Guest Post: The Emergence of Public Safety Data Lakes

Organizations are looking for an architecture that accommodates all of these new devices and the rapid growth of data so that they can finally realize the value that is currently locked in their closed systems. One emerging concept in the surveillance industry is the surveillance data lake.

As it applies to public safety, a surveillance data lake is made up of several key pools of data feeding in from different sources, such as in-car, video, video cameras, body-worn cameras and drones. From this pool of data, organizations can perform critical activities based on their needs, including analytics, evidence management, and anomaly detection. This data needs to be secure, reliable and available to multiple user groups across key applications.

With an estimated 54 percent of their data going unanalyzed, federal organizations are missing many opportunities for applications and insights, including crowd counting, anomaly and incident detection, face matching, safety alerts, traffic monitoring, object recognition and suspicious behavior. Data is growing so fast that these organizations simply cannot find a way to scale, let alone analyze.

But while scale is clearly a challenge here, understanding what should serve as the foundation to the data lake architecture can be even trickier. Should users go on-premise or cloud? If on-premise, do they have distributed or centralized architectures? If they want to be in the cloud, how do they ensure easy access to the data? When they need to quickly access the data for evidentiary support, will they need to dig through piles of storage to find it? How do they decide between private, public and hybrid versions of the cloud? What about a mixture of on-premise and cloud? Choosing a storage vendor alone, before even thinking of analytics, applications, etc., can be daunting and exhausting. And public safety organizations being in the public eye only heightens the pressure.

Forward-thinking public safety departments build a data platform that can collect, store and manage this data. A data lake infrastructure provides a more cost-effective storage environment with the ability to seamlessly integrate new types of devices while gaining more control over the data. Finding a storage vendor that offers this type of open platform is critical to moving forward this enterprise model, which will prove more cost effective, will be less complex to manage, and will allow for more innovation and the flexibility to add applications and gain value from surveillance data.

Ken Mills is a General Manager for Dell EMC’s Surveillance and Security practice area. Dell EMC is a Pelco integration partner. To learn more about the program, visit our Partner First page.



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