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.
Posts Tagged: How You Can Use Data Analytics To Change Government
The way government agencies provide analytics to their users is changing. But one change that should be top of mind for agencies is ensuring the tools and services they offer are easily available to internal and external consumers.
No police department has the manpower to be everywhere at all times. That’s why police officers in Norcross, Georgia, are using predictive analytics to determine the most probable locations where crimes might occur.
For a growing number of agencies, the answer to powering their data analytics operations has come in the form of flash storage, which can be a more cost-effective and efficient alternative to the legacy disk storage agencies have traditionally used.
While the benefits of big data in government are tremendous, the implementation is proving very challenging because legacy infrastructure cannot handle the demanding workload. Here’s how multi-tiered flash storage systems can help.
In 2014, GSA launched a division dedicated to developing workforce analytics deliverables. The first of those deliverables was an interactive dashboard that visualized answers to common HR questions about new hires, separations, onboarding and more. Now, GSA has a turnover model for predicting future employee losses.
This blog post is an excerpt from GovLoop’s recent guide, How You Can Use Data Analytics to Change Government. Download the full guide here. What does 2016 look like for government IT? We may be in for a few surprises, but one thing is clear: data analytics will play a key role. There are several areas whereRead… Read more »
There are countless stories of agencies using analytics to improve online services and better track internal metrics. But the path to a successful big data analytics implementation requires proper long-term planning that addresses growth, flexibility, agility and the evolution of technology.
Analysts can work more efficiently now because they aren’t flooded with a sea of security alerts that realistically can’t all be addressed at the same time. Using analytics, they can prioritize anomalies and understand what data is leaving the network in an unauthorized way.
Given the vast quantity of data out there and the cost of management and analytical processes, many agencies have yet to transform data analytics into a real asset.