Business intelligence (BI) software tools enable companies to analyze events, trends and market changes to gain competitive advantage.
These BI tools collect, manage and interpret mountains of structured and unstructured data. They construct models that deliver answers and insights through reports, charts, graphics and other data representation methods. BI software is the foundation of digital transformation.
BI systems incorporate or use various data sources, including spreadsheets, querying software, reporting tools, online analytical processing (OLAP), data mining, data warehouses, and data marts. They usually encompass data extraction, data cleansing, data governance and dashboards or other mechanisms that allow users to view reports and visualizations.
The objective is to support business processes across an organization. These can range from past events, such as how a product or service performed, to predicting future events and scenarios. They can span various departments, including finance, human resources and operations. Increasingly, BI platforms intersect with machine learning (ML) and other artificial intelligence (AI) tools, such as natural language querying. They support advanced data mining techniques.
Not surprisingly, business intelligence—which dates back to the 1970s—continues to advance. Today’s systems span clouds and tap on-premises data sources, and work alongside data mining tools. They also rely on APIs to extend analytics capabilities across business partners and supply chains. Some platforms are also designed to pull data from edge computing deployments, and many platforms also include open-source tools and components that make them more flexible and adaptable.
How to Choose a BI Software Tool
As you focus on selecting your BI software tools, it helps to focus on five crucial steps:
- Analyze your existing data sources. Obviously, any new solution must ingest your organization’s existing data. Either it will do this directly or you will have map data structures and perform conversions manually. Without knowing what data currently exists and where it resides, it is next-to-impossible to determine what BI platform to use and what’s involved with the transition.
- Identify your objectives. If you’re looking to take your business intelligence and data analytics to the next level, it’s critical to identify the features you need in order to find a good match. For instance, do you want to expand the use of BI to different groups or departments? What types of reporting and data visualizations do you require?
- Determine whether other sources of data can improve business results. A primary reason to adopt a more advanced BI platform is to add features and capabilities. Are you looking to tie together cloud repositories or various enterprise systems? Are you hoping to build out a framework with edge computing companies to expand data collection across a supply chain? These are fundamental questions to ask before selecting a vendor.
- Survey the vendor landscape. Of course, vendors and software solutions approach BI in fundamentally different ways. Is the vendor geared toward on-prem, or are they cloud only? As a result, a critical element in selecting a solution is matching requirements with vendor features, its support framework and its roadmap. It’s important to determine which vendor can unlock the greatest value from your data, support business transformation and continue to add value in the future.
- Understand what changes are required. Any large initiative, including BI, requires changes to both IT infrastructure and business processes. Consequently, it’s essential to match your organization’s needs, desires and requirements with the right BI solution—and ensure that it delivers the ability, flexibility and scalability you need to navigate today’s fast changing business environment.
Top BI Software Tools
Here are 10 of the top BI software tool providers:
Domo
Key Insight: Domo focuses is on tying together data from a variety of sources and building insights through rich reporting and visualizations. The solution delivers sophisticated tools for handling data integration—including through visual ETL—as well as dashboards and mobile BI platforms that use intelligent apps to display analytic insights.
Pros
- Connects to a wide array of data sources and systems and offers powerful data importing and ingestion tools.
- Delivers real-time monitoring and results through robust alerts and notifications.
- Offers a rich and powerful feature set that can be used by data scientists as well as non-technical line-of-business users.
- Powerful dashboard capabilities.
Cons
- Additional apps and other tools and add-ons can increase the price tag significantly.
- Some users find the platform confusing and overwhelming due to a large array of options and choices.
- Lacks some embedded advanced analytics capabilities.
Microsoft Power BI
Key Insight: Power BI is a sophisticated but affordable platform for organizations of all sizes. It supports self-service analytics for line of business users and data scientists, incorporating AI and ML. Microsoft includes strong collaboration features along with rich reporting and data visualizations. Power BI delivers powerful automation and includes tools to align setup and operation with enterprise scorecards.
Pros
- Powerful data ingestion and connection capabilities combine on-premises and cloud data seamlessly.
- Offers a wide array of pre-built dashboards that connect to various applications, products and services.
- Delivers rich interactive capabilities, including real-time reports and visualizations.
- Provides strong data governance features.
Cons
- The learning curve for advanced analysis can be complex and difficult.
- Graphics and visualizations aren’t as robust as competing BI solutions.
- May be difficult to use with non-Microsoft products and technologies.
- Doesn’t support IOS and other Apple devices.
MicroStrategy
Key Insight: The vendor’s focus is “intelligence everywhere.” MicroStrategy offers tools to build powerful and attractive dashboards that pull data from more than 200 data sources. The solution works on both PCs and Macs. It can deliver services based on roles, devices and numerous other factors. MicroStrategy supports automation and embeds analytics functions directly into applications and websites.
Pros
- Includes powerful features, including a “hyperintelligence” function with strong automation capabilities.
- Provides a strong feature set and extremely flexible BI framework.
- Offers powerful data governance features along with strong security.
- Generates highly rated visualizations.
Cons
- Many users find the platform difficult to set up and use, particularly when handling extremely large data sets.
- The solution can be pricey.
- Lags other platforms with collaboration and social BI features.
Oracle Analytics Cloud
Key Insight: The cloud native BI platform is designed to handle the full spectrum of analytics requirements, from data ingestion and modeling to data preparation, enrichment, visualization and collaboration. It includes embedded ML and AI, including natural language search functionality. Open-source data connectivity with built-in connectors simplify data aggregation tasks.
Pros
- Provides more than 50 out-of-the-box connectors, including Java Database Connectivity.
- Delivers a scalable single source of truth data framework for line of business users as well as data scientists.
- Offers strong ML capabilities through a Python-based framework.
- Provides strong support for mobile devices and includes a powerful data governance and security framework.
Cons
- Users complain that the framework can break, particularly on upgrades. Error tracing can be difficult.
- The interface could be modernized and improved.
- User ratings for technical support and end-user training rank below competitors.
Qlik Sense
Key Insight: The vendor delivers robust BI through a cloud analytics platform. Qlik Sense dashboards connect to hundreds of data sources and support complex and varied use cases. This includes self-service visualizations, interactive dashboards, natural language search, and powerful mobility functions. AI and machine learning support augmented and predictive analytics.
Pros
- Comes with built-in connectors for hundreds of data sources and services, including all major cloud platforms.
- Strong support for both structured and unstructured data.
- Highly rated for ease-of-use, including analytics dashboards and interactive visual exploration features.
- Provides rich and varied reporting and visualizations.
Cons
- Lags behind competitors for collaboration and social BI features.
- Users rate governance and metadata management below other BI solutions.
- The software can present a steep learning curve. Training may be required to use the platform effectively.
SAS Enterprise Guide
Key Insight: SAS Enterprise Guide is a Windows .NET client application that offers a self-service framework for collecting, managing, manipulating and formatting data into reports and visualizations. It relies on a point-and-click, menu-and-wizard-driven framework that includes the ability to write code and use custom macros. Thus, developers and other coders can use existing programs to create stored processes, and then run them on demand or port them to external apps, such as Microsoft Excel.
Pros
- Delivers a highly customizable BI framework through a well-developed coding platform and macros.
- Strong IT-managed role-based security along with powerful data governance features.
- Handles huge data sets while delivering fast performance.
- Strong support for Microsoft Office, including Excel.
Cons
- Overall complexity can present challenges for non-technical users and those with limited coding knowledge.
- Expensive and sometimes confusing price structure.
- No support for Python or R tools.
Sisense Fusion Analytics
Key Insight: The platform delivers a highly scalable and flexible self-service framework for conducting enterprise grade BI. The vendor’s focus is on infusing “intelligence everywhere” through extended data discovery in the cloud and on-premises, dashboards and integration APIs. Sisense offers strong AI and ML support, and powerful data visualization capabilities.
Pros
- Offers data connectors for almost every major service and data source.
- Delivers a code-free experience for non-technical users, though the platform also supports Python, R, and SQL.
- Provides a wide array of templates that automate BI and embed actions into applications and processes.
Cons
- Can present a steep learning curve.
- Users complain that errors and problems can be difficult to trace.
- Some complaints about bugs and stability issues.
- Mobile device support not as strong as others in the BI space.
Tableau Desktop
Key Insight: Tableau has emerged as a leader in BI and analytics with a framework that supports rich visualizations and storytelling. It offers appealing and highly customizable dashboards, and it can accommodate huge data sets. Tableau Desktop connects to hundreds of data sources, both on-premises and in the cloud. It includes drag-and-drop functionality along with support for AI and ML.
Pros
- Delivers outstanding visuals.
- Strong data integration and automation features.
- Includes powerful data management and presentation features.
- Supports most types of devices and operating systems, including all major mobile platforms.
- Offers 24/7 support.
Cons
- Steep learning curve for setting up data frameworks.
- Expensive, with complex and inflexible pricing model.
- ETL capabilities are not as advanced as other BI and analytics platforms.
SAP BusinessObjects
Key Insight: SAP offers sophisticated business intelligence and analytics capabilities through its BusinessObjects intelligence suite. The platform serves as an on-premises BI layer for SAP’s technology platform, including SAP Business Warehouse and SAP HANA. It delivers a centralized suite for real-time data reporting, visualization and sharing. It also supports enterprise performance management features such as planning, reporting, query and analysis, and enterprise information management.
Pros
- Offers powerful features and capabilities, including data ingestion and automated reporting.
- Integrates well with numerous applications and cloud platforms.
- Strong Excel spreadsheet and Microsoft Office integration.
- SAP offers solid service and support.
Cons
- Some users say that the interface and dashboards could be more user-friendly and more customizable.
- Collaboration and social BI not as developed as competitors.
- Expensive with somewhat complex pricing model.
Tibco Spotfire
Key Insight: The self-service BI and data visualization platform incorporates a visually appealing interface along with strong AI features to deliver advanced data search capabilities. This includes natural language search, AI-driven recommendations and direct manipulation of data. The platform is designed for line of business users and data scientists. It includes more than 60 native connectors and extensive support for APIs.
Pros
- Extremely flexible and highly customizable.
- Supports extremely large data sets.
- Offers excellent data visualization tools and options.
- Highly rates customer and technical support.
Cons
- Lags behind competitors in mobile exploration and authoring.
- Collaboration and social BI tools are not as advanced as others in the BI space.
- Presents a steep learning curve.
BI Software Tools: Additional Market Leaders
Birst
The analytics provider focuses on pre-built industry and role-specific content and metrics to power BI throughout the enterprise.
Google Charts
Google’s free data visualization tool works with JavaScript to assemble data and generate presentations and reports.
HubSpot
The CRM data platform addresses marketing through customer insights. It features an appealing interface and robust analytics tools.
IBM Cognos Analytics
IBM delivers rich BI insights through reporting and data visualizations. The platform taps Watson AI and machine learning for predictive analytics and other features.
KNIME
The free, open-source data analytics solution supports data integration, modeling and visualization capabilities.
RapidMiner
The platform generates a wide variety of data insights through AI, including predictive analytics.
ThoughtSpot
Delivers AI-driven analytics through powerful data ingestion along with dashboards and visuals.
Xplenty
The platform supports ETL and reverse-ETL functionality within a highly scalable BI and analytics platform. It delivers strong compliance and security features.
Zoho
The self-service BI tool delivers robust uses powerful connectors and intuitive dashboards to deliver reports and visualizations.
Business Intelligence Software Tools: Vendor Comparison Chart
|
Analytics Tool |
Pros |
Cons |
|
Domo |
Powerful data ingestion and excellent dashboards
|
May require add-ons |
|
Microsoft Power BI |
Excellent interactivity and top-notch visualizations
|
Not ideal for use with non-Microsoft applications and products |
|
MicroStrategy Platform |
Powerful automation; highly flexible
|
Expensive, interface can be challenging |
|
Oracle Analytics Cloud |
Suitable for non-technical users; strong AI and data governance
|
Interface isn’t as modern as some users would like |
|
Qlik Sense |
Powerful and versatile platform with excellent connectivity to data
|
Lacks in collaboration and social BI; steep learning curve |
|
SAS Enterprise Guide |
Highly customizable; excellent governance and security features
|
Complex and can be expensive |
|
Sisense Fusion Analytics |
Outstanding data connectivity; offers numerous templates that automate BI |
Steep learning curve
|
|
Tableau Desktop |
Outstanding UI and UX; excellent visualizations |
Expensive; could use more ETL features
|
|
SAP BusinessObjects |
Powerful features and strong integration with other cloud and data platforms |
Lacks collaboration and social BI features; pricey with complicated licensing model
|
https://www.eweek.com/big-data-and-analytics/bi-tools/
