Today’s A:360 discusses why BI software alone is not enough to accomplish your analytics objectives. BI tools are an integral (and necessary!) part of your analytics strategy. However, they alone will not solve all of your objectives for data and analytics. Learn why this true and how you can properly leverage these technologies.

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Hey everyone. Welcome to today’s A:360. My name is Brewster Knowlton, and today we’re going to be talking about why BI software alone is not enough for your analytics programs.

As business intelligence and analytics becomes more popular across industries, we’ve seen the rise in the focus of products like Information Builders’ WebFOCUS, Tableau, Qlik and PowerBI. These advanced visualization tools can often make it appear as if you just need to purchase the product and then you’re good to go. In this podcast I really want to dispel that myth.

BI software alone is not enough. You have to have more than just the technology.

You can’t simply purchase a tool to solve your analytics solutions. There are other crucial components to building a successful business intelligence platform, and we’re going to talk about why these visualization tools are not the magical fix in today’s podcast.

Many BI tools are great for visualization, dashboarding, even some of them have ETL or data mapping components to them as well, but alone they’re not enough. Being able to utilize these technologies alone implies that you understand the business processes, that you’ve understood all of the data sources that you need to get at, you have a roadmap and a plan in place, and you have staff that know and are capable of turning data into information. All of these different components that critical aspects of a business intelligence program, those are things that you need in advance or in conjunction with these BI tools. So, these software products alone will not make your BI program successful.

Many of these applications will advertise that you don’t even need a data warehouse to function with them properly, and that these products can capture and model the data themselves. This often assumes that your data is nearly perfect. How many of you can say, “Yes, my data is perfect”? I’d be shocked if anyone listening to this was nodding their head yes to my question (Or isn’t a liar).

So, the challenge with these tools is they can be used in various ad hoc situations to create some data mappings and other important functions, but this is not a true ETL. That is not an enterprise focus. These are one-off situations. Again, there are software and applications that may work for some situations, but we want to encompass a variety of tools and strategies to use for our enterprise analytics platform. Relying solely on BI technology Is not going to solve all of those problems for you.

Now, that’s not to say that these technologies are not vital, because they are absolutely critical to the success of your business intelligence or analytics program. You have to have a technology that is going to transform that raw data into visualizations, into dashboards and make it easily digestible. We’ve mentioned this idea of a central BI portal while talking about the data strategy and what is entailed in those strategies in past podcasts and articles. These BI solutions, these visualization and dashboard technologies, though are crucial to the plan, alone they are not the magic bullet.

These solutions alone are not going to solve your problems and I just want to be very clear that any organization that purchases one of these tools thinking it will be the end all be all, is going to be going down a long road that won’t lead them to the desired or maximum results that they could achieve. Like anything, we need to understand where and when is the best time to apply each technology, and realize that there are many more components to success with business intelligence and analytics than simply having the right visualization software.

In summary, these technologies are fantastic when applied properly and are used as a single component or a critical component of your entire analytics program, but remember, they alone are not going to solve the problems. Your data strategy, your implementation roadmap, all of the other ancillary components of an analytics program are required to be put into place for these technologies to effectively work together and for you to achieve the greatest success.

That’s it for today. Thanks again for listening to today’s A:360.

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