Analytics Smackdown: Traditional BI vs. Self-Service

In the world of BI, it’s all about the business user these days. Forget about those old tools that only data scientists or the IT department could use: In today’s fast-paced business environment, who can afford to take weeks or months to prepare a report?

By Daniel Humphries

The future is self-service, data discovery and quick insight—bringing power to the business users!

Indeed, in the 2015 Magic Quadrant for Business Intelligence and Analytics platforms, Gartner placed self-service data discovery tools designed for end users firmly in the forefront of the leaders’ quadrant.

Related: The Tools That Power Business Intelligence

Data visualization specialist Tableau held top position—and it was noted that many of the “traditional” vendors were racing to catch up by producing their own user-friendly tools that minimize IT involvement.

But how does traditional BI vs. self-service BI really pan out?

Is this the new BI: a revolutionary, ready to liberate the data and unleash the power of analytics for the non-specialist?

And is this really “traditional” BI—not so easy on the eyes, and decidedly past its prime?

Or are reports of traditional BI’s demise greatly exaggerated? What type of tools should today’s buyer really be looking for?

What are the benefits of traditional BI vs. self-service BI? We spoke to the experts to get their take on the present and future of BI software.

Traditional BI—Dead Tech Walking?

The complaints about traditional BI software are well-known:

  • It’s slow
  • It’s rigid
  • Creating reports is time-consuming
  • It places a burden on IT

Perhaps when there was no other choice it made sense to invest in these tools, but in today’s world, well—what are they good for?

Paul Nashawaty is director of product marketing and strategy for the data connectivity and integration division of tech firm Progress. He suggests that traditional BI is indeed living through its own End of Days scenario.

In the past, there was call for a tool dedicated to working with structured data culled from a single source—but today’s business environment is very different.

“[T]he days of moving data from external sources to a specific data warehouse are gone, as we continue to see the amount of data growing at an incredible pace,” says Nashawaty.

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Organizations thus need to be more strategic about how they access information in real time—and for this purpose, flexible, simple-to-use self-service tools are best, Nashawaty explains.

Better yet, the comparatively low entry cost of self-service tools has allowed SMBs to exploit their data in a way that was once only possible for much larger companies.

“Businesses of all sizes can utilize subscription-based models for real-time access to data to help support every business decision,”Nashawaty says. “The only organization[s] that may want the pendulum to swing back to traditional BI [are] enterprises, [which] have now lost their competitive advantage due to self-service tools.”

Indeed, says Nashawaty, “everyone” is shifting to self-service. And little wonder: Faced with a choice between the two, he says, “self-service tools will give you the same results with less cost of entry, so it doesn’t make sense to invest in both types of tools.”

Traditional BI: Alive and Kicking?

Tapan Patel, global BI manager for software giant SAS, has a different take. He says that while demand is definitely “flat or slowing” for traditional BI, the need for functional reporting on day-to-day business operations remains—and that, in certain use cases, traditional BI still works well.

“Organizations from within all industry verticals always have a need for functional, operational, financial [and] compliance reporting and dashboarding … and hence have adopted enterprise BI tools for years,” says Patel.

“It predominantly meets the needs of answering two questions—‘what happened (historically)’ or ‘what is happening now (operationally)’—in a standardized, scalable manner.”

Southard Jones, vice president of product strategy at BI firm Birst, does not think that traditional BI is dead, either. At least, he says, isolated data can reveal some interesting, “if very limited” reference points for individual problem sets. So perhaps traditional BI lives on, but its glory days are indeed in the past.

As for who could benefit from it, “[o]rganizations or departments [that] are looking for highly scalable, centralized, standardized reporting with guided analysis are good candidates for this approach,” says Patel.

Related: Should You Automate Business Intelligence?

Self-Service Tools: Increasingly the Shape of Things to Come

Self-service tools may be much more flexible and easy to use—but not all of them are created equal, and many come with limitations.

Current business demand is for tools that:

  • Are user-friendly
  • Are intuitive
  • Are interactive
  • Allow users to access or extend not just IT-curated data sources, but also non-traditional ones

But while most solutions are good at the user-friendly aspects, the technology can run into trouble when it comes to the extension of data access: Jones points out that some of the newer tools fail to provide “the accuracy and scalability” of traditional BI.

“The growing reality in the business intelligence market today is that it is not a question of either/or. You need to provide governance and self-service,” Jones explains.

Indeed, good data governance is crucial. For instance, if multiple business users are creating their own reports and dashboards, then there is a risk that the democratization of data could lead to analytic chaos.

Business users are often unaware of the complexities of data preparation and the risks involved in getting it wrong. Without an authority guaranteeing strong data governance, they may miss mistakes in their own data, and draw the wrong conclusions—or different business users may draw upon poorly curated data sets, and reach different decisions.

To prevent this, IT will most likely need to get involved.

Patel agrees that data governance is one of the important criteria that “often gets overlooked during the product evaluation and selection phase.” Self-service data discovery, BI and analytics touch many users, and rely on multiple creation and delivery touch points.

But that’s not all. Patel suggests that when evaluating systems, buyers should consider:

  • Requirements around accessing new data and validating it
  • Sharing of metadata
  • Certifying information insights for broader sharing
  • Setting up criteria for replicating and retiring content
  • Business metadata templates

The good news, adds Patel, is that “we already see a shift where a single tool can meet the needs of not only business users (i.e., data discovery, interactive reporting and dashboards and self-service analytics), but also is IT-enabled (i.e., self-service data preparation) in a well-governed, managed approach.”

Conclusions: It’s Not Just About the Tools

So what makes for a really great BI tool, and what are the benefits of traditional BI vs. self-service BI? Jones is clear on this point.

BI, he says, gets powerful when you can access multiple data sets and “get a single, cohesive data fabric that looks at all of the organization’s data that someone can query. The system then knows how to traverse the data and answer questions.

“It’s not just putting a bunch of data in a big database, which is an outdated way to think about it. Instead, it’s about creating a data fabric in which all the routes between data are mapped at the application level.”

Of course, the market is developing all the time. And while the heyday of traditional, IT-centric BI may be in the past, self-service tools are still maturing, and some support governance, scalability and complex queries better than others. Buyers should be alert to such considerations when researching the tools they want to invest in.