A 4-Step Approach to Building your Predictive Analytics Stack Posted on : May 11 - 2017

We live in a world filled with vast amounts of data that could open endless business opportunities. But with so much data scattered across disparate IT architectures, systems, and applications, these data resources often go untapped.

Traditional business intelligence (BI) tools go some of the way to help organizations harness the power of big data, but these are often enterprise-scale, complex, and rarely customized to the needs of each user.

Self-Service Business Transformation

The cloud has afforded a new approach. Gone are the days when you needed to engage IT to run a BI report. Today, the cloud has brought self-service to BI, making it easier than ever for non-technical users to own, manage, analyze, and visualize their data – wherever it resides.

Cloud-based predictive analytics (the practice of extracting information from data sets to predict outcomes and trends and inform decision making) also solves the problem of disparate data sets. By integrating systems and processing capabilities in the cloud, organizations benefit from a powerful and holistic view of the enterprise and its customers without the need to invest in new systems, software, or expertise. Instead of spending months integrating data siloes and systems into an inflexible traditional BI platform, the cloud makes it possible to connect and analyze legacy and real-time data without the headache or cost.

This makes it much easier for organizations, small or large, to improve services and achieve outcomes such as segmenting customers at the micro-level so they can track customer journeys, understand customer needs and behaviors, and develop more targeted marketing messages.

Thanks to the cloud, predictive analytics is fast becoming the norm and a core basis for business decision-making. But a pure-cloud-based BI approach has its shortcomings. For one thing, cloud BI is still evolving and tends to lack the functionality and range that the traditional (complex and costly) BI solutions provide. Today’s solutions, including cloud, also fall short in terms of future-readiness.

Future-Readiness Goes Beyond the Cloud

The BI tech industry is a fast moving one, today’s tools may not be the best for tomorrow’s business needs. Rather than “rip and replace”, forward-thinking organizations need to be able to adapt as technology changes. This means extending today’s investment in BI tools, something that’s easier said than done given the challenges of vendor lock-in and static technology that typify today’s enterprise-grade solutions. It’s a perplexing dichotomy. View More