Predictive analytics is the use of historical data to determine the likelihood of future outcomes

For example, banks will often identify fraudulent activity based on anomalies in purchasing patterns. Moreover, ratings like credit scores have been predictive indicators of people’s likelihood of paying their bills on time.

Artificial intelligence (AI) and machine learning (ML), among other tools, will enable future network engineers to address potential network performance issues by applying predictive analytics.

As network technology continues to improve, information technology (IT) professionals will see prediction models that closely match real outcomes, making predictive analytics an invaluable tool.

Network security can be greatly improved using predictive analytics. Traditionally, network security professionals have relied on “signatures”: digital fingerprints that hackers leave when they attempt to compromise data. Now, however, signatures have become outdated, and network security can be monitored in real time across multiple networks using predictive analytics. Future network security relies on complex solutions to increasingly complex problems.

About The Writer:

Emmanuel Alamu, Africa’s foremost Network Engineering Expert is a member of the Internet Society (ISOC) International and Nigeria. He is the Chief executive officer of NetEng Solutions, a network and internet solution providing company in Lagos, Nigeria. Emmanuel is an active volunteer at the Internet Society Global Volunteer Training Program on Community Networks.

He is the president of The Emmanuel Alamu Network Academy (TEANA) where he has trained and certified hundreds of young people to become network engineers.

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