For this review, I took each platform (except Oracle — there’s not a trial) for a test drive after poring through the vendor documentation and tutorial videos for hours. Additionally, I relied on product research from our JumpStart Platform which includes functional and technical requirements, and implementation and vendor qualification criteria. Let’s dive in.
- Strategy One: Best Overall
- Oracle Analytics Cloud: Best for Augmented Analytics
- Domo: Best for Integrations and Extensibility
- Qlik Sense
- SAP Analytics Cloud: Best for Embedded Analytics Capabilities
- Tableau: Best for Advanced Analytics
- Cognos Analytics
- Logi Symphony: Best for Embedded Analytics
Best Data Visualization Tools
Here’s a quick look at our analyst-curated top products so you can see how they stack up:
Select up to 5 products from the list below to compare
| Product | Analyst Score SelectHub's Analyst Rating is based on data from our 400+ point analysis of Business Intelligence Tools,
user reviews, and our own crowd-sourced data from our free software selection platform.
Scores are used to determine the top features and are periodically updated via ongoing selection projects
and user activity within our platform.
| Awards | User Sentiment Score
The percentage of users who would recommend this product based on user
reviews collected from popular reviews sites.
| Start Price | Free Trial | Company Size | Deployment |
|---|
| Strategy One | Best Overall | 84%Great |
$13 Per User, Monthly
| 30 Days (Request for Free) |
Small
Medium
Large
|
Cloud
On-Premise
| |
| Oracle Analytics Cloud | Best for Augmented Analytics | 83%Great |
$16 Per User, Monthly
| 30 Days (Request for Free) |
Small
Medium
Large
|
Cloud
On-Premise
| |
| Domo | Best for Platform Capabilities | 87%Great |
Custom Quote
Domo doesn't have a fixed starting price. For pricing details, you'll need to request a custom quote.
Factors that can influence final pricing for Business Intelligence Tools typically include number of users,
chosen modules or features, level of support, services like implementation, and add-ons.
| 30 Days (Request for Free) |
Small
Medium
Large
|
Cloud
On-Premise
| |
| Qlik Sense | None | 85%Great |
$31 Per User, Monthly
| 30 Days (Request for Free) |
Small
Medium
Large
|
Cloud
On-Premise
| |
| SAP Analytics Cloud | Best for Embedded Analytics Capabilities | 84%Great |
$36 Per User, Monthly
| 30 Days (Request for Free) |
Small
Medium
Large
|
Cloud
On-Premise
| |
| Tableau | Best for Advanced Analytics | 88%Great |
$15 Per User, Monthly
| 14 Days (Request for Free) |
Small
Medium
Large
|
Cloud
On-Premise
| |
| Cognos Analytics | None | 81%Great |
$7.88 Per User
| Yes |
Small
Medium
Large
|
Cloud
On-Premise
| |
| Logi Symphony | Best for Embedded Analytics Capabilities | 87%Great |
Custom Quote
Logi Symphony doesn't have a fixed starting price. For pricing details, you'll need to request a custom quote.
Factors that can influence final pricing for Business Intelligence Tools typically include number of users,
chosen modules or features, level of support, services like implementation, and add-ons.
| No |
Small
Medium
Large
|
Cloud
On-Premise
|
Bottom line: Strategy One is a good fit if you're at a mid-to-large org handling high data volumes routinely and need scalable reporting. If you're a smaller team or just starting with BI, I suggest you check out simpler tools.
During the free trial, I was impressed with the Targeted Visualizations feature — filters applied to one view updated linked charts automatically. The semantic layer is a differentiator, earning Strategy One best-in-class honors for data preprocessing in our analysis. The platform also excels at offline mobile data access.
While the desktop version suits developers and data analysts, the web version supports content delivery to clients and stakeholders. However, users say learning to use the platform can take time, and the web, desktop, and mobile experience don’t always sync.
- AI bots – Auto Express bots analyze your data, generate dashboard summaries, and suggest questions worth asking that you might have missed.
- Action Triggers – You can update Salesforce records, trigger Marketo campaigns, and approve Workday expenses directly from a Strategy One dashboard.
- HyperIntelligence – Add a Chrome extension and contextual data surfaces when you hover over a name on any webpage.
- Intelligent Cubes – Data stored in memory gets reused across reports, so your team isn't querying the same large datasets over and over.
- Metadata management – A central index organizes datasets with consistent naming and tracks their history, so teams rely on the same trusted data every time.
- You get a semantic layer for no-SQL data modeling
- You get advanced analytics, including text data and what-if analysis
- Strategy One earns best-in-class honors for mobile capabilities, offering offline caching and barcode scanning for field teams
- You also get over 200 connectors out of the box, plus SDKs if you need to build something custom
- Users say the learning curve is steep, especially if your team is new to enterprise BI
- Users also say the platform is expensive, putting it out of reach of leaner orgs
- The web, desktop, and mobile products don't always stay in sync, which can make the experience feel fragmented
- You won't get the same NLP capabilities in the desktop version as you do in the web version
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Bottom line: Oracle Analytics Cloud is a strong fit if you’re at a large or upper‑mid enterprise that already runs Oracle Cloud/Fusion apps/NetSuite and wants governed BI plus self‑service. It might not be ideal if you want ultra‑low‑cost, quick, standalone BI and are not on Oracle at all.
Though Oracle Analytics serves all industries, its primary users include IT, software, and financial services. It connects to Oracle, Azure and AWS clouds, databases, and data lakes, and standard source files. Our research pegs it as best-in-class for reporting and location insights.
Deployment is fairly straightforward for existing Oracle users, and your work will mainly involve data modeling, security, and dashboard setup. For on-prem implementation, you’ll need to connect to the Oracle Analytics Server.
That said, users new to Oracle consistently flag onboarding issues and a slow support response as barriers to getting value quickly.
- Semantic modeling – You get a business-friendly layer that translates raw data structures into plain terms to explore and analyze data independently.
- Reusable workflows – Oracle Analytics captures each step of your data transformation pipeline, making it easy to reuse the workflow across projects.
- Direct query – You can run live queries for critical KPIs or use data caching if it’s routine reporting, balancing data freshness against system load.
- Oracle Analytics Publisher – Generate formatted labels, checks, PDF forms, letters directly from any dataset or semantic model.
- Visualization library – Choose from a broad library of 45+ charts, geospatial maps, and network diagrams, or build custom views using extensions from the community library.
- You get built-in machine learning with one-click predictions
- You also get plain text, podcast-style insights on mobile devices
- You can use text searches to find and visualize content in reports
- It fits right in if you’re already using Oracle HCM, ERP, CX or SCM
- It's not as intuitive as Power BI
- Premium pricing can put it out of reach if you’re a small org
- Performance can lag under heavy data loads
- You won’t get the custom viz and reporting flexibility of Power BI and Tableau
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Bottom line: Domo is a strong fit if you’re at a mid-to-large org that needs an all-in-one, self-service cloud analytics platform with broad integrations. If you have a small team (<50) or need semantic layer governance, I suggest you check out Strategy One.
Retail, financial services, and tech companies use it to unify CRM, ERP, and operational data. During the free trial, I noticed the interface felt a bit clunky in places, and the mobile app didn't work offline.
Implementation is SaaS, so you can get started within days if you need connectors and basic ETL. Setting up governance, credit optimization, and custom apps can take a few weeks, though. Integrations include Salesforce, Snowflake, NetSuite, Workday, Google Analytics, POS systems, and cloud warehouses.
However, consumption-based pricing can make bills unpredictable during workload spikes.
- Magic ETL – You can blend, aggregate and filter datasets using a guided checklist with a drag-and-drop transformation tool.
- Beast Mode – You can perform advanced calculations using complex formulas with built-in validation even if you don’t know SQL.
- Permissions – Create data views by role, so regional managers only see their slice of data while senior leaders can toggle between filtered and full views.
- KPI alerts – You can set threshold-based alerts on key metrics and choose whether notifications go to email, mobile app or SMS.
- AI chat – Query data in plain language and get SQL outputs or text-based summaries without writing a line of code.
- You get self-service ETL out of the box
- Domo has the best integration network in the industry, according to our research, covering CRMs, ERPs, EHRs, and cloud apps
- You can add unlimited users as pricing is usage-based
- You get AutoML and Jupyter integration for predictive data modeling out of the box
- Consumption-based pricing can get expensive fast, if workloads or data volumes spike
- Users say Domo can slow down occasionally
- Data querying isn’t as strong as Power BI, Tableau, and Looker
- Getting Started documentation is outdated, which can slow down team onboarding
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Bottom line: Qlik Sense is a strong fit if you’re at a mid-to-large org that needs associative, self-service analytics for complex datasets. It might not be ideal for complete BI novices, tiny teams (<10 users), or orgs wanting zero governance overhead.
The platform serves manufacturing, retail, finance, and healthcare. During the free trial, I was impressed with the associative engine, a welcome change from building data models manually in Tableau or Power BI. It’s a time-saver for teams managing high data volumes routinely.
Implementation is cloud SaaS, but configuring governance, data prep, and security can take a while. Qlik Sense supports a broad set of AI integrations, including OpenAI, H2O.ai and IBM Watson for NLP. It also connects to Slack for automated report delivery and notifications. Pricing starts at $31/user monthly.
- Associative linking – Qlik Sense automatically detects data relationships at load time, so you can explore datasets freely without manual joins.
- Insight Advisor – You can ask questions in plain language and get chart recommendations plus follow-up questions — no SQL needed.
- Smart data loading – Qlik Sense pulls live data when needed and can use stored calculations for historical dashboards to reduce compute load.
- Qlik AutoML – AutoML automates model building, preprocessing, training, and hyperparameter tuning on your datasets to deliver forecasts and driver analysis.
- Automated reporting – You can schedule and send reports to stakeholders with the Reporting Service, including people who don't have a Qlik license.
- You get an associative engine that establishes dataset associations, saving significant modeling time
- A modular architecture lets you start lean and add capabilities as your analytics needs grow
- You get more deployment flexibility with Qlik Sense working on Windows, Mac, Linux and all mobile devices
- You get volume-based discounts
- Users say performance degrades noticeably when processing large datasets
- Qlik Sense is expensive compared to Tableau and Power BI
- You won’t get as many visualization types as with Tableau
- The SaaS model requires admin setup for private workspaces
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Bottom line: SAP Analytics Cloud is a strong fit if you’re at a mid-to-large org that’s already invested in SAP products and needs a unified hub for financial planning, budgeting, and analytics. If you're a smaller team looking for a straightforward BI tool, I suggest checking out Power BI and Looker Studio.
SAP is purpose-built for enterprise finance. During the free trial, I was impressed with its planning and consolidation capabilities. Bidirectional filtering makes SAP a leader in embedded analytics — embedded dashboards update when you apply filters in the host application, and vice-versa.
That said, the platform can be slow when handling live non-SAP connections at moderate scale. Also, reporting often needs IT involvement to get it right.
For SAP-invested organizations, the platform's depth makes it worth the ramp-up.
- Smart Predict – You can forecast sales figures, order values, and campaign impact using machine learning.
- Just Ask – You can type plain-language questions, and Qlik Sense auto-completes your queries and suggests follow-up analysis.
- Automated data prep – Qlik Sense automatically detects metrics, dimensions, and dates, linking related tables to reduce manual data modeling.
- Smart Insights – The system automatically spots what’s affecting your key metrics, flags outliers, and highlights unusual trends early.
- Accessible dashboards – Built-in screen reader, speech, and color-contrast support meets WCAG 2.1 standards without extra setup.
- You get a rich graphics library for dashboarding
- You get direct write-backs to BW/4HANA for planning and budget/headcount/quota adjustments
- SAP earns a perfect score for data management in our analysis, delivering real-time data blending from Datasphere/S/4HANA
- You get bidirectional filtering so you can refine a CRM list while drilling into SAP sales charts simultaneously
- Users say SAP underperforms at scale
- Users also say reporting isn’t entirely self-serve and requires IT support
- Interface navigation feels unintuitive, and there’s a steep learning curve
- SAP Analytics has limited value outside of the SAP ecosystem without live semantics and direct write-back
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Bottom line: Tableau is a strong pick if your org needs fast, self-serve access to polished visuals and you're working across a mix of data sources. It might not be ideal if you need a dedicated reporting tool or your budget is tight.
The platform works well across all industries, especially healthcare, finance, retail, manufacturing. During the free trial I was impressed that I could go from raw data to a working dashboard in minutes. Tableau earns our best-in-class honors for advanced analytics, supporting regression, what-if, IoT, and text analytics.
At $70 per user monthly for authoring, dashboard creation can get expensive as more team members need access. The good news is, Tableau Prep Builder is bundled into the Creator license.
- AI-assisted exploration – Explain Data delivers plain-text explanations of visuals and trends.
- Storyboard narratives – You can drag dashboard sheets onto a storyboard to show stakeholders how key metrics are trending over time.
- Tableau Prep – Clean and reshape messy data — surveys, social media posts, you name it — before it ever hits your dashboards.
- Interactive filtering – Drag any field onto the Filter shelf to slice data by value range, conditions or top-N results, no query writing required.
- Mobile sharing – Share dashboards and maps from Android or iOS, with push notifications keeping your team up to date on comments and status changes.
- Users say the drag-and-drop builder gives them a lot of visualization flexibility
- Tableau offers the best advanced analytics in the industry, according to our research
- You can pull data from files, databases and major cloud platforms
- A tiered licensing structure lets you mix user plans to keep costs in check as your team grows
- Authoring rights are limited to the Creator tier, which starts at $70 per user monthly
- Users say performance slows down noticeably with massive datasets
- You'll need Python/R knowledge to get the most out of statistical visualizations
- You can't schedule report exports
Insider Tip: Salesforce integrated Tableau with Einstein Analytics, leading to the launch of Tableau Pulse, which uses analyzed data to recommend the next best action.
However, compared to a homegrown solution such as Power BI, Tableau lacks certain subtleties, like intelligently assigning magnitude to amounts ($2.5 B instead of 2,500,000,000) and including curved lines in visualizations.
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Bottom line: Cognos Analytics is a strong fit if you’re at a mid-to-large org that needs reporting and visualization in a single self-service platform. It might not be ideal if mobile-based authoring or NLP are priorities for you.
During the free trial, I found the interface easy to use — learning the basics took about three days, which is fast given the platform's depth. Reporting and visualization both earn perfect scores in our analysis, making it a step up for teams stuck manually assembling dashboards from spreadsheet exports.
Cognos fits most naturally in an IBM ecosystem, connecting to Watson Studio and Jupyter Notebooks natively, but broader integrations need data prep and custom coding. If you want a more cost-effective solution, I suggest checking out Power BI.
- Event Studio – You can set conditions that automatically trigger report delivery, email alerts, or database updates without any manual intervention.
- Active reports – Cognos delivers fully interactive reports that open directly in email, with no login, app, or browser tab-hopping — ideal for field sales teams.
- Guided explorations – Automatic visualizations and natural language queries let you dig into data patterns without writing code.
- Time-series forecasting – Click on any time-based chart to generate Watson-powered trend predictions on the spot.
- Data catalog – You can search a shared inventory of databases, reports, and metadata to find data assets fast.
- Cognos earns a perfect score for data visualization in our analysis, auto-generating dashboards once you’ve selected the data
- Our analysts give it a perfect score for full-featured reporting, with conditional formatting, scheduling, versioning, and burst capabilities
- You get automated data validation alongside strong metadata management
- Users say the platform is easy to use
- Users also say performance slows noticeably when handling large, complex datasets
- Licensing costs are high compared to competing BI tools offering similar or better features
- You won’t get competitive natural language insights
- You can’t create/edit reports on the mobile app, though you can interact with them
Bottom line: Logi Symphony is a strong choice if you’re a dev-heavy mid-to-large org embedding analytics into SaaS apps, CRMs, or ERPs. It might not be ideal if you’re a small org with non-technical users seeking a self-serve analytics solution.
The platform earns our best-in-class honors for embedded analytics, serving SaaS product vendors, fintech (embedded trading dashboards), healthcare (patient portals), and supply chain (real-time tracking).
Logi Symphony connects to SQL/NoSQL databases and APIs, works on-prem and in the cloud, and supports custom R, Python, and REST workflows.
However, lean documentation and a steep learning curve mean you'll need developer resources ready from day one. If you want an embedded analytics solution without the development overhead, I suggest checking out Sisense.
- Application embedding – You can drop analytics straight into the apps your users already work in — CRMs, ERPs, and custom tools.
- Low-code development – Developers can build and customize analytics apps using configurable features and code-level controls — no need to start from scratch.
- Predictive analytics – Tweak inputs for ML models and run scenarios to project outcomes across your business — no coding needed from your team.
- Self-service analytics – Business users can clean, analyze and visualize data on their own, reducing reliance on data scientists for everyday reporting tasks.
- Generative AI – Logi AI connects to leading LLMs like ChatGPT, Hugging Face models, and Azure OpenAI for quicker insights.
- You can embed analytics directly into the CRM and ERP apps your team already uses
- Logi Symphony connects to a wide range of cloud and on-premise data sources
- You also get strong reporting out of the box, including pre-built and ad hoc options
- Users say the support team is responsive and especially helpful during onboarding
- Users also say licensing costs keep rising, and unclear pricing changes are confusing
- You won't find much help documentation when you hit a wall with complex reporting scenarios
- Users say performance and load times can be slow when working with large datasets
- Users say updates can break existing features, leaving your developers to rewrite scripts to get things working again
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How We Rated and Tested Products
Our process for rating and reviewing products involved two parts:
- The analyst scores, which determine the top products
- My personal research into each product to supplement our analyst data
How the Analyst Score Works
Our team of analysts conducted in-depth research of the business analytics software market using primary and secondary sources. This included SelectHub Analyst Briefings, direct communication with vendors, and reviewing materials such as user reviews, product brochures, specification sheets, case studies, user manuals and technical documentation.
Our platform’s Scoring Engine processed all the research to compute the analyst score. The score is based on how comprehensive each product’s feature-set is and how much is available out of the box vs. through extra modules, integrations and other means. The scores that determined the top 8 products for our list were based on all the data visualization features in our platform:
- Accessible dashboard
- Animation
- Annotation
- Charts types
- Custom dashboards
- Dashboard templates
- Dashboard themes
- Data visualization recommendation
- Export visualizations
- Interactive visual components
- Scorecard
- Slideshow
- Third-party visualizations
We use the scale below to rate every feature in our platform:
| Level of Support | Score | Description |
|---|---|---|
| Fully Supported Out of the Box | 100 | This feature is comprehensively supported out of the box with industry-leading capabilities and is immediately available after installation, without needing any additional modules, integrations, or custom development. |
| Moderately Supported Out of the Box | 85 | This feature is moderately supported out of the box and is immediately available after installation, without needing any additional modules, integrations, or custom development. |
| Supported with Workarounds | 70 | This feature is not directly available in the software but can be accomplished using other built-in features or any other workarounds, without any additional cost. |
| Supported with Additional Modules | 60 | This feature is available through additional modules or products from the vendor at an additional cost. |
| Supported with Partner Integrations | 50 | This feature is available through additional integrations, plugins, or marketplace applications from a third-party vendor at an additional cost. |
| Supported with Custom Development | 25 | This feature is not built in, and cannot be added by purchasing additional modules or integrations, but can be custom developed using the APIs, libraries, extensions, and development framework supported by the software, with or without any additional cost. |
| Not Supported | 0 | This feature is not supported. |
My Research Process
I spent countless hours reading product documentation, watching video tutorials and demos, and sourcing sample data from vendor websites and reliable online sources.
Here’s a breakdown of the key areas I focused on when testing each product firsthand:
- Data Integration: I examined the variety and quality of data connections, checking for connector types, ease of connectivity, live integration, and any noticeable latency when loading data.
- Data Preparation: My focus here was on blending data from multiple tables, establishing dataset associations, and testing calculated columns and measures to determine the platform’s capacity for in-depth data analysis.
- Data Visualization and Dashboarding: I evaluated auto-charting, interactive visualizations, and drill-through capabilities, as well as the ease of dragging and dropping items onto the workspace. I also assessed filtering, the consistency of data changes when filters were applied, and customization options.
- Ease of Use: I assessed the layout for ease of navigation and organization, checking if the required tabs were easy to locate and if it was equally easy to return to the homepage. Additionally, I examined whether the screen elements were arranged logically for data analysis.
- Reporting: I tested report generation, customization, sharing, and collaboration features, including the platforms to which reports could be shared, the seamlessness of email distribution, and the functionality of shareable links.
- AI Insights: Due to limitations in AI capabilities during free trials, I focused on the ease of uploading data to an AI bot (if available) and the understandability of the results.
When unable to test Oracle Analytics, I turned to user reviews on Capterra, G2, Gartner, Software Advice and Reddit, as well as product reviews on reliable publications like PCMag. Vendor blogs were helpful in establishing product use cases.
Jump back to the product comparison. Or learn more about our research methodology and editorial standards.
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FAQs
Among the above tools, at $10 per user monthly, Cognos Analytics is affordable for small businesses and offers a robust feature set that includes AI insights and strong system integration. We also advise checking out Strategy One for a good balance of cost and features.
Consider Tableau and Qlik Sense for advanced AI and sophisticated data visualization, though their price point is higher.
However, you need not limit yourself to these platforms. Check out our data analytics product directory for more options.
For real-time updates, a data visualization tool should focus on live data integration, low-latency processing and automated alerts. You also need customizable dashboards with adjustable refresh rates, scalability, and integration with data pipelines and collaboration tools.
For scheduled reporting, your requirements checklist should have automation, batch processing and report distribution. Additionally, report templates, customization and formatting, access control, audit trails, and integration with BI tools are useful features.
We advise factoring in add-ons, advanced analytics and sophisticated AI features, white-labeling, branding, and customization. Understanding the licensing structure can help you negotiate better and even take advantage of bundled offers and discounts.
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Need Expert Advice? Get Personalized Recommendations
Use our free comparison report to evaluate up to five products at a time. Our analyst ratings, based on functionality, industry, and business size, help you determine the right product for your organization.
Have you used a data visualization tool? Which features did you find useful? What challenges did you face? Let us know in the comments!
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Conversation (10)
Ryan - May 25, 2022
ChartExpo is missing, I use it because it is the only tool I can integrate with my both Excel and Google Sheets.
Surya - July 23, 2021
Don’t see Power BI here. Strange.
Myles - November 24, 2020
can i ask what year did this article was released thank you.
Hsing Tseng - December 7, 2020
Hi Myles,
This article was first published in 2018, though we update our articles every year.
Thank you for reading!
Netset Software Solutions - September 3, 2020
Thanks for sharing this great information, such as a great article and valuable thoughts about business intelligence visualization.
Hsing Tseng - October 9, 2020
Thank you for reading! Data visualization is certainly a critical requirement for business intelligence. We appreciate your thoughts!
Appknock - August 31, 2020
Great Article!! Thanks for sharing this great information about Data visualization. Keep Sharing
Hsing Tseng - October 9, 2020
Thank you for reading!
Zuo - November 25, 2019
Lol. Tableau not mentioned? Really?
Hsing Tseng - February 5, 2020
Hello,
Thank you for bringing this to our attention. You’re right – we agree that Tableau should be added to this list.
We’ve updated the article accordingly to reflect this.
Thank you for reading and providing your insight!