experience, Power BI offers more advanced features and a larger user community.

4. Power BI vs Amazon QuickSight: Collaboration and Sharing Capabilities

Simply put, how easy and supportive are the tools of collaboration and sharing dashboards, reports and projects with others . Data democratization , is the process of creating  a data-driven culture  where business intelligence data is accessible to all users within an organization, is one of our top trends in Business Intelligence .

How is collaboration in Microsoft Power BI?

Collaboration in Microsoft Power BI is made easy with the ability to work together in workspaces, share dashboards and reports with your team. 

As most have probably got familiar with Microsoft Teams, it is a collaboration tool that integrates well with Power BI and allows you to easily find data, use fully-featured experiences without leaving Teams, and bring data and insights into the collaboration platform. 

By sharing reports, dashboards, and scorecards from your workspace or another workspace, you can distribute the data to coworkers to help make informed business decisions

How is collaboration in Amazon QuickSight?

Amazon QuickSight offers collaboration and sharing capabilities to help you work with others. You can easily share your dashboards and reports with others, collaborate on projects, and provide access to your data.

Recommendation: AWS QuickSight vs Power BI for Collaboration and Sharing

Ultimately, it depends on the other tools you are using. If you are working extensively with the Microsoft offering, example Teams, then Power BI integrates very well and seamlessly with other Microsoft apps. 

On the other hand, if you are familiar with and using Amazon Web Service (AWS) apps, then QuickSight is easier to integrate into your current setup. 

But on a general note, I would recommend Microsoft Power BI over Amazon QuickSight for collaboration and sharing capabilities. One of Power BI strengths is its collaborative features, which enable you to work together in workspaces to create meaningful reports and dashboards. 

From my experience, collaboration in Power BI is easier and smoother than in QuickSight. Not that collaboration in QuickSIght is poor, it’s also good, it’s just that I think that Power BI is better in that area.  

5. Power BI vs Amazon QuickSight: Pricing

Depending on who you ask, perhaps the most important aspect – what is the cost of the business intelligence tool. 

What is the price of Microsoft Power BI?

There are three alternatives for Microsoft Power BI 

• Free (also called Power BI Desktop)
• Premium. 

Power BI has two main licensing options: Power BI Pro and Power BI Premium. Power BI Pro is priced per user, per month. The Power BI Premium option, however, not only has pricing per user per month, but also has a second pricing option called “per capacity”.

Image source: Microsoft Power BI Pricing

Power BI Free

Power BI Free (also known as Power BI Desktop) allows you to utilize the majority of the tools that Power BI Service provides. One of the biggest differences you’ll see when you look at Power BI Free vs Pro/Premium is that the Power BI Pro license really levels up the content sharing and collaboration options with other Power BI users

This means that creating data connections, transforming the data, and building dashboards and reports can now be a team effort.

Power BI Pro: $9.99 per user per month

The biggest difference between Free and Pro is that with Pro you can share your data, reports, and dashboards with other users who also have a Power BI Pro license. In addition, it allows connecting to numerous on-premises datasets and setting automatic refresh for these datasets.

Key differences between Pro and Free are: 

• Sharing and collaboration
• Improved data refreshes
• On-premise data gateways

I would say that if you want to share data, reports, and dashboards privately – you need to look at Power BI Pro. It allows you to share your data with individual coworkers or publish enterprise-wide “content packs” and “apps” with row-level data security

Power BI Premium: $20 per user per month

Power BI Premium includes all of the features available in Power BI Pro and offers a few additional features to users. Premium is targeted towards large enterprise deployments and workloads . 

Power BI Pro vs Premium 

What ultimately separates the Pro and Premium versions is performance and storage . From my experience and understanding, Pro is preferable for those who want to create and share their content internally while Premium is best for those who want to share their content externally from the organization

For instance, Power BI Premium (per user) license holders have the possibility to create paginated reports, a model size limit of 100 GB (versus 1 GB for Power BI Pro users), the ability to refresh datasets 48 times per day (versus 8 for Power BI Pro users, and access to some of the more advanced and technical features in Power BI. 

What is the price of Amazon QuickSight?

QuickSight is priced on a per-user basis and ranges from 

• Reader: $5 per month 
• Author: $28 per month

If a user goes a month without logging in, they pay nothing.

QuickSight Author is a user who can connect to data sources (within AWS or outside), create visuals and analyze data. Authors can create interactive dashboards using advanced QuickSight capabilities such as parameters and calculated fields, and publish dashboards with other users in the account

QuickSight Reader is a user who consumes interactive dashboards. Readers can only view reports and dashboard, not build and configure them. This means that readers can view shared dashboards, filter data, drill down to details or export data as a CSV file. 

Want to see how Amazon QuickSight compare to Tableau? See our comparison where we discuss the key differences between the two platforms and give recommendations, including their data source compatibility, data visualizations, collaborations, pricing, and advanced features.

Conclusion and Recommendation: Power BI vs QuickSight

In conclusion, both Microsoft Power BI and Amazon QuickSight are powerful business intelligence platforms with their own unique features and strengths. Power BI is a more mature platform with a wider range of features and integrations, while QuickSight is more affordable and offers better scalability for larger organizations.

Recommendation: QuickSight vs Power BI

When choosing between the two platforms, it’s important to consider your specific business needs, budget, and level of technical expertise. If you’re looking for advanced data visualization capabilities and are willing to invest in a more established platform, Power BI may be the better choice. On the other hand, if you’re a small to mid-sized business with limited resources and want a more cost-effective option that can scale with your needs, QuickSight may be the better option.

Overall, both platforms are great choices for businesses looking to improve their data analysis and reporting capabilities. By understanding the key differences between these two platforms, you can make an informed decision about which one is right for your business.

Definition of Business Intelligence

Business Intelligence (BI) is a technology-driven process of analyzing and visualizing data to extract valuable insights and inform decision-making. It involves the use of various tools and techniques to collect, store, and analyze data , and then presenting it in an easy-to-understand format.

The goal of BI is to provide organizations with the information they need to make informed decisions and drive business

Learn more about diffferent roles in Business Intelligence in our comprehensive guide to different roles in BI

FAQ: AWS QuickSight vs Power BI

What are the key differences between amazon quicksight and microsoft power bi.

Amazon QuickSight is a cloud-based BI platform that focuses on providing users with fast, interactive visualizations and data exploration capabilities. u003cbru003eu003cbru003eOn the other hand, Microsoft Power BI offers a more comprehensive solution that includes data preparation, modeling, visualization, and sharing. u003cbru003eu003cbru003ePower BI also integrates with other Microsoft products, such as Excel and SharePoint, making it a good fit for organizations already using the Microsoft ecosystem.

Which platform offers more advanced data visualization features?

Both platforms offer robust data visualization features, but Microsoft Power BI has a more extensive set of visualization options, including custom visuals created by the Power BI community. Power BI also offers more advanced data modeling and analysis capabilities.

How does the pricing of Power BI compare to Amazon QuickSight?

Power BI and QuickSight have different pricing models. QuickSight charges per user per month, with a separate cost for data access. u003cbru003eu003cbru003ePower BI, on the other hand, offers a range of pricing plans, including a free version, a per-user subscription, and an enterprise plan. The pricing for Power BI varies based on the number of users and the features required.

Can both Amazon QuickSight and Microsoft Power BI connect to the same data sources?

Both platforms can connect to a wide variety of data sources, including popular cloud-based solutions like Amazon Redshift, Google BigQuery, and Microsoft SQL Server. u003cbru003eu003cbru003eHowever, some sources may be better supported on one platform than the other, so it’s important to check the list of supported data sources before making a choice.

What kind of support and training resources are available for Microsoft Power BI and Amazon QuickSight?

Both platforms offer a range of support and training resources, including documentation, online forums, and video tutorials. Microsoft also provides paid support options for Power BI users. u003cbru003eu003cbru003eAdditionally, Power BI has a strong community of users who create and share custom visuals and other resources. QuickSight, on the other hand, has fewer community resources available but provides access to Amazon’s extensive support network.

Meet Eric, the data "guru" behind Datarundown. When he's not crunching numbers, you can find him running marathons, playing video games, and trying to win the Fantasy Premier League using his predictions model (not going so well).

Eric passionate about helping businesses make sense of their data and turning it into actionable insights. Follow along on Datarundown for all the latest insights and analysis from the data world.

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Lisa's journalism career spans two decades, and she currently serves as the Americas Day Editor for the Global News Desk. She played a pivotal role in tracking the COVID pandemic and leading initiatives in speed, headline writing and multimedia. She has worked closely with the finance and company news teams on major stories, such as the departures of Twitter CEO Jack Dorsey and Amazon’s Jeff Bezos and significant developments at Apple, Alphabet, Facebook and Tesla. Her dedication and hard work have been recognized with the 2010 Desk Editor of the Year award and a Journalist of the Year nomination in 2020. Lisa is passionate about visual and long-form storytelling. She holds a degree in both psychology and journalism from Penn State University.

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