Best 10 BI Platforms in 2023


Business intelligence (BI) platforms are software tools that collect, store, analyze and visualize data to uncover insights and drive better decision making. With data playing an increasingly critical role in organizations of all sizes, demand for robust and scalable BI platforms continues to grow.

According to MarketsandMarkets, the global BI platforms market size is projected to grow from $20.5 billion in 2020 to $33.3 billion by 2025 at a Compound Annual Growth Rate (CAGR) of 10.6% during the forecast period.

With so many options to choose from, selecting the right BI platform can be a daunting task. To help you make an informed decision, we have compiled this comprehensive guide to the top 10 BI platforms for 2023 with an in-depth comparison of their key features, pros and cons, pricing, and ideal use cases.

How to Choose a BI Platform

With so many BI platforms to evaluate, it can be challenging to determine which one best fits your needs. Here are some key criteria to guide your selection process:

Key Evaluation Criteria

User FriendlinessHow easy is the platform to use for users of all technical abilities? Look for intuitive visual interfaces.
Data VisualizationDoes the platform offer various visualization options (charts, graphs, gauges, etc.) to spot patterns and trends?
Data PreparationWhat data transformation and modeling capabilities does it have for preparing data for analysis?
Embedded Advanced AnalyticsDoes it offer built-in statistical, predictive, and machine learning capabilities for deeper insights?
CustomizationHow flexible is the platform for customizing dashboards, visualizations, and reports?
ScalabilityCan the platform handle large and complex data volumes as your needs grow? Evaluate technical architecture.
Cloud Platform SupportDoes the platform allow deploying analytics in the cloud? Evaluate integration with Azure, AWS, Google Cloud.
Mobile SupportAre there native mobile apps for data access and analytics on the go?
CollaborationDoes the platform enable collaboration through sharing reports, annotations, and comments?
SecurityWhat security, authentication, and access control features does it have to protect sensitive data?
PricingWhat is the pricing model – subscription, perpetual license, or consumption-based? Compare cost of licenses.
Customer SupportIs prompt technical support and troubleshooting assistance available when needed?

Top 10 BI Platforms for 2023

1. Tableau

Overview and Key Features

Tableau is one of the most widely used BI platforms globally, renowned for its strong visual analytics capabilities. The software makes it easy for anyone to produce rich interactive reports and dashboards with advanced analytics built-in.

Some key features include:

Drag and drop interfaceEnables business users to quickly analyze data using a simple drag and drop method to create charts, graphs, and dashboards.
Vibrant visualizationsOffers a wide variety of visualization options, including heat maps, plots, scatter plots, Gantt charts, and more.
Smart analyticsProvides smart analytical features like trendlines, forecasting, regression analysis, clustering, and distributions.
Natural language queriesAllows users to query data using conversational natural language.
Collaboration toolsSupports sharing insights online and offline through subscriptions, Slack integration, bookmarks, and comments.
Robust dashboardingEnables building highly interactive and web-based dashboards with advanced filtering, drilling, linking, and parameterization.
Augmented analyticsLeverages capabilities like natural language generation and insight suggestions to enhance analysis.
Enterprise scalabilityTableau Server scales to support large distributed deployments in on-premise, multi-cloud, or hybrid environments.

Pros and Cons

Extremely intuitive and user friendly interface
Limited data preparation and modeling capabilities
Powerful and beautiful data visualizationsAdvanced users may find it constraining
Smart analytics built-in for deeper insightsCan experience slow performance with large complex data
Collaborative dashboarding capabilitiesSteep learning curve for coding custom visuals
Broad product ecosystem and large community


Tableau offers subscription-based pricing that varies based on product edition and deployment size:

PlanPriceUser Limit
Tableau Creator$12 per user/monthUnlimited (Cloud Only)
Tableau Explorer$35 per user/monthUp to 100 users
Tableau ViewerFreeRead-only access
Tableau Server$35 – $70 per user/monthUnlimited

They offer a free trial to evaluate the product. Discounted pricing is available for academic institutions and non-profits.

Use Cases

With its self-service model and rich visualizations, Tableau is a great fit for:

Use CaseDescription
Business AnalyticsEnables different departments (sales, marketing, operations, etc.) to analyze data and create relevant dashboards.
Interactive ReportingCreates visually interactive reports, allowing business users to independently explore and analyze data.
Data DiscoveryEmpowers users to quickly explore various data sources, ask questions, and uncover valuable insights.
Embedded AnalyticsIntegrates analytics into internal and external applications using Tableau’s REST APIs.

2. Power BI

Overview and Key Features

Power BI is Microsoft’s rapidly growing cloud-based business intelligence service integrated with the Office 365 ecosystem. It offers intuitive self-service BI capabilities for data discovery, visualization and dashboarding.

Key features of Power BI include:

Interactive ReportsEmpowers business users to analyze data and create dynamic, interactive reports with integrated AI features.
DashboardingCompiles reports into flexible dashboards with filtering options, enabling drill-down and drill-through.
Natural Language QueriesAllows users to explore data using conversational natural language queries, enhancing data exploration.
AI VisualizationsAutomatically generates graphs and visuals through data analysis, providing insights in a visual format.
Predictive AnalyticsOffers machine learning capabilities for tasks like forecasting, predictions, sentiment analysis, and more.
Mobile AppsProvides secure native mobile apps for iOS and Android, enabling access to analytics while on the move.
Data ConnectivitySupports connections to 100+ data sources, including Excel, Salesforce, Azure data services, and Facebook.
Enterprise ScalabilityScales to accommodate large enterprises via XMLA endpoints and dataset aggregation in Premium capacity.

Pros and Cons

Tight integration with Microsoft data platformLimited advanced analytics functions compared to tools like R and Python
Familiar Excel-like interface for business usersDashboards can be complex to build
Auto AI for quick insights and smartsOn-premise gateway required for some data sources
Built-in natural language queriesLimited community and partner resources
Cost effective licensing model


Power BI is priced based on a monthly or annual subscription model:

Power BI Pro$9.99 per user/month (annual plan)
Power BI Premium$4,995 per dedicated cloud compute resource/month
Power BI EmbeddedPay per session based consumption pricing

Free desktop trial is available. Academic pricing offers a 60% discount.

Use Cases

Power BI is ideal for:

Use caseDescription
Self-service AnalyticsEmpowering individual business units to independently analyze data and uncover insights.
Interactive ReportingDesigning visually engaging and interactive reports to facilitate data analysis.
Dashboard ConsolidationCreating executive dashboards by aggregating essential reports into a unified view.
Embedded AnalyticsCustomizing Power BI for embedding into internal applications, providing end-user analytics.

3. Qlik Sense

Overview and Key Features

Qlik Sense is an end-to-end modern BI platform built around interactive data visualization, analytics and dashboards. It differentiates itself through its associative analytics engine and cognitive capabilities.

Some key capabilities include:

Associative AnalyticsPermits users to explore data freely and establish associations across multiple datasets.
Conversational BIAllows users to ask questions using natural language via Qlik Insight Bot and receive automated answers.
Smart VisualizationsAugmented intelligence suggests relevant graphs while users analyze data.
Geo-analyticsEnables location-based analysis through mapping, filtering, and grouping data by region.
MobilityOffers responsive analytics apps accessible on any device.
Big Data IntegrationProvides native connectivity to various data sources across cloud, on-premise, and hybrid environments.
Enterprise ScalabilityQlik Sense Enterprise SaaS delivers governed self-service analytics with full enterprise capabilities.

Pros and Cons

Speed of analysis through associative modelShort learning curve to grasp associative model
Conversation and insight bots for natural interactionLimited advanced analytics functions compared to R and Python
Smart visual suggestions accelerate analysisHave to build complex visuals outside using D3, WebGL
Data storytelling constructs narrative flow in analysisMore suited for data exploration than dashboards
Platform built for broad data access and scalability


Qlik Sense is licensed based on two subscription models:

Qlik Sense Business$15 per user/month billed annually
Qlik Sense Enterprise SaaSStarts at $10 per user/month (500 user minimum)

Free trials are available on the cloud. Discounted pricing for academic and non-profit use.

Use Cases

Qlik Sense is a great fit for:

Use CaseDescription
Guided Analytics AppsDeveloping curated analytics apps with guided stories and narratives tailored to specific business needs.
Self-service ExplorationEmpowering business users with interactive data exploration capabilities across various data sets.
Embedded AnalyticsProviding the ability to white-label and embed analytics within applications for partners and customers.
Geospatial AnalyticsMapping, filtering, and analyzing regional trends through built-in geo-analytics features.

4. Looker

Overview and Key Features

Looker provides a modern business intelligence platform optimized for cloud applications and designed for sophisticated analytics users.

Some key capabilities include:

Browser-based AnalyticsDelivers analytics and insights via the web browser, visualizing data in reports and dashboards.
LookML Modeling LanguageEnables analysts to integrate data sources, create semantic layers for SQL queries and visualizations.
Embedded AnalyticsAllows partners to embed interactive analytics within their applications through Looker’s APIs and SDKs.
Predictive AnalyticsUtilizes Looker’s analytics functions (time series, clustering, anomalies) to uncover predictive insights.
Flexible DeploymentSupports multi-cloud, hybrid, and on-premise deployments on AWS, GCP, Azure, and private cloud.
Governance and SecurityProvides enterprise-grade security, access control, activity audit, and governance workflows.

Pros and Cons

Powerful LookML modeling language for analystsSteep learning curve for non-technical users
Sophisticated analytics functions for data expertsAdvanced dashboard customization requires coding
Built for operationalization and embeddingDoesn’t integrate easily with on-premise data sources
Integrates natively with modern cloud data stacksSmaller ecosystem of partners and extensions
Flexible multi-cloud deployment options


Looker offers a subscription model priced based on the size of deployment:

PlanBase PriceAdditional User Price
Looker Core$3000/month$120 per user/month
Looker Standard$5000/month$150 per user/month
Looker Enterprise$9000/month$180 per user/month

Volume discounts available along with discounted pricing for non-profits and startups.

Use Cases

Looker is a great choice for:

Use CaseDescription
Embedded AnalyticsOffers customizable analytics experiences embedded within web and mobile applications.
Sophisticated AnalyticsEmpowers expert data analysts to create semantic models and derive insights from complex data.
Fully Cloud-based AnalyticsProvides analytics optimized for cloud data platforms such as Snowflake, BigQuery, Redshift, and more.
Data-driven WorkflowsEnables the triggering of actions and workflows based on analytics insights and scheduled data monitoring.

5. ThoughtSpot

Overview and Key Features

ThoughtSpot provides an enterprise-focused modern BI platform delivering search and AI-driven analytics across cloud, hybrid and on-premise environments.

Key features include:

Search-driven AnalyticsUsers can query data in natural language similar to Google-like search.
Augmented AnalyticsThoughtSpot automatically generates relevant charts, insights, trends, and predictions.
Conversational AnalyticsEnables asking follow-up questions and filtering data through conversations.
Column-level SecurityProvides enterprise-grade security for sensitive data at both row and column levels.
Embed AnalyticsOffers embedding capabilities to integrate analytics into internal applications.
Cloud ScaleWorks across major cloud data platforms including Snowflake, Azure Synapse, and Databricks.
SpotAppsPrebuilt analytics apps allow customized deployments for specific industry use cases.

Pros and Cons

Ask data questions conversationally in plain languageAnalytics workflows require learning proprietary language
AI-driven analytics and natural language capabilitiesCustom visuals need to be built outside platform
Unified analytics across cloud, on-premise and hybridSmaller developer ecosystem than leaders
Prebuilt SpotApps for accelerated deploymentLimited advanced statistical analysis functions
Enterprise-grade governance and security


ThoughtSpot pricing is based on annual subscriptions tiered by features:

PlanStarting Price
Search & AnalyzeStarts at $25,000/year
Build Your OwnStarts at $75,000/year
Embedded AnalyticsCustom pricing

Free trial available on cloud environment. Discounted pricing offered for non-profits.

Use Cases

ThoughtSpot is a great fit for:

Use CaseDescription
Conversational AnalyticsAllows business users to explore data and find insights through conversation using search.
Guided AnalyticsInvolves creating interactive dashboards with guided walkthroughs of data analysis workflows.
Embedded AnalyticsProvides partners and customers with capabilities for embedded analytics.
Cloud AnalyticsSuits organizations looking to standardize on cloud data platforms like Snowflake, Databricks, etc.

6. Sisense

Overview and Key Features

Sisense provides a scalable BI solution to build and embed interactive dashboards across a hybrid, multi-cloud data landscape.

Some of its key capabilities are:

Unified Data ModelAutomatically merges disparate data sources into a single data model for analysis.
Customizable DashboardsEnables highly customizable and interactive dashboards through drag-and-drop development.
AI-assisted AnalyticsProvides AI-driven insights, anomaly detection, and forecasting for enhanced analysis.
Broad Data ConnectivityConnectors support a wide array of data sources including cloud apps, databases, APIs, and files.
Embedded AnalyticsOffers white-label embedding, theming, and APIs to seamlessly integrate analytics into applications.
Hybrid and Multi-cloud SupportFacilitates deployment across hybrid and multi-cloud environments.

Pros and Cons

Unified data models across disparate sourcesSteep learning curve for new users
Highly customizable and interactive dashboardsAdvanced coding needed for custom visuals
Broad data connectors and hybrid cloud supportLess focus on end user self-service
Embedding analytics capabilitiesSmaller partner and extension ecosystem
Optimized for large and complex datasets


Sisense offers two main subscription packages:

PlanPriceMinimum Users
Explorer$960 per user/yearMinimum 5 users
Designer$2,500 per user/yearMinimum 3 users

It provides a free trial to test out the platform. Discounted pricing is offered for non-profits and educational institutions.

Use Cases

Sisense is a great choice for:

Use CaseDescription
Embedded AnalyticsWhite labeling analytics for embedding in internal apps or partner products.
Multi-cloud AnalyticsUnifying analytics across complex hybrid, multi-cloud environments.
Customizable DashboardsBuilding highly interactive pixel-perfect custom dashboards.
Large Dataset AnalysisOptimized to handle large high-cardinality datasets.

7. Domo

Overview and Key Features

Domo provides a business optimization platform with embedded BI, data management and app development capabilities. It enables real-time analytics across the entire business.

Key capabilities include:

Interactive DashboardsDrag-and-drop interface for easy creation and customization of dashboards.
Data AppsCreate interactive data apps and analyze data collaboratively.
Mobile OptimizationDomo is mobile-optimized with native apps for iOS and Android.
AI AssistantMr. Roboto analyzes data and provides predictions and recommendations.
Embedded BIOffers robust APIs and SDKs for embedding and white-labeling analytics.
Transactional ConnectionsIntegrates transactional data sources like payments, POS, ecommerce, etc.
Prebuilt ConnectorsHundreds of connectors available for cloud apps, databases, files, social media, and more.

Pros and Cons

All-in-one platform beyond just BI analyticsLimited advanced statistical analysis functions
Mobile-first design optimized for execsSteep learning curve for some users
Hundreds of prebuilt connectorsCustom visuals require development skills
Strong embedded analytics capabilitiesSmaller ecosystem than leaders like Tableau
Integrates transactional data sources


Domo pricing is based on an annual subscription model:

PlanPriceMinimum Users
Business$83 per user/monthMinimum 25 users
EnterpriseCustom pricing

Free trial available on cloud. Discounted pricing for non-profits and education.

Use Cases

Domo works well for:

Use CaseDescription
Mobile-first AnalyticsFocusing on delivering analytics for executive mobile devices.
Embedded AnalyticsOffering partners and developers APIs to integrate analytics.
IoT and Streaming DataIngesting and analyzing real-time IoT and streaming data feeds.
Transactional Data AnalyticsConnecting and analyzing transactional data like POS, payments, ecommerce data.

8. Yellowfin

Overview and Key Features

Yellowfin is a flexible, integrated BI platform renowned for collaboration, automated analysis and data storytelling capabilities.

Key features include:

Data StorytellingInteractive slideshows guide users through data narratives and analysis.
CollaborationEnables annotation, commenting, and sharing of reports and dashboards.
Auto AnalysisAutomated insights customize analysis and suggest charts for specific data sets.
Data PreparationOffers tools for data profiling, cleansing, enrichment, and transformation.
Embedded BIProvides APIs, JS frameworks, and plugins to embed BI content.
Mobile OptimizationNative iOS and Android apps for full mobile optimization.

Pros and Cons

Automated data analysis and insightsComplex UI can have learning curve
Strong focus on data storytellingLimited advanced coding for customization
Interactive collaboration capabilitiesSmaller analyst and developer community
Packaged for fast time to insightLight on some enterprise-grade features
Broad device and environment support


Yellowfin offers value-based pricing packages:

Starter$600/month5 users1 admin
Standard$1,200/month10 users1 admin
Premium$2,400/month25 users2 admins

Free one month trials are available for cloud. Academic pricing offers a 75% discount.

Use Cases

Yellowfin works well for:

Use CaseDescription
Interactive Data StorytellingCreating guided narratives and storyboards for engaging data analysis.
Collaborative AnalyticsFacilitating insight sharing, commenting, and discussions among users.
Quick DeploymentUtilizing prebuilt connectors to swiftly deploy dashboards.
Embedded AnalyticsOffering partners APIs and iframes for embedding content into applications.

9. Zoho Analytics

Overview and Key Features

Zoho Analytics is an end-to-end BI and analytics platform optimized for business users. It focuses on easy visual data exploration augmented by AI.

Some key features:

Interactive DashboardsEnables intuitive dashboard creation using drag-and-drop and guided workflows.
Conversational AIUtilizes Zia, Zoho’s conversational AI, to ask natural language questions.
Enterprise ScalabilityHandles large data volumes and user loads with an in-memory analytics engine.
Embedded AnalyticsProvides capabilities to embed reports and dashboards into other applications.
Mobile AccessOffers native apps for full mobile optimization across various devices.
Broad Data ConnectivityIntegrates data from databases, files, applications, and cloud services.

Pros and Cons

Conversation AI and natural language searchStandard charts and visualizations
Guided dashboard creation workflowsLimited advanced statistical capabilities
Packaged for fast time to insightStill maturing platform with some gaps
Part of broader Zoho One platformSmaller partner and extension ecosystem
Cost effective pricing model


Zoho Analytics offers a simple annual subscription model priced per user:

Standard$30 per user/year
Professional$60 per user/year

They provide free trials for evaluation. It is also included in the Zoho One platform bundle.

Use Cases

Zoho Analytics works well for:

Use CaseDescription
Self-service AnalyticsFacilitating intuitive visual data analysis by business users.
Guided DashboardsCreating interactive dashboards with guided workflows.
Conversational AnalyticsExploring data through natural language conversations.
Embedded AnalyticsWhite labeling and integrating analytics into business applications.

10. Databricks Unified Analytics Platform

Overview and Key Features

Databricks Unified Analytics combines data engineering, business intelligence and machine learning on an open lakehouse architecture powered by Delta Lake.

Key capabilities include:

Unified SQL AnalyticsProvides unified analytics on Delta Lake using ANSI SQL, optimization, and BI integrations.
Business Intelligence ConnectorsComes pre-integrated with BI tools like Tableau, Power BI, and Looker.
ML-powered InsightsCombines SQL analytics with Python ML frameworks to provide ML-powered insights.
Low-code Visual AuthoringSimplifies dashboard creation without coding using SQL-based workflows and visual interface.
Open and ExtensibleIntegrates data science libraries, visualization tools, and notebooks.
Enterprise-scaleLeverages cloud scale and open formats for petabyte-scale analytics.

Pros and Cons

Unified SQL, BI and ML on Delta LakeSteep learning curve without SQL knowledge
ANSI SQL support avoids coding for analysisLimited advanced coding customizations
Scalable to petabyte-sized datasetsLock-in to Databricks ecosystem
Integrated with leading BI and ML toolsCosts can be complex to estimate
Common metadata across analytics and MLNot optimized for embedded analytics


Databricks pricing is based on cloud compute usage:

Standard$0.08 per DBU hour
Premium$0.192 per DBU hour

Discounted rates for annual contracts. Free Community Edition available.

Use Cases

Databricks works well for:

Use CaseDescription
Unified SQL, ML and BIProvides an end-to-end platform for data engineering, ML, and BI.
Petabyte-scale AnalyticsEnables running complex analytics at a massive scale.
ML-powered AnalyticsCombines traditional BI with predictive analytics using Python and R.
Lakehouse ArchitectureBuilds analytics on open Delta Lake for reliability, performance, and governance.

Choosing the Right BI Platform: Key Factors to Consider

With the wide variety of leading BI platforms profiled above, selecting the right option for your needs depends on several factors:

User Skill SetsEvaluate the technical abilities of users, ranging from self-service to expert orientation.
Available Data SourcesAssess the need to connect to existing on-premise and cloud data environments.
Analytics PrioritiesDetermine the types of analysis that are important, including self-service, dashboards, ML, etc.
Budget ConstraintsCompare license costs, discounts, and “value” across different price tiers.
Cloud StrategyAssess the plans for migrating analytics capabilities to the cloud, if applicable.
Embedded Analytics NeedsConsider whether robust APIs are provided for embedding analytics into applications.
Timeline ConstraintsFactor in the timeline for delivering analytics needs, including POCs and trials.

Focus on platforms that align best to your key requirements with flexibility to adapt as needs evolve. Leading options have strengths across core capabilities but optimize differently.


In closing, selecting the right business intelligence platform involves aligning key organizational requirements around user skills, analytics needs, existing infrastructure, budgets and timelines with leading solution capabilities.

Modern BI platforms profiled here like Tableau, Power BI, Looker and ThoughtSpot excel at areas like interactive visualization, natural language analytics, search-driven insights and embedded analytics. Legacy BI leaders like MicroStrategy and IBM Cognos lead on governed enterprise analytics, custom dashboards and advanced capabilities.

With data significance growing across roles and applications, investing in a contemporary BI platform tailored to your needs can help unlock the full value of data and drive competitive advantage. Reach out for guidance finding the right fit.