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Traditional BI vs. self-service BI shouldn't be a choice

Traditional BI vs. self-service BI isn't a choice organizations need to make, but rather a partnership that requires elements from both to bring effective data use to users.

Traditional vs. self-service business intelligence doesn't have to be an either-or choice. Both bring different tools and benefits to organizations.

Many organizations are leaving value on the table by solving problems through conventional methods, which can take months or years to resolve. Business intelligence helps companies extract actionable insights from their data much quicker -- and the market is booming.

But to really make these data-driven insights impact a company's bottom line, they need to be in the hands of employees who can make use of them. Only 13% of senior decision-makers use analytics on a daily basis, but the trend is moving toward making more use of data, according to a survey released by IDC and Sisense in 2021.

Nearly all employees will be regularly leveraging data to support their work. Putting this power into the hands of employees who are not themselves data scientists requires a new approach to business intelligence, which is where self-service BI comes in.

Traditional business intelligence platforms offer tools to transform data into actionable insights that organizations use to make strategic and tactical business decisions. This requires experts in statistics, analytics or data science. Self-service business intelligence puts this power in the hands of ordinary end users at a time and place where they need those insights to make business decisions.

Chart showing the differences between traditional BI and self-service BI
Traditional BI vs. self-service BI operations.

Not a 'silver bullet'

There's a myth that self-service BI can take away the perpetual pain of not having the right report when it's needed. But self-service BI is not a silver bullet vs. traditional BI, said Igor Ikonnikov, director of research and advisory for enterprise architecture, data and analytics at Info-Tech Research Group.

"Self-service BI would be one of several facets or pipelines of reporting and analytics," he said. "It's not a complete replacement for traditional BI."

In addition, implementing self-service BI takes work. Experts must plan the capabilities that end users need, architect the data flows, set up the appropriate governance structures and make sure the user interface works as intended.

Depending on the kind of self-service BI that's being set up, the end users may require some training.

"I don't think it would be reasonable to force employees who are great specialists, but are reluctant to learn new BI technologies, to engage in self-service BI," Ikonnikov said.

Instead, companies should offer the appropriate level of self-service BI to meet user needs. For example, some users might only want to learn how to customize views in pre-built dashboards. Others might want to be able to create new visualizations. Some very advanced users may want to get all the way into data engineering.

Self-service BI has limited capabilities compared to traditional BI, but there's a common misconception that self-service BI can do everything traditional BI does, said Jay Yu, vice president of product and innovation at TigerGraph, the provider of a graph analytics platform.

Complex analytics may still require domain expertise and advanced data analytics skills. Even when the self-serve BI platform does have particular capabilities, limited user skill levels can hamper effectiveness. It would be a mistake to think that self-service BI tools require zero training, Yu said.

"While these tools are designed to be super simple and easy for business users, some level of initial training is still required in order to leverage their full power," he said.

Self-service BI still requires support

In addition to training users how to use self-serve BI platforms, companies should also be prepared to support self-service BI in other respects. For example, all BI tools need data, which requires expertise in setting up data pipelines.

Just because it's self-serve doesn't mean any data that users need shows up automatically -- and it shouldn't, said Mathias Golombek, CTO at Exasol, an analytics database management software company.

[Self-service BI is] not a complete replacement for traditional BI.
Igor IkonnikovDirector of research and advisory for enterprise architecture, data and analytics, Info-Tech Research Group

For example, organizations must comply with data access regulatory rules. They can't grant access to sensitive data to the whole organization, Golombek said.

Plus, with more and more people accessing data, there is an increased risk of creating too many disjointed and unaligned reports across the business, he added.

"Replications or different interpretations of the same data can often lead to incorrect assumptions and contradictions," Golombek said.

In addition to setting up data literacy programs to train employees on data, organizations should also embed trained data engineers into their business units to address data management issues.

Tips for self-service BI success

Successful self-serve BI starts with good, well-organized data. That takes knowledge of the data itself, data modeling work and presentational layer work, said Myles Gilsenan, vice president of data, analytics and AI at Apps Associates, a technology consulting firm.

"Just connecting a BI tool to a bunch of data sources with no modeling work is often a recipe for disaster," he said.

Then, the data needs to be modeled and presented to users in a way they can understand and not get themselves in trouble, Gilsenan said. To prevent situations where there are multiple versions of the truth presented to different employees, guardrails and distribution protocols should be established.

The final piece is keeping the data safe. Preventing unauthorized access requires tightly designed data security.

Bottom-line benefits

Data-driven organizations are seeing annual growth of more than 30%, according to an Accenture report released in May 2021. These are organizations that integrate data analysis into the core of their businesses and use insights from data to transform business processes.

While 87% of employees believe in the value of data, Accenture reported only 25% are capable of using that data effectively, and 74% feel overwhelmed and unhappy when they work with data.

"Data can be a very intimidating concept for people," said Dave Hurt, CEO and co-founder at Verb Data, an analytics dashboards company.

When it comes to self-service BI, companies focus more on curation than customization, as well as creating strong foundations, paths and guide rails for users to follow, Hurt said.

"Providing a baseline allows people to see examples to build from and they tend to be a lot more comfortable," he said.

In the end, the effort is worth it.

"Data is the crown jewel of an organization, and every company across all industries from retail to finance are looking for ways to use data to their advantage," said Terri Sage, CTO at 1010data.

When companies do it right, they can use the data to personalize marketing, improve sales, optimize operations and much more, he said.

Next Steps

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