WEBINAR
Detecting anomalous patterns in real-time data can lead to significant actionable insights in a wide variety of application domains, such as fraud detection, network traffic management, predictive healthcare, energy monitoring and many more.
However, detecting anomalies accurately can be difficult. What qualifies as an anomaly is continuously changing and anomalous patterns are unexpected. An effective anomaly detection system needs to continuously self-learn without relying on pre-programmed thresholds.
Join our speakers Ravishankar Rao Vallabhajosyula, Senior Data Scientist, Gathr and Saurabh Dutta, Technical Product Manager – Gathr, in a discussion on:
-
Importance of anomaly detection in big data, types of anomalies, and challenges
-
Prominent real-time anomaly detection application areas
-
Approaches, techniques and algorithms for big data anomaly detection
-
Sample implementation of a big data anomaly detection use case on the Gathr platform
MEET GATHR
Turn raw data into business outcomes, at scale and 50x faster
Gen AI/ML Powered
No-code drag & drop simplicity
Unified collaborative experience
-
Ingestion
-
ETL
-
CDC
-
DQM
-
ML
-
Insights
-
Atomation
-
Xops
-
Business Apps
Recent Posts
View more postsBlog
50X faster time to value with Confluent and Gathr...
Blog
Data + AI Summit 2023: A must-attend for data scientists,...
Blog
Move away from batch ETL with next-gen Change Data Capture
Blog
ETL vs ELT: Which data integration practice is right for...
