Discover What’s Driving Your Metrics with Real-Time Anomaly Detection
Read this blog (https://startree.ai/blog/discover-whats-driving-your-metrics-with-real-time-anomaly-detection) to see it in action for the following:
- “Dimension level timeseries metrics monitoring” and anomaly detection.
- “Dimension recommender” for automated identification of top dimensions driving your metrics without the need for you to mine the data manually.
In today’s fast-paced business world, it’s more important than ever to be able to quickly identify and address anomalies in your metrics. Real-time anomaly detection can help you do just that, by providing you with insights into what’s driving your metrics and alerting you to potential problems before they cause major damage.
In this blog post, I’ll discuss what real-time anomaly detection is, how it works, and how you can use it to improve your business.
What is real-time anomaly detection?
Real-time anomaly detection is the process of identifying unusual patterns in data as they occur. It can be used to monitor a wide range of metrics, such as website traffic, sales, and customer support tickets.
Real-time anomaly detection systems typically use either rule based or statistical or machine learning based algorithms to learn what normal behavior looks like for a given metric. Once they have a good understanding of normal behavior, they can identify anomalies as they occur.
How does real-time anomaly detection work?
Real-time anomaly detection systems typically work by following these steps:
- Collect data: The system collects data from a variety of sources, such as databases, logs, and sensors.
- Preprocess the data: The system preprocesses the data to clean it up and remove any noise.
- Train a model: The system trains the learning model (Statiscal or machine learning) to learn what normal behavior looks like for the data.
- Detect anomalies: The system uses the trained model to detect anomalies in the data as they occur.
- Alert the user: The system alerts the user to any anomalies that it detects.
How can you use real-time anomaly detection to improve your business?
Real-time anomaly detection can be used to improve your business in a number of ways, including:
- Identify and address problems quickly: Real-time anomaly detection can help you to identify and address problems before they cause major damage. For example, if you’re monitoring your website traffic and you see a sudden drop in traffic, you can investigate the issue and take corrective action before it’s too late.
- Improve customer satisfaction: Real-time anomaly detection can help you to improve customer satisfaction by identifying and resolving problems before they impact your customers. For example, if you’re monitoring your customer support tickets and you see an increase in tickets related to a particular issue, you can take steps to resolve the issue and improve the customer experience.
- Make better business decisions: Real-time anomaly detection can help you to make better business decisions by providing you with insights into what’s driving your metrics. For example, if you’re monitoring your sales data and you see a sudden increase in sales for a particular product, you can invest more resources in marketing and selling that product.
Real-time anomaly detection is a powerful tool that can help you to improve your business in a number of ways. By identifying and addressing problems quickly, improving customer satisfaction, and making better business decisions, real-time anomaly detection can help you to achieve your business goals.
If you’re interested in learning more about how to use real-time anomaly detection to improve your business, please read this blog (https://startree.ai/blog/discover-whats-driving-your-metrics-with-real-time-anomaly-detection), visit our website (https://startree.ai/products/startree-thirdeye) or contact us for a demo (https://startree.ai/demo). Link to freetrial incase you want to explore further.
