Enterprises today commonly cite wanting to become data-driven as a key strategic goal in the coming months and years. Of course, achieving this objective successfully entails a major commitment at every level, including developing a data-savvy culture and implementing real decisions driven by data. However, one of the very first decisions that companies make when it comes to overhauling or updating their data strategy is which business intelligence (BI) and data analytics platform to deploy.
The underlying choice of BI platform has a ripple effect throughout the rest of the data strategy, as it determines how users are able to interact with tools and the nature of the insights they can produce — both major factors in how they are subsequently able to harness data for making decisions in ways capable of measurably affecting performance outcomes.
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Thus, choosing a business intelligence platform is an important step, not to be taken lightly. Acting too hastily or choosing the least expensive option upfront can have negative ramifications on the longer-term data strategy.
Here are some areas of consideration for comparing platforms before your enterprise invests in BI and analytics technology.
While legacy business intelligence systems tended to rely solely on on-premises hardware, many enterprises now are opting for hybrid or cloud-based solutions.
Running BI and analytics in the cloud requires less up-front, physical investment in equipment and also tends to offer more scalable options for growing companies. Which model your company chooses depends on many factors, including whether you plan to integrate your existing solution and your IT strategy.
BI technology is capable of bringing a substantial return on investment, but leaders will want to carefully compare costs before approving funds for any purchase.
The first step is comparing price quotes from different vendors, including the cost of the software, optional add-ons, start-up fees, licensing costs per user (if applicable), expected maintenance expenses and more. Considering all these factors will allow your organization to calculate a total cost of ownership for each platform, which you can then compare head-to-head — even if the platforms have different pricing models.
A best-fit BI platform suits your enterprise’s current user base while also planning for six months, a year or five years down the road. The scalability, or lack thereof, will limit how many users are able to comfortably use BI tools — and the speed and cost of them doing so.
No matter how great tools look on paper, it’s important to take them for a test drive with the “average” user experience in mind. Here’s an example of a question worth asking during this shopping phase: Is the interface navigation understandable and intuitive, even for employees who are working directly with BI reporting and analytics tools for the first time?
Enterprises continue to struggle against low adoption rates, meaning that many users are still not yet including the BI tools available to them in their workflows and decision-making processes. There are many reasons why analytics adoption rates are an ongoing challenge for organizations, but clunky, complicated and otherwise frustrating tools can certainly contribute.
Not all BI platforms are created equal in terms of the actual tools they provide. For instance, a self-service search analytics tool is great for when employees want to run specific queries — but your company may also benefit greatly from an AI-powered data mining engine that can detect patterns missed by previous queries. The lesson? Take the time to explore the capabilities of the various tools offered by various vendors to choose the software most conducive to meeting your company’s needs.
Keep these considerations in mind when your enterprise is undertaking the task of choosing its next BI platform. A worthy investment will fulfil the company’s needs in all of these areas, making it a beneficial solution for months and years to come.