How Big Data Analytics Strengthens Cybersecurity
The attacks cybercriminals are using grow more complex and sophisticated by the day. However, with the help of big data analytics, you aren’t left defenseless. You can use big data analytics to fortify your cyber defenses and reduce your vulnerabilities.
This article covers some of the ways big data analytics can reinforce your company’s cybersecurity.
Big data analytics protects your business data and strengthens your cybersecurity by providing valuable cybersecurity intelligence to your data analytics experts. These experts are knowledgeable and trained to collect, store, and examine data on your systems’ functionalities and workflows.
As they process the data, they can note any suspicious activity and track the information sources. They can determine whether these patterns are signs of potentially fraudulent transactions, data breaches, and other cyber attacks.
For instance, specialists can monitor user behavior and uncover anomalies in the way people work within the system.
The experts can further investigate if these anomalies are indications of phishing, distributed denial of service attacks, brute-force attempts, or other illicit operations. Over time, your team can become well-acquainted with vulnerabilities and warning signs of cybersecurity attacks.
They can also track security threats, develop proper investigation and response protocols, and keep a database of your cybersecurity risks.
Big data lets you handle volumes of various data formats — be it structured, unstructured, or relational — and sources. These data sources can include business transactions, sensor information, social media analytics, text documents, email videos, stock ticker data, and more.
Because of that, you can encounter cybersecurity risks since you process truckloads of sensitive information. You can overlook data access issues, deletions, and unintentional and deliberate misuse. Not to mention dealing with data inconsistency and disorganization!
Address those potential data security risks by cleaning your data and enhancing how you manage massive, complex data. Do that effectively with the help of robust technologies such as a data warehouse.
A data warehouse is a system built to support data analysis and reporting. It serves as your central repository for integrated data — that is, data consolidated from various sources, enabling users to access a unified, understandable, and usable view of critical data.
Data warehousing systems also modernize corporate data utilization through robust, scalable infrastructure. Data warehouse content can come from your operational systems (enterprise resource planning, PI system, historian, etc.), relational databases, transactional and financial systems, and more. The warehouse data can also include historical and up-to-date information, which internal users can access to create analytical reports.
