Anomaly Detection for CRM Production Data


As part of Salesforce's Platform performance engineering team, we use Python to employ anomaly detection techniques and other analytics methods for monitoring customer data. This helps us gain real-time insights into the performance of our production data and its impact on customers. By promptly identifying anomalies and extracting valuable insights, we improve system reliability, reduce downtime, and enhance customer trust—core values at Salesforce.

Our efficient data processing capabilities enable faster modeling, analytics, and anomaly detection. In our technical talk, we'll demonstrate the value of machine learning and analytical visualizations in solving real-world data analytics challenges. We'll showcase how our data-driven production system addresses these challenges, emphasizing the importance of data analytics in ensuring reliable systems and building customer trust.
Key Points:

1. Anomaly Detection: We use techniques to detect abnormal patterns in customer data, ensuring prompt identification and resolution of anomalies for system reliability.
2. Real-time Insights: Our data analytics techniques provide immediate insights into production data performance, enabling proactive measures for optimization.
3. System Reliability and Reduced Downtime: Data analytics minimizes system downtime by actively monitoring and resolving performance issues.
4. Enhanced Customer Trust: Our data-driven approach shows our commitment to delivering a trustworthy platform that customers can rely on.
5. Efficient Data Processing: We efficiently collect, aggregate, and process large volumes of data, facilitating faster modeling, analytics, and anomaly detection.

By sharing the value of machine learning and analytical visualizations, we aim to inspire attendees with practical insights and strategies for their own performance engineering efforts.


Geeta Shankar is a software engineer who specializes in leveraging data for business success. With expertise in computer science, data science, machine learning, and artificial intelligence, she stays updated with the latest data-driven innovations. Her Indian classical music background has taught her the value of sharp thinking, spontaneity, and connecting with diverse individuals. Geeta uses these skills to translate complex data into meaningful insights that enhance performance and customer experiences.

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