In a recent blog post we talked about Gartner’s view on the Corporate Performance Management market, and why they retired the Magic Quadrant for Corporate Performance Management Suites in favor of two magic quadrants. They are the Magic Quadrant for Financial Corporate Performance Management and the Magic Quadrant for Strategic Corporate Performance Management.
Our clients and our team have found a lot of valuable information in two additional magic quadrants from Gartner. The first is the Magic Quadrant for Advanced Analytics Platforms. This report, by Lisa Kart, Gareth Herschel, Alexander Linden and Jim Hare, defines advanced analytics as “the analysis of all kinds of data using sophisticated quantitative methods (such as statistics, descriptive and predictive data mining, machine learning, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) – such as query and reporting – are unlikely to discover.”
In some ways, analytics can seem like “all things to all people.” But in reality, different types of analytics are being used today by a wide range of organizations. And they are seeing tangible results from those analytic applications. In fact, Gartner reports that “by 2018, more than half of large organizations globally will compete using advanced analytics and proprietary algorithms, causing the disruption of entire industries.” Let that sink in a minute. In approximately two years, analytics will play such a strategic role in some organizations that it has the potential to disrupt entire industries. Whether you are working in a large organization, or in a mid-sized organization, now is the time to evaluate and assess what predictive analytics and advanced analytics can do for you.
The second Magic Quadrant in this space is the Magic Quadrant for Business Intelligence and Analytics Platforms by Josh Parenteau, Rita Sallam, Cindi Howson, Joao Tapadinhas, Kurt Schlegel, and Thomas Oestreich. In the report, Gartner outlines the shift in buying power for BI applications from IT to the business as a result of the evolution of self-service analytics. The authors write, “this significant shift has accelerated dramatically in recent years, and has finally reached a tipping point that requires a new perspective on the BI and analytics Magic Quadrant and the underlying BI platform definition – to better align with the rapidly evolving buyer and seller dynamics in this complex market.” The report also presents five use cases and 14 critical capabilities of a BI and analytics platform.
Clearly, there’s no lack of analysis available on vendors and solutions in the overall analytics space. In fact, just determining which Magic Quadrants are relevant for your project can be a challenge. We hope these posts provide some clarity and direction for you.