There are many levels to how our federal government protects our country. Teracore uses data and analytics to uncover insider threats and systemic failures for our government clients. We look for behavior and associations related to corruption, misconduct and policy violations. Our analytics have not only found individuals; they have also spotted trends that identify particular cohorts that tend to be vulnerable to misconduct.
With the increased volume and diversity of data comes the need for handling data in-bulk, we must keep in mind the architecture and the analytics needed for handling the large datasets. Here are a few analytics best-practices that we’ve developed:
- Analyze the universe of data. Analytics is headed away from statistical sampling and more so towards working with the universe of data.
- Good data modeling is crucial. Having the correct data modeling software ensures efficient communication between your analysts and your officers. Data modeling software breaks down the data visually so that operators can understand the importance of the data and allows analysts and officers to reach a discussion point.
- Focus on indices. Indices are helpful in tracking the difference between which statistics are increasing and which remain constant.
- It’s important to have your own set of tools. Building your own taxonomy of data analytics tools is vital because sometimes your job site will not have them readily available. Data visualization and synthesizing are the best ways to model your data.
- Analyze real-life events. Testing hypothetical scenarios can be a useful tool for collecting data but there’s no better way to get accurate and relevant results than looking at real life events and collecting their data.
Our government works hard to keep us safe. Identifying the most efficient way to study and act on data findings is a key part of keeping threats at bay. In an age where data is gold, agencies must know how to properly analyze and process it.