Datafication
(also big data)
Datafication definition
Datafication is a method that helps organizations convert everyday aspects, such as human behavior, economic transactions, and social interactions, into digital data by using cameras, sensors, and other data-collection devices. Then, computers store, analyze, and process the data to gain insights into improving business work and predicting human behavior.
Datafication has many benefits and uses. It improves decision-making, increases efficiency, and enables new insights and discoveries. Moreover, it helps cybersecurity experts identify anomalies and patterns that may suggest a data breach or other malicious activities. This is possible due to datafication’s ability to analyze data, user behavior, and system logs. However, datafication also raises concerns around privacy, security, and the potential misuse of data.
See also: data breach, exploit
Datafication usage
- SIEM systems. They collect and analyze security-related data from various sources, such as servers, applications, and network devices. Therefore, SIEM systems can quickly detect and respond to potential security threats.
- Vulnerability management. Datafication analyzes the system’s vulnerabilities and allows organizations to address them in the future, reducing the risk of exploitation by attackers.
- Machine learning algorithms. They analyze large amounts of data and help detect anomalies that show there is a data breach or another potential attack.
- Data visualization. It displays and analyzes data in an easily-understandable way, allowing experts to detect threats quickly.
- Incident response. Datafication collects and analyzes data about security incidents, like system logs and page traffic. It helps organizations determine the incident’s impact and scope and generate response strategies.