Predictive analytics analyze current and historical facts to forecast future outcomes, and the practice is a cornerstone of a fully-realized IoT strategy.
Government IT leaders know that efficient data backup and recovery are integral to mission success. But there are a few challenges that agencies have to overcome if they’re really going to secure and access their data.
Agencies recognize that modern analytics is imperative. But to harness these capabilities, they need platforms that support real-time decision-making.
Improve your state’s data analytics initiatives by partnering with urban science programs that offer the policy know-how you need.
Is legislation alone enough to make government work the right way? For the most impactful solutions, communities need to get involved at some point.
As the volume of data increases every day, government will need new and innovative ways to identify, prioritize and, most importantly, secure their data.
Government knows they have a long way to go in making up the gap of satisfaction in the citizen experience. But by adapting an empathetic mindset when it comes to conducting and measuring citizen interactions, they can get themselves on the right path.
Machine data is an authoritative record created by the activity of computers, mobile phones, embedded systems, network devices or any digital component. It includes all sorts of information, including logs, configurations, message queues, change events, call detail records, sensor data from industrial systems, and more.
Learning a new language is akin to how cities should learn use data as an asset. Here’s how to adopt data as an asset strategy citywide.
Probing deeply into big data and pinpointing solutions to important problems demand a chief analytics officer (CAO), rather than a chief data officer (CDO). Both are essential to a smart city or smart business, but they are quite different.