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.
These days we hearing about many things being delivered “as a service.” Recently, I got to moderate two days of discussions about mobility as a service.
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.
Natural tendencies aside, integrating data in pursuit of removing silos can actually cause more problems than solve. Here are three key issues that are introduced when integrating a lot of data into one data warehouse.
If you’re an elected leader, appointee or senior executive, this article will help you think strategically about data leadership.
The government relies on data to perform a number of critical services and simply to function. But what happens when data fails?
If you’re knee deep in the data and starting to feel lost, here’s how you can scope your data science projects.
If you are starting a data science service in your jurisdiction, your first task will be to develop a backlog of projects. This article walks you through how to solicit and select data science projects.
The role of Chief Data Officer (CDO) is still new in government. Here are some tips to help you navigate in this new but increasingly popular title.