YData for Telecommunications
Telecom companies are increasingly using predictive tools for resource optimization. Most telecom companies collect customer and usage data, but organising it and extracting coherent samples out to be able to properly train models that manage and optimize networks and resources is something most companies have not yet been able to achieve.
Read moreNetwork defects can be detected using Anomaly Detection algorithms. But the algorithms are severely hampered due to the lack of good data. YData can automatically classify the different types of anomalies and synthesize data accordingly to train better predictive models. YData’s Pipelines allow the user to compare, contrast and fine-tune the ML model for the detection job.
The value of information assets has never been greater. Synthetic data has the same statistical and business value of real data, but it is not traceable back to the real individuals. This makes it suitable to be monetized without concerns around privacy.
With AIOps, teams are able to tame the immense complexity and quantity of data collected from modern IT environments, prevent outages, maintain uptime and attain continuous service assurance. YData enables the creation of training datasets and models, and seamlessly integrates production ML models and pipelines into existing IT operations.
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A new paradigm for AI development — focused on data quality
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According to the 2021 enterprise trends in machine learning report by Algorithmia
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Modern data development tools and how data quality impacts ML results
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