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Secure Data, Secure Decision-Making

Easy access to data is crucial for decision-making, especially in finding the right questions to ask. But security is equally crucial. As data increases, it becomes more challenging to store, share and secure it, within and across organizations.

“We want to use data more and more to make data-based or data-oriented decisions,” said Kevin Steeprows, Field Chief Technology Officer with Red River, a technology transformation company serving government and enterprise customers. “But we’ve still got that same dilemma that has existed since the dawn of time, that there’s so much data out there. Where does it reside? Who has access to it?”

Red River helps agencies with many facets of technology integration that pertain to data, such as cloud migration, data center development, data mapping and infrastructure.

Take Stock of What You Have

To make solid steps forward, Steeprow recommended agencies “start where they are.”

That means evaluating the systems that are already in place and finding out who can access them. Red River helps identify the characteristics of the highest-value data sources to determine if they align with the agency’s mission. Data that pertains to compliance requirements and mandates is a priority.

Visualization, which pulls together information from different sources, helps users understand what data means and respond to it.

Keep Access Authorized

A big challenge is managing the tension between keeping data secure and making it accessible.

Red River helps agencies build security models that help them with threat-hunting, through adaptive thresholding, mathematical principles and ML, and dashboards highlighting potential malicious activity.

“So, with all those things to protect the data, how are we going to get access to it in order to make a decision that’s meaningful and appropriate?” asked Steeprow.

For example, if zero-trust architecture prevents an agency from accessing data needed for decision-making, Red River systems help notify the user that data is missing, because of the way they have tried to access it. Steeprow and his team also help agencies record data correlations, so that there is a historical record of how users have analyzed information, he said.

Build a More Complete Picture

According to Steeprow, agencies need to get a full, holistic view of data systems, “rather than just diving in and asking a question, pulling data and coming up with an answer — and hoping that that’s the right answer.”

If someone is working with incomplete data, they might be asking the wrong question, resulting in useless or, worse, misleading results, he said. That’s especially true for emergency situations when directors need to make decisions quickly.

As Steeprow said, AI and ML are only just beginning to bring data management to a place where information is comprehensive and accurate. But already the process is helping software engineers and agencies think in new ways, ask questions and evaluate processes.

All those capabilities — when fully integrated into an agency’s data coordination and processes — lead to more secure and complete use of data.

This article appears in our guide, “Decision Intelligence: New Possibilities for Data-Based Decision-Making.” For more about how agencies are using data in practical ways, download it here:

Image by Roman from Pixabay 

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