Beyond the ‘Dashboards Are Dead’ Rhetoric: from Origins to AI-Driven Futures

A Comprehensive Analysis of the Real Story of Business Intelligence’s Evolution

Over the past few years, a significant discourse has arisen within the Data & Analytics domain, questioning the vitality of Business Intelligence (BI), with some of the thought-leaders of this space even suggesting its demise, like the “Dashboards Are Dead” campaign by various vendors, such as Thoughtspot, Yellowfin, Count, iGenius, and others. Yet, the unfolding narrative warrants an exploration of the value that self-service dashboards and similar innovations have injected into businesses. According to Gartner’s analysis, the year 2022 witnessed a robust growth of over 8%, propelling the Analytic Platform software market to a staggering $31.87 billion.

With these figures in mind, a logical assumption emerges that BI tools are poised to retain their pivotal role in our professional landscape. Furthermore, it’s foreseeable that these tools, armed with substantial resources, will ingeniously reinvent themselves, birthing novel technologies to align with the ever-evolving landscape encompassing web 3.0, the metaverse, Generative AI, LLM technologies, and the forthcoming unknowns.

“The Driver For Business Intelligence Solutions Inception”

The genesis of BI tools is traced back to the need for democratizing analytical expertise, shifting it from the confines of IT departments to business units. The pursuit was to expedite data-driven decision-making by untangling dependencies and restraints. 

The first wave of BI solutions started at the beginning of the 90s in the shape of flat reports with the ability to slice and dice the data by different dimensions. By harmonizing data from disparate sources into a consolidated dataset, these tools expedited the derivation of business insights. SAP Business Objects, IBM Cognos, and more led this phase.

As the market evolved, new tools with new capabilities were introduced in the 2010s. The most conspicuous innovation was the introduction of a visualization layer, ushering in interactive dashboards and visuals that democratized comprehension across the organization. This user-friendly interface enabled everyone to understand the figures quickly, engaged more users and was a key factor in making a company a data-driven organization.  

As this new generation of BI tools became more popular, the existing and new vendors came up with further technological advancements, such as in-memory capabilities to improve responsiveness, shifting from desktop to web applications via HTML5, expansion of integrations, embedding capabilities, cloud nativeness, and more.  

The Business Intelligence market has become convoluted and fragmented, with each vendor introducing their specific angle and differentiation. Customers mainly bet on the biggest players, such as Tableau, Qlik, and MicroStrategy, which created the ripple effect of the much-needed consolidation and support of the wide variety of use cases within the same tool. The transformational journey many of these tools undertook, from their rudimentary origins to their present forms, offers an intriguing narrative. However, the essence remains that BI tools, like snowflakes, remain singular in design, with no two tools being identical. This uniqueness has led most BI practitioners to gain hands-on familiarity with only a limited set of tools throughout their professional tenure.

The Age of Business Intelligence Tool Specialization

Recognizing this, I believe that delving into the disparities within the elements of BI tools would be beneficial to existing and aspiring Analytics professionals for the understanding of the current uniqueness and overlaps of the vendor’s offerings and maybe for inspiration to switch camps:

• Evolution – the background each vendor comes from, their approach from inception.
• Technology and Architecture – the way data traverses from sources to visualizations, whether it runs solely on a web app or includes desktop and server apps, the different components each vendor uses, the relationship between a dashboard and its visuals, whether their dashboards support multiple tabs and the type of containers they use to manage their different entities.
• Focus and strengths – the vendor’s current focus, core feature, capability, or strength, what they try to accomplish, and how they do it.
• Future – my thoughts on what the future entails for each BI provider. 

Certainly, other nuances and idiosyncrasies differentiate these tools, but I’ve endeavored to uncover commonalities for a deeper grasp of their behaviors and approaches.

And while dozens of vendors populate this landscape, making this read brief and insightful led me to spotlight only a handful. I selected the vendors that are used by most of the customers at illumex.ai, granting me an intimate familiarity with them:

• Tableau (a Salesforce company)
• Microsoft Power BI
• Looker (a Google Cloud company)
• Thoughtspot
• Sisense
• Amazon Quicksight
   

Disclaimer: I collected information while writing this piece from the vendors’ websites, Gartner, G2 Crowd, and other sources. I’ve tried to focus on their structure and approach, which are not expected to be subject to frequent changes. That being said, it might be that some more detailed pieces of information would change in time. I encourage you to leave a comment if you notice any misalignment with the structures of the up-to-date tools.  

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