Traditional vs. Modern BI Buyer Trends Report

by:
on October 14, 2016

The BI market has witnessed a fundamental transformation over the past decade. Traditional systems focused on reports generated by the IT department have given way to “self-service” tools that allow nontechnical users to analyze data with minimal IT involvement.

Visual data discovery tools are one of the most important categories of self-service BI. They allow users to model and query data using a graphical user interface (GUI), as opposed to performing these tasks via a programming language like SQL.

At Software Advice, we help hundreds of buyers find the right BI solutions for their needs each year. We’ve taken a random sample of these buyer interactions to find out just how many buyers are looking for visual data discovery tools as opposed to traditional systems.

We also drill down into data discovery buyer pain points, current adoption rates of data warehouses and self-service tools among data discovery buyers, the types of businesses that are in the market for visual data discovery tools and more.

Key Findings

Our analysis of buyer interactions uncovered three key trends:

Buyer Preferences for Visual Data Discovery/Self-Service Solutions

The most striking finding is that in a random sample of 200 BI buyer interactions, nearly half of the buyers are seeking visual data discovery tools, as opposed to integrated BI suites or best-of-breed solutions for advanced analytics, extract, transform and load (ETL) etc.

In most cases, these buyers are looking for tools with robust ad hoc reporting, attractive visual interfaces and strong capabilities for creating and sharing dashboards.

Our analysis also revealed that, in 35 percent of interactions, buyers specifically mentioned the need for custom reporting with minimal reliance on the IT department or an easy-to-use interface for nontechnical users such as top executives.

Finally, we found that 11 percent of buyers have already deployed self-service tools such as Tableau and Qlik Sense.

All three of these findings show a strong market shift toward the self-service BI model. Buyers of traditional platforms are increasingly demanding self-service capabilities and emphasizing ease of use, just like data discovery buyers.

Many Data Discovery Buyers Haven’t Yet Adopted Data Warehousing

One particularly interesting point our analysis uncovered is that visual data discovery tools are increasingly being used at organizations that don’t use data warehouses.

Current Adoption of Data Warehousing/Self-Service BI
Among Data Discovery Buyers
Traditionally, data discovery tools were deployed alongside existing BI systems based on data warehousing. However, more than two-thirds of our sample of visual data discovery buyers don’t yet have a data warehouse in place.

Because data discovery solutions allow business users to directly access data and develop data models themselves, smaller organizations may no longer even need to warehouse data to perform complex and rapid analyses. They can simply connect the tool to their Excel files or SQL databases and start analyzing.

Indeed, 10 percent of buyers are already in the market for another self-service tool, even though they don’t yet have a data warehouse in place.

While traditional data warehousing isn’t going to disappear anytime soon, the above chart does show that many organizations now see a greater need for visual data discovery than traditional data warehousing.

Reporting, Analytical Sophistication and Visualization Are Major Pain Points

In our buyer interactions, we record the top pain points buyers have with their current solutions (or lack thereof). When we drill down into the woes of data discovery buyers in particular, we can spot a few interesting patterns:

Top Pain Points of Data Discovery Buyers 
It’s hardly surprising that reporting is the top pain point among data discovery buyers. With traditional BI systems, IT is largely in charge of producing reports. If business leaders and analysts want to report on new metrics, it can take weeks or months for IT to catch up. In other cases, the constraints of the BI system itself (data integration issues, ease-of-use issues etc.) limit the usefulness of reports.

Reporting was also the top pain point in our overall sample of BI buyers, cited in 13 percent of the buyer interactions we analyzed.

Two of the other pain points, however, are quite intriguing. More than one in 10 buyers specifically cited analytical sophistication as a pain point with their existing tools, and buyers cited weaknesses in data visualization capabilities at the same rate.

With traditional BI solutions, the data model encoded in the semantic layer constrains how analysts can query historical data (see our explanation of this problem here). When analysts are able to develop their own data models, however, they have much more freedom to blend the data sources they need in order to discover new insights.

Additionally, the visualization capabilities of data discovery tools make analysis much simpler by allowing analysts to manipulate data using drag-and-drop gestures in a GUI, instead of writing drawn-out SQL queries to get the data they need.

Such capabilities are clearly more important to buyers than classic issues such as support, mobile compatibility and siloed analytics (e.g., an analytical tool embedded in an HR system that isn’t integrated with other data sources).

Health Care & Manufacturing Are the Major Verticals Interested in Data Discovery

Data discovery tools of course have broad applicability in business analytics. However, certain industries (insurance, financial services, health care etc.) rely far more heavily on trained analysts than others.

Not surprisingly, buyer interest in data discovery tools tends to vary greatly by vertical:

Buyer Interest in Visual Data Discovery by Industry
We can see that interest in visual data discovery is particularly explosive in health care and social services. Manufacturing, interestingly, comes in before financial services in terms of buyer interest in visual data discovery.

However, these buyers are more focused on developing dashboards to deploy across the organization than on serving analyst work groups performing daily ad hoc analyses to diagnose performance issues and identify opportunities.

When we look at buyers who’ve already deployed self-service tools, we can see that manufacturing clearly leads the pack:

Self-Service Tool Adoption by Industry
Another interesting demographic present in both of the above charts is software vendors/IT consultancies. These organizations are primarily looking to improve analytics on customer data. Given the highly competitive nature of most software-as-a-service (SaaS) markets, it’s not surprising that businesses are turning to analytics to gain an edge.

Buyer Demographics

Many of the data discovery buyers in our sample have fairly deep pockets. Over a fourth are generating more than $300 million in annual revenue:

Data Discovery Buyer Size by Annual Revenue 
This chart shows that data discovery is still largely an enterprise market. That said, 31 percent of the buyers in our sample are generating $50 million or less in annual revenue, so full-blown expansion into the SMB space is only a matter of time.

The buyers in our sample also have plans to roll out data discovery solutions to fairly large groups:

Planned Number of Users for Data Discovery Deployments
Around a fourth of our sample is planning to use data discovery tools in small work groups (10 analysts or fewer). However, a good number are planning to roll out dashboards to broader populations of end users.

These more sweeping plans, where the data discovery tool is one of the primary ways in which dashboards spread through the organization, also demonstrate the influence of self-service BI on traditional BI territory.

Conclusions

It’s clear from the analysis we’ve performed that businesses are increasingly turning to data discovery solutions instead of traditional BI platforms. While many organizations are seeking to supplement the capabilities of their existing systems with visual data discovery, others are foregoing the data warehouse entirely.

Additionally, many buyers are planning massive dashboard rollouts for their data discovery tools, indicating that these tools are replacing enterprise platforms focused on IT-directed reporting for basic purposes such as tracking key performance indicators (KPIs).

Buyers are increasingly guided by concerns with analytical flexibility, data visualization and even the aesthetics of the tools they’re using. In particular, more than a third of both data discovery and traditional BI buyers mention ease of use as a primary selection criterion.

These findings point to a BI market in transition, guided increasingly by a concern with democratic data access and friendly interfaces for less technically inclined users. This is in contrast with the traditional mission of setting up a BI system to serve as a tightly controlled “single source of truth” about business performance across the organization.

Note: You can find more information about our methodology here.

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