What Gartner says about the top BI tools of 2022
Each year Gartner publishes a report that takes a closer look at the top-performing business intelligence vendors. This year’s report was 42 pages, which would take several hours to get through. There’s no need to read the entire report in order to understand the main point, though; you could also examine the two-dimensional matrix that maps all 20 vendors in the report. To determine a vendor’s place on the graph, Gartner uses criteria like market understanding, product capabilities, innovation, product strategy, company viability, pricing, and more.
The graph is divided into four different quadrants, with the highest-rated BI tools being assigned to the “Leader” category in the top right quadrant. This year, only three BI tools made it into this category.
Which capabilities do the best BI tools include?
If you wanted to make an objective evaluation of a BI tool for yourself, you’d need to know what to look for. Once you’re aware of what it can do, you can determine if it would make a good fit for your organization. These are the top capabilities that a good BI tool should have:
Data Analytics
- Interactive dashboards should let end users explore data freely, no matter what they’re exploring. This includes generating reports, working with huge data sets, or viewing performance overviews. This helps them uncover connections that would have been hard to find with a query-based BI tool.
- A fully functioning mobile version of the business intelligence tool lets users stay connected even if they can’t access their main desktops. Dashboards that are optimized for smaller screens are one feature that will aid them in navigating the BI tool on their mobile devices without losing functionality.
- Data visualization lets stakeholders view data according to the type of visual that suits it best. It could be a map, a chart, or a graph. A great BI tool will use AI to show the shape of the data and identify outliers as well.
- Augmented analytics helps users connect with data by using machine intelligence to raise their data literacy. This also increases their efficiency, because they can be automatically notified of relevant insights like trends or correlations. Thanks to augmented analytics, they don’t have to spend all their time looking for this information themselves.
Data Management
- Governed self-service is essential to keep a balance between self-service discovery and protecting data integrity. User access, publishing, and sharing should be managed through rules-based governance. This preserves data quality and makes the insights you derive from your data more trustworthy.
- End-to-end data integration will deliver consistent insights to all users by combining, transforming, and cataloging data. Ideally a BI tool will offer this capability without making users invest in outside products or write extra code.
- Scalability lets a BI tool handle any amount of data effortlessly, whether it’s historical data or real-time data. This could also include the capacity to add, modify, or remove records in order to keep data as fresh as possible.
- A flexible cloud strategy lets your organization focus on gaining insights, not on building new infrastructure in order to fully utilize the BI tool. With a multi-cloud, platform-agnostic architecture, you’ll also have the option to update your data storage solution in the future if it’s ever needed. This enables the BI tool to operate in any environment with full scalability and excellent performance.
Ease of Use
- Embedded analytics allows users to explore data and make discoveries no matter what application, portal, or process they’re using. A BI tool should be incorporated in the whole enterprise ecosystem so that stakeholders can make data-driven decisions without having to interrupt their workflows.
- Data literacy is a key skill that users need to navigate a BI tool, but the BI tool should also meet them halfway. With natural-sounding language and an easy-to-use interface, stakeholders will be able to explore the data and make informed decisions without having to learn how to use a complex interface first.
- A single interface keeps the user experience consistent, which is important if stakeholders of different skill levels will be using the BI tool.
Additional considerations to help you make the right choice
Finding a business intelligence tool that completes a certain checklist is great, but you should also think about a few other factors that could affect a BI tool’s suitability for your organization.
Total cost of ownership – You’ll probably be looking at pricing plans when comparing BI tools, but you should also look at additional expenses that could be incurred. These expenses could include set-up costs, expansion of infrastructure, maintenance fees, and more.
Data integration – End-to-end analytics and data integration lets you concentrate on finding insights instead of managing a complex technology stack.
Passive data vs. active data – If you want to make decisions based on real-time data, you’ll need a BI tool that brings you active rather than passive (historical) data. Analytics pipelines can deliver data to you as soon as it becomes available.
In conclusion
The first step to choosing the best BI tool is to figure out what your organization needs from it. After that, you can compare the top choices, determine which one fits the criteria you’ve established, and pick the one that will help your organization grow far into the future.