With more data at our fingertips, it’s getting harder to focus on what’s relevant to problems, and then present it in an actionable way. That’s what business intelligence (BI) is all about.
BI tools make it simpler to corral the right data, and then see it in ways that you can understand what it means. But how simple that process gets, and how you can visualize the data depends on the tool, so picking the right one for your needs is essential.
According to Gartner, the mandatory features of a BI platform include:
- Data visualization: Platforms must support the graphical representation of information and data, and the creation of interactive dashboards.
- Governance: An enterprise BI platform must have the capability to track usage and manage how information is secured, shared, and promoted.
- Reporting: It must support the creation of reports to share data insights.
- Analytics catalog: These simplify finding and consuming data. Platforms need analytics catalogs that are searchable and can make recommendations to users.
- Data preparation: BI platforms must support cleaning, transforming, and organizing data to make it usable by algorithms.
- Data science integration: Platforms must have capabilities that enable the augmented development and prototyping of composable data science and ML models.
In addition to these mandatory features, BI tools are increasingly leveraging AI to power automated insights. In a recent study by MIT SMR Connections, 67% of data and business leaders said their organizations have adopted gen AI for data and analytics, and 26% said they’re planning to do so.
Here, we round up 10 popular, highly regarded BI tools to help uncover what your organization’s data says about your business.
Top 10 business intelligence tools
- Amazon QuickSight
- Domo
- Looker
- Microsoft Fabric
- Oracle Analytics
- Pyramid Analytics
- Qlik Cloud Analytics
- SAP Analytics Cloud
- Tableau
- ThoughtSpot
Amazon QuickSight
Amazon QuickSight is a cloud-based offering integrated with the Amazon Web Services (AWS) data and analytics stack. AWS leverages Amazon Q, its gen AI-powered assistant, to power natural language query (NLQ) capabilities in QuickSight. With that, business analysts can build and refine dashboards using natural language. Beyond dashboards, QuickSight’s gen AI can create executive summaries and autogenerate data stories.
- Target audience: Customers in the broader AWS ecosystem.
- Notable features: Deep integration with AWS offerings including Amazon Redshift, Amazon Athena, and Amazon EMR; and serverless cloud architecture that enables high performance and can scale to high concurrency based on usage.
- Pricing: Starts at $3 per user/month for a Reader license.
Domo
Domo is a cloud-based platform focused on business-user-deployed dashboards and ease-of-use. It has a strong position in the marketing analytics space, and is popular with SMEs that lack a robust data warehouse foundation. It also offers BI tools tailored to various industries (such as financial services, health care, manufacturing, marketing, and education) and roles (including CEOs, sales, BI professionals, and IT workers). Domo has started to add AI-powered NLQ features, but lags behind some competitors in that space.
- Target audience: CEOs, sales and marketing, BI professionals.
- Notable features: Domo AI Model Management, a bring-your-own-model approach that enables users to deploy third-party models, or build and train their own.
- Pricing: On request; Domo has embraced a credits-based consumption model.
Looker
Looker is a multicloud-architected BI platform from Google. It offers governed analytics, including self-service visualizations and dashboards, and a code-first semantic modeling layer based on LookML. Google has integrated Looker Studio with that semantic layer to enable built-for-production reports and dashboards, self-service ad hoc questions, and support for analytic content developers. Looker is also integrated with Google’s data and analytics stack, and features direct integrations with Google Sheets, Chat, and Slides. Plus, it can leverage Google LLMs, including Gemini.
- Target audience: Customers in the broader Google ecosystem.
- Notable features: Looker is known for its composability, with a modular architecture that enables headless BI integration with other analytics and BI platforms.
- Pricing: By request; pricing has two main components: platform pricing and user pricing.
Microsoft Fabric
Microsoft Fabric is Microsoft’s unified, AI-powered data analytics platform, supporting both data management and analytics. It consolidates data movement, processing, storage, analysis, and visualization into a single stack. Microsoft has incorporated Power BI into Fabric to support data preparation, visual-based discovery, interactive dashboards, and augmented analytics. And Fabric has augmented Power BI’s capabilities with advanced analytics and ML functions. These capabilities enable Fabric to generate insights, automate tasks, and build predictive models.
- Target audience: Microsoft shops.
- Notable features: Integration with Power BI, Azure, and Microsoft 365; Copilot for Power BI.
- Pricing: Pay-as-you-go or capacity reservation.
Oracle Analytics
Oracle has spent the past several years bulking out its Oracle Analytics offering, launched in 2014 as an outgrowth of its flagship Business Intelligence Enterprise Edition suite. In 2020, it added a Cloud HCM offering to provide self-service workforce analytics to HR executives, analysts, and LOB leaders. Oracle has also focused on making its cloud offering intuitive and user-friendly, with powerful reporting and ML features. Other key features include data preparation, data connectors, visualizations, predictive analytics, a native mobile app, and support for embedded analytics. Regarding AI, Oracle has added document understanding to its existing vision, text, and language capabilities, enabling the use of gen AI to create data stories. Additionally, Fusion Data Intelligence, Oracle’s cloud-based analytics warehouse platform can be associated with Oracle Analytics to enable these features by embedding analytics and AI into business applications and workflows.
- Target audience: Users in midsize to large enterprises.
- Notable features: Conversational analytics support natural language queries; can automatically generate natural language explanations to explain visualizations and trends.
- Pricing: Enterprise: $80 per user, per month; Professional: $16 per user; Professional – Bring Your Own License (BYOL): $0.3226 Oracle compute unit (OCPU) per hour; Enterprise – BYOL: $0.3226 OCPU per hour.
Pyramid Analytics
Pyramid Analytics is a business and decision intelligence platform built from the ground up on ML-based data preparation and data wrangling. Its multi-LLM strategy offers customers flexibility, and the platform is deployment-agnostic, enabling customers to host it in AWS, Microsoft Azure, Google Cloud Platform, Oracle Cloud, Alibaba, or on-premises. Users can leverage Pyramid’s own internal portable language model or third-party LLMs with the platform’s NLQ interface for text and speech input and output.
- Target audience: Business users and data professionals; large enterprises.
- Notable features: Deep support for data prep, including a one-click quick Smart Modeling tool for augmented model building; a Direct Model for creating a semantic data model on top of an existing database without data manipulation; Model Lite, which offers a step-by-step wizard; and an advanced ETL-like process with pipeline workflows and ML tools.
- Pricing: On request.
Qlik Cloud Analytics
Qlik Cloud Analytics is a SaaS platform that includes Qlik Sense, Qlik AutoML, and Qlik Application Automation. Qlik’s goal is to give anyone in the enterprise access to all its data — subject, of course, to corporate data governance policies. All that data should be enough to bog down most database engines, but Qlik says its Associative Engine can associate every piece of data with every other piece to make it easier to search for connections. The Associative Engine now has AI and ML capabilities that offer context-aware insight suggestions, thanks to the Qlik cognitive engine. Qlik Staige, introduced in 2023, combines a data foundation with automation, and AI-based descriptive, predictive, and prescriptive analytics.
- Target audience: The whole enterprise.
- Notable features: Associative Engine can analyze all your data, on the fly.
- Pricing: By request for enterprise edition.
SAP Analytics Cloud
SAP Analytics Cloud is a cloud-native multitenant platform that supports data visualization, reporting, augmented analytics, and business planning. It unifies analytics and enterprise planning, and leverages gen AI via the Joule copilot to automate reporting, discovery of insights, and development of business plans. Together with SAP Datasphere, SAP Analytics Cloud can analyze both SAP and non-SAP data into enriched semantic models.
- Target audience: Customers in the SAP ecosystem.
- Notable features: Seamless integration with SAP enterprise applications, including SAP S/4Hana, SAP SuccessFactors, and SAP Ariba.
- Pricing: On request.
Tableau
With Tableau, Salesforce covers all the bases: You can run its software on premises, choose a public cloud, or opt to have it fully hosted by Tableau. It offers tailored versions for over a dozen industries, including banking, healthcare and manufacturing, with support for financial, HR, IT, marketing, and sales departments, although that’s almost expected these days. Tableau’s capabilities include mapping and analysis of surveys and time series data. Gen AI and natural language processing allows users to describe what they want to see, rather than having to click and drag to create formulaic queries. Then Tableau Pulse provides an augmented analytics experience integrated with existing workflows that uses AI to automate analysis, surface insights in plain language, and proactively anticipate user questions.
- Target audience: Midsize and larger enterprises.
- Notable features: VizQL, a visual query language that translates SQL queries to generate visual representations of data.
- Pricing: Enterprise Creator: $115 per user/month billed annually; Enterprise Explorer: $70 per user/month billed annually; Enterprise Viewer: $35 per user/month billed annually.
ThoughtSpot
ThoughtSpot is an agentic AI-powered BI platform that provides insights and visualizations in response to natural language queries. It’s available as a vendor-managed SaaS, customer-managed cloud, and/or on-premises software. Sage, a gen AI-enabled conversational analytics interface, enables native NLQ with human-in-the-loop feedback, while SpotIQ provides automated insights and data storytelling. SpotIQ also has a monitor function for KPIs, and the self-learning AI is powered by Microsoft OpenAI GPT-4 model and Google Gemini.
- Target audience: Data analysts and analytic content consumers.
- Notable features: Spotter, an AI analyst copilot that allows users to ask questions in natural language and receive insights and visualizations.
- Pricing: Essentials: $1,250/month for 20 users billed annually; Pro: pricing on request for unlimited users billed annually; Enterprise: pricing on request for unlimited users and unlimited data billed annually.
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Read More from This Article: BI buyer’s guide: Top 10 business intelligence tools
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