Key Criteria for Evaluating Business Intelligence Solutionsv1.0

1. Summary

Business Intelligence (BI) as a paradigm and product category has been around for decades. Arguably, though, it is enjoying its greatest popularity, adoption, and ubiquity today. Based on the notion of taking granular data pertaining to specific events or entities and summarizing it, BI has been critical to the ways business gets done.

The core BI practice of visualizing data has been drilled into us since high school math class as we plotted points on a graph. Just as it gave life to the otherwise esoteric formulas and individual numerical results we were computing back then, it succinctly conveys the meaning of business data now. BI also comprises text-based reporting. But even in the days when reporting was the mainstream way to derive useful information from raw data, the inclusion of “charts” in those reports was the apex of elegant delivery.

Data visualization was difficult then and required developers or IT personnel to craft and produce it. With each passing year, visualization has become easier, with a dwindling dependency on technologists’ support. BI platforms have helped in two ways: by providing drag-and-drop interfaces for the creation of data visualizations, and by delivering those interfaces as part of a framework of tooling that empowers IT, analysts, and even business users to obtain and model the data before visualizing it.

Not every organization wants the data collection and visualization BI experience to be fully business user-led, however.

Many enterprise organizations prefer a more hybrid approach in which IT or a centralized analytics group takes responsibility for curating, sourcing, and modeling the data, then lets business users—with sufficient permissions—access the data, explore it, visualize it, and present it. We refer to the full business user approach as self-service BI and the cooperative technologist/business user approach as enterprise BI.

This Gigaom Key Criteria report lays out the core principles of BI overall. The accompanying GigaOm Radar reports review and compare vendor offerings in the BI space, taking separate looks at enterprise and self-service BI.

Although it makes sense to divide BI platforms into these two cohorts, the fact remains that they are converging, and the distinctions are getting blurrier. All BI users have the same goal: to make the patterns, relationships, and underlying truths in data much more apparent and understandable than they can be from examination of the raw data. All of this is done with the goal of making informed business decisions based on the data and analysis of it. While data-driven decision-making may sound like modern jargon resulting from the digital transformation phenomenon, it is actually a very old concept. In fact, before most people referred to BI as such, they called it “decision support.”

In this report, we’ll cover the specifics of the BI workflow and the table stakes, key criteria, and evaluation metrics necessary to evaluate BI platforms. We’ll point out two important emerging technologies as well. This will prepare you to digest the critical reviews of various vendor platforms detailed in the accompanying Radar reports.