QuickSight vs Sisense For Cloud Data Teams

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Our analysts compared QuickSight vs Sisense For Cloud Data Teams based on data from our 400+ point analysis of Business Intelligence Tools, user reviews and our own crowdsourced data from our free software selection platform.

QuickSight Software Tool
Sisense For Cloud Data Teams Software Tool

Product Basics

Amazon QuickSight is a business intelligence tool that enables organizations to visualize and analyze data, derive insights, and make informed decisions. It empowers users with interactive dashboards, data exploration capabilities, and machine learning-driven insights, making it an ideal solution for businesses seeking to leverage data for better outcomes.

The benefits of Amazon QuickSight include its ease of use, fast performance, and scalability to handle large datasets. Its popular features include natural language querying, automated insights generation, and integration with other AWS services. Compared to similar products, Amazon QuickSight stands out for its affordability, ease of deployment, and robust feature set.

Pricing for Amazon QuickSight is based on a per-user, per-month subscription model. It offers flexible pricing options to accommodate varying business needs, ensuring cost-effectiveness and scalability as organizations grow.

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Formerly known as Periscope Data, Sisense for Cloud Data Teams is a data analytics software tool that integrates seamlessly with the Sisense platform, offering advanced analytics that delivers actionable insights to teams that work with data in the cloud. It provides a single, cohesive interface for users to store, organize, analyze and visualize all their data for better decision-making. It empowers users of all kinds to produce, consume and share insights intuitively together, with or without coding knowledge.

Originally founded in 2012 in San Francisco, California, it was acquired by Sisense in May 2019 and rebranded in January 2020.
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Product Insights

  • Self-Service BI: Get answers to questions and share insights independently through self-service analysis of business data. Connect to data sources, manipulate values to create visualizations, invite others to collaborate and share dashboards and reports — all without the need to install any application. 
  • Multi-Tenancy: Its multi-tenant architecture with namespaces allows vendors to provide data exploration and dashboarding capabilities for multiple applications at the same time. Host multiple clients and add templates created and shared by dashboard authors to the proprietary visualizations library. 
  • Embedded Analytics: Embed dashboard sessions into proprietary software to enhance business with console analytics. Personalize the appearance of visualizations and reports by adding custom fonts, colors and styles. Set defaults and error handling to match the host application for a cohesive feel. 
  • Report Sharing: Stay informed as to how key metrics are performing by scheduling automatic email updates. Ensure secure access to dashboards and email reports by showing only relevant data through targeted reports. 
  • Flexible Pricing: Save on upfront costs and capacity planning through its p    ay-as-you-go pricing model for report consumers — people who view dashboards, but don’t create them. 
  • Mobility: Get data insight and forecasting summaries on-the-go through its mobile version, available on both iOS and Android. Drill down into mobile-optimized dashboards and reports for in-depth analysis and filter to view specific metrics, even when away from the office. Share results with others and get email alerts for changes in business data as they happen. 
  • Automate Deployments: Deploy applications at scale, keeping them online for continued access while minimizing downtime. AWS CodeDeploy provides automated app deployments to multiple cloud compute services, such as Amazon EC2, AWS Fargate, AWS Lambda, and on-premise servers. Seamlessly integrates with continuous delivery process pipelines, such as AWS CodePipeline, GitHub and Jenkins. 
  • Promote Data Literacy: Identify key metrics, perform what-if analysis through simple point-and-click actions, discover hidden trends and generate forecasts — without needing any technical skills. Generates dashboard summaries in easy-to-understand language to enable shared understanding of data insights. 
  • Scalable: Its serverless architecture makes it easily scalable, ensuring fast loading of dashboards even during peak traffic. Scales as the organization grows to take on larger loads — no need to set up dedicated servers. 
  • Data Security: Its Enterprise version provides additional security features through permissions-based access to AWS data, row level security, SSO and data encryption. It is FedRamp, HIPAA, PCI PSS, ISO and SOC compliant, keeping with industry best practices. 
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  • Transforms Data Fast: Perform timely data querying and large-scale data ingestion for any volume of workload, through the analytics warehouse integration. Plug the data engine directly into cloud databases and optimize raw data by bypassing steps of the ETL process. Enable hassle-free data import via proprietary data caching technology
  • Centralized Data Warehouse: Creates a single source of truth by ingesting and storing data where it’s analyzed, speeding up analytics processes.
  • Ease of Use: Explore data and visualize trends through simple search query language, rather than via coding or modeling, making it an accessible solution for users of all technical skill levels.
  • Stats at a Glance: Understand and parse the results of data queries through Summary Statistics, without needing to write more SQL while exploring data and building models.
  • Reusable Analysis: Save time by storing frequently used in-house codes for swift collaboration without needing to start new queries from scratch.
  • Collaborative Insights: Enable collaboration between analysts and decision-makers through programming and self-service analytics combined. Hand off data analysis between teams, then publish and share insights with others via direct linking, password-protected links, email or Slack.
  • Self-Service BI: Pinpoint important data points in minutes, with reusable formulas and ad hoc analysis modeling that query data and return answers in real time.
  • R, Python and SQL On One Platform: Develop more advanced analytics processes with any programming language, with support for SQL, Python and R all in the same environment. Integrate open-source programming and formulas from other packages or libraries.
  • Scalability: Incorporate more complex datasets, higher volumes of data, more users and more, as the solution grows with the company.
  • Security: Have confidence in data security, with a cloud security infrastructure that upholds industry wide best practices and standards. Encrypt all traffic between users’ web browsers and Sisense’s servers, and for additional user-level security, manage data permissions, TFA and single sign-on functionality.
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  • Data Connectivity: Connect to a multitude of cloud-based and on-premise data sources such as Salesforce, JIRA, Github, Teradata, MySQL, SQL Server, Postgres and many more, or upload data from Excel, JSON, CSV and Presto files. 
  • Integrations: Perform predictive data analysis by integrating Amazon Sagemaker ML-based data models with its supported data sources, such as S3, Athena, Redshift, as well as third party sources that include Salesforce and JIRA, among others. Easily integrates with BI tools such as Domo and Tableau for data querying through an intuitively similar SQL interface. 
  • Data Visualization: Create interactive visualizations and reports by choosing from a rich library of graphs, charts and tables. Build dynamic dashboards by interacting with data in real time through drag-and-drop, drill-down and filtering options. 
  • Reporting: Its Enterprise edition provides ad-hoc as well as scheduled reporting to share targeted reports on a daily, weekly or monthly basis. Subscribe to receive reports via email. Creates a custom snapshot of the report based on individual data permissions. 
  • In-Memory Engine: Perform calculations and analyses at the speed of thought by querying through its super-fast parallel in-memory calculation engine, SPICE. Built from the ground up, it prepares data faster by replicating it in memory and updates in real-time as the underlying data changes. 
  • Dashboards: Create data dashboards with 28 supported charts, such as filled maps, histograms, funnel charts, stacked area charts, waterfall charts and boxplots, as well as tables and pivot tables. View information based on business context by sorting on fields not shown in the visualization. Provide report readers with on-sheet controls to slice and dice data by filtering on fields. Offers multiple report layout customization options that include adding drop-downs with single-select or multi-select sorting. 
  • ML-Based Insight: Get in-depth data insights through its out-of-the-box ML and NLP capabilities. Perform queries on data in seconds in simple language through its natural language attribute, Q. It learns from data patterns to provide accurate predictions based on historical trends. Detect anomalies and variations in data aggregates through scheduled anomaly detection. 
  • Localization: Available as a global solution with support for 10 major languages: English, German, Spanish, French, Italian, Portuguese, Japanese, Korean, Simplified Chinese, and Traditional Chinese. 
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  • Native Data Connectors: Blend data together into a single accessible database via an ecosystem of native data connectors and ETL partners.
  • Cloud Data Pipelines: Control when and how often data is refreshed and what the flow of information looks like. Gain visibility and control over data pipelines with a flexible, low maintenance solution.
  • Data Discovery: Directly access CSVs and data sets curated by analysts and interact with these insights through a drag-and-drop interface that does not require fluency in SQL. 
  • Git Integration: Grant developers complete control over their analytics environment through Git integration, sophisticated version control, release management workflows as well as file-level access to all user-generated content, like reports. Create, edit, sync and delete all settings through Git. 
  • Model-as-You-Go: Perform ad-hoc analysis to answer crucial questions at the click of a button by generating custom, on-the-fly data models.
  • Data Visualization: Create and share advanced, highly customizable data visualizations, including scatter plots, bar charts, bubble charts, bullet charts, funnel charts, waterfall charts, control charts, Gantt charts, radial bar charts and more.
  • SQL Editor Tools: Shorten the amount of time necessary to go from query to answer with powerful SQL writing tools, such as query revision history, views, filters, autocomplete suggestions, formatting and more. 
  • Learn SQL: Experiment with SQL programming language and data querying via drag-and-drop fields and see how the results change. Encourage users who aren’t fluent in SQL to become more familiar with it.
  • Code Library: Reduce repetitive data entry tasks and save time for subsequent report generation. Store frequently used code in a common library via Snippets for easy access later. 
  • Spaces: Manage data-level permissions to gate and restrict access to sensitive data and customize dashboards on a per-organization basis.
  • Share and Embed: Share dashboards via password-protection enabled public URLs or embedding inside other web applications or web portals. Download dashboards as static PDF images for uses such as email distribution.
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Product Ranking

#80

among all
Business Intelligence Tools

#16

among all
Business Intelligence Tools

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Analyst Rating Summary

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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

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Sisense For Cloud Data Teams
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Advanced Analytics Augmented Analytics Data Management Data Pre-processing Data Transformation Data Visualization Embedded Analytics Capabilities Geospatial Visualizations And Analysis Mobile Capabilities Platform Capabilities Reporting 75 54 100 95 90 99 86 73 79 83 88 0 25 50 75 100
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

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User Sentiment Summary

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Great User Sentiment 140 reviews
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87%
of users recommend this product

Sisense For Cloud Data Teams has a 'great' User Satisfaction Rating of 87% when considering 140 user reviews from 4 recognized software review sites.

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4.5 (72)
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4.3 (33)
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4.8 (4)
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4.1 (31)

Synopsis of User Ratings and Reviews

Self-Service Analytics: QuickSight empowers business users to create and customize visualizations, dashboards, and reports without relying on IT or data scientists.
Cloud-Based Platform: QuickSight's cloud-based architecture eliminates the need for costly on-premise infrastructure and provides seamless access from anywhere with an internet connection.
Scalability and Performance: QuickSight handles large datasets efficiently, allowing users to analyze vast amounts of data in real-time.
Easy Integration: QuickSight seamlessly integrates with popular data sources, including Amazon Redshift, Amazon Aurora, and Salesforce, enabling users to access and analyze data from various systems.
Machine Learning Capabilities: QuickSight leverages machine learning algorithms to provide predictive analytics, anomaly detection, and automated insights, empowering users to uncover hidden patterns and make data-driven decisions.
Collaboration and Sharing: QuickSight facilitates collaboration among teams by allowing users to share dashboards, reports, and insights securely.
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Data Querying: Almost 77% of users who mentioned data querying and data modeling said that this solution allows them to perform data queries of almost any kind.
Data Visualization: Of the users who mentioned data visualization, about 75% said that this tool excels at creating easily understandable graphics and visuals.
Sharing and Collaboration: Approximately 88% of users who mentioned this feature said that this solution facilitates strong collaboration on data analysis internally, while allowing for easy external sharing.
Implementation: In reference to setting up the platform, about 90% of users said that the process was smooth and quick.
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Pricing Structure: Complicated pricing model that can lead to unexpected costs for advanced features and usage.
Limited Customization: Pre-built dashboards and visualizations may not fully meet specific business requirements, limiting customization options.
Data Connectivity: May not seamlessly integrate with all data sources, requiring additional effort for data preparation and ingestion.
Limited Advanced Analytics: Lacks certain advanced analytical capabilities, such as predictive modeling and machine learning algorithms, which may be essential for deeper insights.
User Interface: Some users find the user interface to be cluttered and not as intuitive as other BI tools, impacting the ease of use.
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Reliance on SQL: While it excels in data querying, around 78% of users said that SQL knowledge is necessary to use this platform.
Self-Service Analytics: About 80% of users reviewing this feature said that data analysis is not truly self-service, requiring the involvement of a hands-on IT or analyst team.
Cost: Of the users who reviewed the cost of this tool, almost 86% of them found it too expensive, especially for smaller companies.
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Amazon QuickSight has received positive user reviews for its ease of use, intuitive interface, and quick data visualization capabilities. Users find it simple to connect to data sources, create dashboards, and generate insights. The drag-and-drop functionality and pre-built templates make it accessible to users of all technical skill levels. QuickSight's strengths include its integration with other Amazon Web Services (AWS) products, such as Amazon Redshift and Amazon S3, allowing for seamless data analysis. It also offers advanced features like machine learning-powered insights and natural language querying, providing users with deeper analytical capabilities. Compared to similar products, QuickSight is praised for its cost-effectiveness and scalability. Users appreciate its pay-as-you-go pricing model and the ability to handle large datasets without performance issues. However, some users have expressed concerns about the limited customization options and the lack of certain advanced features found in competing products. Overall, Amazon QuickSight is well-suited for businesses and organizations looking for an easy-to-use and affordable business intelligence solution. Its intuitive interface, integration with AWS products, and scalability make it a valuable tool for data visualization, analysis, and decision-making.

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Sisense for Cloud Data Teams is a powerful BI tool that excels in the hands of data analysts with coding knowledge. These analysts will be able to model, manage, prepare, manipulate and analyze data with ease. As the platform supports SQL, Python and R programming languages, the sky's the limit when it comes to extensibility, development and coding support. The platform allows for strong collaboration within an organization, designed to alleviate the time-consuming burden of reporting and data visualization on IT teams while allowing business users to access insights on their own time. Most of the features are built around making the analytics team’s job easier, with reusable code, built-in collaboration and more. The support team earned universal praise from users who contacted them, citing their swift, in-depth and informative answers as immensely helpful in resolving any issues they had with the solution. In addition to hands-on support, a speedy implementation process ensures that customers can get the platform up and running in no time. We found that users’ opinions of the platform’s functionality and ease of use differed significantly based on their own roles; analysts generally praised its robust data visualization and data querying features, while decision-makers often found it hard to use, due to the SQL language barrier. SQL is necessary for most functions, and even though there is a visual query editor that attempts to make SQL more accessible, some users said that the platform doesn’t do enough in this regard. Overall, users did agree that the tool makes it easy to collaborate with each other to bridge that gap, with most of the analytics being done on the technical end, letting business users simply access those results. Still, it’s difficult to accurately call Sisense for Cloud Data Teams a self-service analytics tool, as it requires an IT or analyst team’s involvement to truly shine. Additionally, the cost can be prohibitive to smaller businesses. Overall, Sisense for Cloud Data Teams can be extremely powerful in the right hands - for those who know SQL and how to use it, it’s a dream for querying data and delivering analytics, but for those who don’t have the necessary IT resources, it could prove difficult to fully maximize the value of this data solution.

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