Modern analytics tools often use artificial intelligence and machine learning, which allows processing huge amounts of information in real time. This makes network data analysis indispensable for ensuring the stability and security of corporate and operator networks. Data Light , in turn, deals with data labeling, which plays an important role in training AI systems for subsequent analysis of network traffic and identification of anomalies.
Splunk
Splunk is one of the most well-known platforms for monitoring and analyzing big data in networks. It allows you to collect information from different sources, analyze it, and identify important patterns. Splunk actively uses machine learning technologies, which makes it a powerful tool for analyzing huge volumes of network traffic. The system allows you to find and eliminate bottlenecks in the network, optimize its operation, and improve performance indicators.
Using machine learning, Splunk helps costa rica telegram data automate the analysis and prediction of potential problems in network infrastructure. This speeds up decision-making and improves overall network health, which is especially useful for companies that work with a lot of data.
2. Elasticsearch and Elastic Stack
Elasticsearch
Elasticsearch is part of the Elastic Stack, which includes Kibana and Logstash, and offers powerful tools for analyzing network data. Elasticsearch uses AI to find anomalies and analyze network flows. The integration of machine learning allows the platform to analyze network logs and traffic in real time, predicting possible failures or errors.