Business Intelligence (BI) Tools

TrustRadius Top Rated for 2023

Top Rated Products

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1
Sigma Computing

Sigma Computing headquartered in San Francisco provides a suite of data services such as code free data modeling, data search and explorating, and related BI and data visualization services.

2
Spotfire

Spotfire® is a data visualization platform that utilizes predictive analytics. In addition to data viz, it includes data wrangling capabilities, predictive analytics, location analytics, and real-time streaming analytics. Spotfire® is a business unit of Cloud Software Group, formerly…

3
SAP Analytics Cloud

The SAP Analytics Cloud solution brings together analytics and planning with integration to SAP applications and access to heterogenous data sources. As the analytics and planning solution within SAP Business Technology Platform, SAP Analytics Cloud supports trusted insights and…

4
GoodData

GoodData is a cloud-based data and analytics platform, bringing AI-fueled data-driven decision-making to organisations across the globe. With a platform that leverages the potential of automation and AI, GoodData empowers its customers to make data analytics available to end users…

5
Clari

Clari is a predictive sales analytics and sales forecasting solution from the company of the same name headquartered in Sunnyvale.

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176
Strategy Companion Analyzer

Analyzer from Strategy Companion headquartered in Irvine provides a self-service business intelligence solution that allows managers to explore, visualize, publish, and share actionable insights in minutes. Users can ask questions of their data to uncover trends, opportunities, and…

177
BDB Decision Platform

BizViz Analytics Platform is a business intelligence solution that is designed to serve any vertical, and provides a 360° view of a organization’s data. This solution includes tools for creating dashboards, business apps, and geospatial analysis. It is comprised of a variety of modules…

178
Smarten
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Videos for Business Intelligence (BI) Tools

What is Business Intelligence (BI) and Why is it Important?
01:40
BI keeps businesses smart. Watch to learn more about business intelligence and how it can help businesses thrive. Business intelligence, or BI for short, is a technology-driven process for analyzing data and presenting information. This helps executives, managers, and other co...
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Top Business Intelligence Tools (Qlik Sense, Tableau, ThoughtSpot, IBM Cognos Analytics)
06:50
In this video, the TrustRadius team will be discussing the top business intelligence tools available: Qlik Sense, Tableau, ThoughtSpot, and IBM Cognos Analytics.

Business Intelligence (BI) Tools TrustMap

TrustMaps are two-dimensional charts that compare products based on trScore and research frequency by prospective buyers. Products must have 10 or more ratings to appear on this TrustMap.

Learn More About Business Intelligence (BI) Tools

What is Business Intelligence (BI)?

Business Intelligence tools are designed to make sense of the huge quantities of data that organizations accumulate over time. BI tools analyze this information and present it as actionable information that can guide decision making.

Business Intelligence software (BI) makes up a large heterogeneous category of software. Not all tools in the category can be meaningfully compared to each other. There are several types of BI tools of which the most substantive are Full-Stack Business Intelligence Tools and Data Visualization Tools.

Business Intelligence Tools Features & Capabilities

  • BI Platform Type
  • Supported Data Sources
  • Standard Reporting
  • Ad-Hoc Reporting
  • Report Output and Scheduling
  • Data Discovery and Visualization
  • Access Control and Security
  • Mobile Capabilities
  • APIs / Embedding

Full-Stack Business Intelligence Tools

Full-stack or traditional products are enterprise-level BI tools designed to solve the specific problem of enterprise data silos. Much crucial business data is stored in a range of different data stores, many attached to business applications like ERP. Full-stack BI tools consolidate all data in a data warehouse which is a relational database designed for data mining instead of transactional processing.

Slices of data from the warehouse—usually summary data for a single department like sales or finance—are stored in a “data mart” for quick access. All of this structured data is normalized by using an ETL process (Extract, Transform and Load) whereby transactional data is combined into a single pool of data and then “transformed” into a more appropriate format for querying and analysis before being written in the data warehouse database.

The Full-Stack Business Intelligence TrustMap shows only those products that belong in this sub-category.

Data Discovery and Visualization Business Intelligence

Data Visualization products have a different purpose. These BI tools are primarily designed to help data analysts discover patterns in large quantities of data and to build compelling visual representations which allow these patterns to be easily understood.

These business intelligence tools often use a technology called in-memory analytics to query data residing on a computer’s RAM rather than on a physical disk. This means that the data does not have to be stored anywhere for subsequent analysis.

Data visualization products often have lower cost of implementation and require less support. This can make them good business intelligence tools for small companies that don’t need a full-stack business intelligence solution.

The Data Visualization TrustMap shows only those tools that belong in this sub-category.

Business Intelligence and Reporting

Many BI tools also enable some forms of reporting. Modern BI’s ability to intake many different forms of data and present them in increasingly high and professional quality, some organizations are able to use their BI tool both to surface specific insights and generate regular reports. The level of automation found in BI reporting will vary highly from product to product. For general reporting needs, the ability to set-and-forget data pipelines into a BI tool and the normalization of functions like dynamic dashboards make some leading BI tools competitive automated reporting tools as well. However, specialized reporting cases that use more niche data structures may be less automatable in traditional BI tools.

Business Intelligence Software Comparison

When considering different business intelligence tools, consider the following aspects of each product offering.

  1. Ease of Use: Some BI tools offer high complexity and customization, but can be difficult for non-technical users. You should consider the technical ability of the staff that will be using the BI tools as well as if you need more complex features.
  2. Compatibility: Many BI tools are not complete, end-to-end solutions. For some organizations, purchasing BI software from multiple vendors may be necessary. If your business needs BI features that aren’t all covered in a single product, be sure to ask venders about integrations and compatibility with other software.
  3. Scalability: Some BI software doesn’t scale up very well as data needs increase. Consider the breadth of data generated by your organization and decide if that amount will stay the same or increase. If your data needs will increase, be sure to choose a BI solution that can handle your expected growth.

Start a Business Intelligence Software Comparison

Pricing Information

Business Intelligence software is generally quite expensive. However, it’s worth remembering that it is often money very well-spent in terms of significantly improved decision-making.

One of the impediments to understanding pricing is that vendors base their pricing on a broad range of different variables from number of users to number of CPU cores.

However, as a very rough guide, advanced report authoring can cost $2,000 to $2,500 per seat, while interactive report viewing can be about half that amount. Static report viewing can be as little as $50 per seat.

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Frequently Asked Questions

What problem does business intelligence solve?

Business intelligence tools help to make sense of the enormous quantities of data business have regarding customers, suppliers, and business partners, and help uncover the insights within that data that are vital to winning in the marketplace. Business intelligence is an umbrella term for various methods of collecting and analyzing this data to help organizations make data-driven decisions.

What are data discovery and visualization products?

Data discovery and visualization products are primarily designed to help data analysts and business users discover patterns and outliers in large quantities of data, and to build compelling visual representations which allow these trends and patterns to be easily understood. Commonly available visualizations include charts, graphs, and maps.

What is embedded business analytics?

Embedded analytics is the integration of BI capabilities directly into a business application or portal. The idea is to provide analytics that are contextual. In other words, analytics tools are available directly within whatever business application is being used at a given moment, whether it be Salesforce, an ERP system, or a marketing automation tool.

What is augmented analytics?

Augmented analytics is a term used to denote the use of machine learning and natural language processing to automate insights into datasets generated by analytics and BI tools. Today, many well-known BI platforms have built-in capabilities to automate data preparation and detect some correlations and anomalies in large data sets. The ultimate goal is for this technology to be capable of analysis and even insight generation and action plan generation.

What is the difference between business intelligence and data science?

Both business intelligence and more recent technologies like data science are predicated on gaining business insight based on data analysis. The primary function of BI tools is to explore past trends in a business’s historical data and compare data across time. Data science tools, on the other hand, use algorithms to understand and predict a business’s future performance. Data scientists build data models to try to answer questions or discover predictive patterns in huge volumes of data.