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Traditional vs. Self-Service BI: What's the Difference?

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Traditional vs. Self-Service BI: What's the Difference?

Self-service BI applications let users focus on their questions without needing to build elaborate solutions, and allow them get the insights they need ASAP—without having to wait for IT staff to help them out.

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Slow. Inflexible. Time-consuming. Does that sound like any sensible way to get users the business insights they need to do their jobs? A few years ago, this might have been the only option for business intelligence, but now there's a fork in the road. Users can go one way with centralized BI run by their IT department, or they can strike out with modern BI solutions they can use by themselves. As you might imagine, in the traditional vs. self-service BI debate, there are pros and cons to be considered before making a choice.

Is Traditional BI the Answer?

Let's take the traditional approach first. There are reasons for this controlled BI environment to exist. When you control the data and the BI application, you have a chance of controlling the quality of the results. IT departments concerned about quality (meaning every conscientious IT department) can make sure that data is properly prepared, stored, and secured. They can build systems that offer standardized, scalable reporting, and they can give users answers to their business questions. Of course, those answers may take a little time to materialize, especially if the IT department is busy with other projects. Or if the rate of growth of data (and big data) starts to outstrip the IT department's resources for handling it.

The Self-Service BI Alternative

So, how about the self-service approach? There are now numerous business intelligence tools available that appeal to users through their simplicity and affordability, and we're not just talking about spreadsheets. Self-service BI has made giant strides to get to a point where users can access data from different sources, get insights from all the sources altogether, and make faster business decisions. The tools are typically intuitive and interactive (those that aren't tend to disappear from circulation), and let users explore data beyond what the IT department has curated.

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How About Both?

But perhaps representing traditional vs. self-service BI as a fork in the road is unrealistic. An organization may need both types of business intelligence. Functional reporting on daily business operations is still a common requirement, even if it is now a smaller part of the overall BI picture. Compliance reporting and dashboarding, for example, are still needed. Moreover, once they are set up, these functions often run happily with little or no intervention. Traditional BI still has a role to play in answering questions about what happened in the past, or about what is happening about operations now. By comparison, for questions about the future, especially spur of the moment "what if" style questions, users want more individual power and faster reaction times than traditional BI is designed to give them. In this case, self-service can be preferable.

Figuring Out That Fork in the Road

This calls to mind the advice of one expert, who said, "When you come to the fork in the road, take it!" This apparently non-sensical statement now starts to make sense. How you "take the fork in the road" and navigate between traditional vs. self-service BI will depend on several factors. Identification of suitable self-service BI use cases is one factor. Business user levels of BI understanding is another. So are data governance and the commonality (or not) of BI systems. We look at each in turn, below.

Which Self-Service BI Use Cases Make Sense?

Much of the demand for self-service BI is driven by the general use case of needing answers in a hurry. Specific examples might be:

  • A retail company wants same day answers about which products to put on special offer or how to adjust its daily online advertising.
  • A pizza chain searching for a new flavor to captivate companies is looking for "fail-fast analytics" to quickly explore test market reactions and eliminate pizza experiments that don't find favor.
  • A construction company needs to consolidate spreadsheet data sent in by subcontractors to immediately spot any signs of rising costs or delays that could jeopardize building schedules.

How Much Understanding of Business Intelligence is Needed?

If a deep understanding of BI or data science is needed for a BI application, then that application is unlikely to be self-service. On the other hand, when a self-service tool is sufficiently intuitive and allows users to focus on business results instead of underlying technology, then end-users can work independently of developers, data specialists, and the IT department. One example is smart data visualization allowing ad hoc questions to be easily asked about any part of the data and to any depth.

How Can Self-Service BI and Data Governance Issues be Resolved?

Self-service BI cannot be at the expense of clarity or confidence in the results. Self-service tools that can use data sources directly can avoid such problems. The data sources do not change, and different users can apply the same tools to check that they get the same results. There may still be a discussion about the way the results are to be interpreted, but there should never be disagreement about the sources or the consistency of the data used to get the results.

Will You Need Totally Separate BI Hardware and Software?

Cost is a factor for most enterprises and organizations. Whereas in the past you may have had no option other than to pay separately for hardware and software, now there's a better way. Instead of the older assembly line or legacy system approaches, enterprises can now move to a single-stack BI approach that provides BI to satisfy advanced users in the IT department, as well as non-technical business users. Once again, "When you come to the fork in the road, take it!"

The Future of Business Intelligence Is Self-Service

Even if both traditional and self-service BI will continue to coexist, constantly rising data volumes and accelerating business needs will mean that end-users will do an increasingly large part of BI for themselves. Good self-service BI applications will let users focus on their business questions without needing to build elaborate solutions, and get the insights and answers they need immediately, without having to wait for specialist IT staff to help them out.

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Topics:
big data analytics ,big data ,business intelligence ,self-service analytics ,data governance

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