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.
Budgets are getting tighter and resources are being spread thin at the state and local level. One way for governments to stretch their diminishing dollars is to use data to make smarter decisions.
Accumulation of data is common for any organization — especially those in state and local governments. Learn how San Francisco tackles its data science.
The most important part of the analytics process within an urban environment is impacting the resident.
Algorithms play an important part of our every day lives and will continue to grow and expand. Here’s what algorithms and the future of government could look like.
The next to last – and what many believe is the most important phase of a citywide analytics project – is the development of an analytics solution. Here’s how you can build your analytics solution in order to solve problems.
If you’re an elected leader, appointee or senior executive, this article will help you think strategically about data leadership.