The Defense Logistics Agency has begun to use predictive analytics so it can proactively combat issues and develop creative solutions in anticipation.
Posts Tagged: predictive analytics
What would be possible if your organization could predict future occurrences? A new generation of advanced analytics—high-level diagnostic, predictive, and prescriptive—can now provide that opportunity.
Predictive analytics analyze current and historical facts to forecast future outcomes, and the practice is a cornerstone of a fully-realized IoT strategy.
Platforms like Amazon Web Services (AWS) are transforming the way government thinks about storage, integration, cybersecurity and analytics, and are helping agencies overcome common data challenges.
Learning from the past to predict the future.
This blog post is an excerpt from GovLoop’s industry perspective: Seizing the Power of Predictive Analytics in Government. Download the full report here. The data analytics landscape is rapidly evolving, thanks to more powerful and affordable tools for data gathering and processing. These tools are helping agencies make sense of their data and use that informationRead… Read more »
Business users know that if they had better access to the mounds of data available to them they could make more informed and better business decisions and they could be looking ahead not backwards. We finally have modern user-friendly data analytics tools available to do just that.
Big data and predictive analytics come with big promises of delivering new and greater insights for government agencies. While the capabilities are real, results won’t happen overnight – there is a methodology to implementing big data analytics.
Depending on the type of analysis agencies want to conduct — real-time or historical — there are different data gathering and analytics tools to support those efforts. Let’s take a closer look at each of these examples to better understand how they benefit government agencies.
The practical applications of clustering are vast. With the ability to identify groups in the data based on their shared characteristics, future customers, employees and stakeholders can be marketed and delivered products and services that are most likely to be pertinent to their specific needs.