Anomaly detection forms an essential component of real-time analytics, which help enterprises gain significant actionable insights across a wide variety of application domains. However, detecting anomalies accurately can be difficult. As systems evolve, behaviors change, and software gets updated, the system needs to be upgraded continuously to detect an anomaly effectively.
This white paper explores the know-hows of big data anomaly detection in real-time.
- The importance of big data anomaly detection
- How to build an anomaly detection model
- A view of the platform approach to real-time anomaly detection
- How StreamAnalytix can help in real-time anomaly detection
You may also be interested in…
As the Internet of Things (IoT) generates incessant data, organizations need smarter and more efficient ways to manage and process…
Enterprises and IoT applications can benefit immensely from real-time streaming analytics by visualizing the business in real-time, cutting preventable losses, detecting urgent situations…
To keep up with the new digital consumer and remain competitive, the auto insurance industry is increasingly investing in connected…
Learn how a large US-based bank used predictive analytics and machine learning to identify and prevent insider information security threats…
Organizations are collecting massive amounts of data from disparate sources. However, they continuously face the challenge of identifying patterns, detecting anomalies, and projecting future trends based on large data sets.
Detecting anomalous patterns in real-time data can lead to significant actionable insights in a wide variety of application domains, such as…
Ensure successful data ingestion on the cloud: Strategies for 2021
Mar 19, 2021 | 11:00 am PT / 2:00 pm ET