Selecting Data Visualization ToolsBy
Finance professionals must weigh a number of factors in choosing a program to suit the data consumption within their organizations.
Data visualization can be defined as the practice of transforming raw data into visual information to distill complex concepts and support better business decisions. As Fatema El-Wakeel, Loreal Jiles, and Raef Lawson wrote in “Storytelling with Data Visualization,” “The most comprehensive and empowering uses of data visualization not only tell the story but also allow the audience to view and draw insights, identify correlations, recognize trends, and, ultimately, form their own fact-based story” (Strategic Finance, December 2020).
Taking full advantage of this business communication tool can help management accountants leverage compelling narratives and captivating visuals to interpret business results and gain greater organizational influence. Effective data visualization is no longer an optional skill. The sheer volume of available data requires we have the tools and methods needed to consume it efficiently.
MICROSOFT POWER BI
As a de facto leader in the data visualization space, Power BI enjoys a very loyal following among Microsoft users, who find the program familiar after using Excel and appreciate the compatibility with other Microsoft products, excellent charting options, intuitive features, and the standout number of non-Microsoft data connectors.
While Microsoft offers a free version of Power BI, its Pro license (which includes advanced sharing and collaboration options, embedded apps, and application programming interfaces) is available for only $9.99 per month. Should you want to share your content with nonlicensed stakeholders or if you need to use a larger data set (up to 10GB) or to keep more data in your total storage allotment (up to 100TB), as well as enjoy a handful of other niceties (higher refresh rates, geo distribution, read-only replicas, etc.), then the Premium version at $20 per month is the way to go.
When it comes to data preparation capabilities, Power Query and DAX language set their own standards, enabling Power BI users to transform data for use in their analysis and fully customize their data modeling process. Advanced analytics is also enabled via support for the R and Python scripts and respective custom visuals. Integration with Azure Data Lake storage supports enterprise-scale analytics workloads in the cloud. Various machine learning enhancements are also introduced in the form of smart narratives, anomaly detection, and sentiment and image analytics.
Arguably the most established data visualization brand on this list, Tableau managed to disrupt the traditional business intelligence landscape in 2003 by offering then-unprecedented ease of use, intuitive charts, and self-service capabilities powered by various data source connectors. Chances are that your favorite media outlets rely on Tableau to share their data stories.
A fully functional Tableau Public program is offered free of charge, though you must deal with privacy considerations as your work is available to the public. While the cloud-based Tableau Explorer license costs $42 per month, most use cases will also require addition of the Tableau Prep features for their data discovery work streams, bringing the cost up to $70 per month for the Creator version.
This mature application used to dominate the world of data visualization and still fits the bill for most real-life scenarios, offering a formidable array of data connectors, impressive visualization cachet, and a future-proof processing engine. While new users can learn to use this software right away, full mastery requires substantial training and time investment.
Like Power BI, Tableau offers various third-party add-ons from its loyal community of followers; it also supports R and Python integrations (including its own version of Python called TabPy). Unlike Power BI, which is hosted exclusively by Microsoft, Tableau can be deployed by enterprises on premises, thus offering greater control over their data. Its industry-leading in-memory engine technology, Hyper, allows efficient processing of large and complex data sets.
Since it was acquired by Salesforce, Tableau stands to achieve additional competitive advantage, including strong customer relationship management integration, enhancements to its Ask Data natural language capabilities, the power of Einstein Analytics to automate data stories, analysis of key contributing factors, and explainable AI functionality.
Dating back before the data visualization boom, Qlik had a very pronounced business intelligence focus, later transforming itself into a modern data visualization powerhouse. With the target customers being mid- to large-sized enterprises, Qlik Sense Business plan costs $30 per month, which is the midpoint of its competition. With the “standard” app size limited to 1.25GB and shared spaces peaking at 5GB, custom token-based pricing for the Enterprise edition might be a better fit.
When it comes to data connectors, you’ll likely encounter all the usual suspects, but Qlik’s ability to process Big Data repositories will be lacking compared to its competitors. When it comes to third-party data sets, Qlik limits its DataMarket to data sets it curates on its own, so the selection is going to be better vetted but more limited. The Enterprise version beats both Power BI and Tableau in terms of flexibility of access rules, user roles, and security policies. Furthermore, this level of enterprise support has an additional differentiator—centralized data governance. Another feature that makes Qlik Sense stand out is an AI-powered inference engine running the associative experience, which enables dynamic what-if results using associated parameters that weren’t part of your query.
GOOGLE DATA STUDIO
Absorbed by the Looker product last year, Google’s Data Studio (released at the end of 2018) is a mighty challenger to the more established vendors. Users seeking a completely free product could benefit by leveraging Google Data Studio’s state-of-the-art interactive drag-and-drop interface, vast charting options (further expanded by third-party add-ons), and custom formulas (à la Power BI’s DAX or Tableau’s VizQL). Existing Google tech stack users will appreciate seamless support of Sheets, BigQuery, Google Analytics, Google Ads, DoubleClick Manager, and the like. The program’s sharing and collaboration options exceed already high standards set by the competition.
If you’re late on your journey to becoming a data visualization extraordinaire, the good news is that access to training materials is as ubiquitous as the data itself. The data visualization course from IMA® (Institute of Management Accountants) and University of Illinois’s Gies College of Business might be a good place to start, and you can continue the voyage with the IMA Data Analytics & Visualization Fundamentals Certificate® program. Additionally, all four of the vendors reviewed provide their own on-demand educational resources—Power BI, Tableau, Qlik, and Data Studio.
These resources could prepare you to test any software program by trial to find the one that best suits your organization’s circumstances. We’ll look forward to your contributions to this exciting field and to your sharing your data story.