To really move the needle in a way that sustainably transforms the organizational culture to a data-driven one, agencies need to progress beyond these initial ad-hoc use cases. They can do this by strategically harnessing the creativity and operational know-how of departmental staff to identify analytics opportunities enterprise-wide.
The role of a data analyst is evolving in the era of emerging artificial intelligence (AI). So much so, we might need to relabel this role as Analyst 2.0. Here’s a look at what Analyst 2.0 means for the next-gen data guru helping organizations use data for better decision-making.
As video cameras become even more ubiquitous, video analytics will be one of the front faces of AI.
Agencies are seeking innovative ways to boost internal efficiencies, while also improving how they manage and safeguard data.
Agencies are looking for better approaches to data storage and backup. They are are shedding those complex, legacy multi-tiered solutions for simplified data management that still has physical support but is built for virtualized environments, and native cloud capabilities.
Adaptive Networks are automated and programmable networks that can configure, monitor and maintain themselves, as well as adapt to changing requirements.
If your agency wants to optimize access and security around its data, it should look to a data strategy. That strategy has to occur on a hybrid cloud-enabled, multi-modal data and analytics platform.
Learn more about Operations Research, the discipline of applying advanced analytical methods to inform better decisions, primarily to optimize organizational operations through a scientific methodology.
If you learn nothing else from this blog, remember this: The most important step in adding AI to any process is correctly labeling the training data.
Geographic information system (GIS) technology captures, organizes and analyzes geographic data for public servants trying to improve their communities.