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Significance of Anomaly Detection and Predictive Analytics for your enterprise

by David Hunt Data Geek and Analytics Fanatic

Anomaly detection and predictive analytics are closely related. Predictive analytics helps you prevent anomalies in your business by analyzing past data and forming predictive models.


Anomaly detection again means identifying outliers in a time series data using mathematical models, analogizing it different influencing elements and delivering insights to business decisions makers. For industrial production systems, it is critical to have a 100% up-time of their machinery. It has many applications in the business right from intrusion detection, system health monitoring, fraud detection in credit card transaction to fault detection in operating environments. It is also known as outlier detection; this anomaly detection is a process which is used for determining types of anomalies found in a data set and also learn details about their occurrence. The big data anomaly detection is a very crucial part in today’s time where the sheer capacity of data makes it difficult to tag outliers manually.   



Predictive business analytics uses machine data to determine the most well-organized time to perform maintenance. It is beneficial in making predictions regarding the unknown future events. This predictive analytics make use of various techniques right from statistics, modeling, data mining to artificial intelligence to predict the future.



The big data anomaly detection is steadily used in behavioral analysis and other forms of analysis to assist in learning about the identification, prediction as well as detection of the occurrence of anomalies. Advances in machine learning, deep learning algorithms, and artificial intelligence have authorized automated anomaly detection to become an actuality.


An organization can become proactive, anticipating outcomes, and proactive with the help of predictive business analytics. The process of this analytics includes define project, data collection, data analysis, modeling, statistics, deployment, as well as model monitoring. It quickly automates composite decisions and trade-offs to make a prediction. Through this type of analytics, you can also identify the most practical combination of product versions, communication channels, timing, as well as marketing material that should be utilized to target a given consumer.  


Why your enterprise needs anomaly detection


It is now very easy to efficiently measure a single aspect of your business activity with entire analytical programs and different management software available. To evaluate the success of your business, it makes use of the operational performance of applications and infrastructure components. With this, you will be able to trace the root cause, whether it’s about a promotional discount that drove up sales or a price glitch that’s impacting revenue. Thus, if there are thousands of metrics to track across your business, there are also thousands of distinctive methods to gain insights from anomaly detection.


Thus, the above-stated information is sure to give you enough knowledge about what anomaly detection is and why is it essential for your business.


An e-commerce business can quickly adopt this anomaly detection as e-commerce creates large quantities of data regularly. This data helps them in deciding which contributes to their success. Thus, anomaly detection is one such thing which is going to benefit retailer with the use of data which already exists in the database. Apart from this, the main objective of anomaly is to detect the needle in the haystack.


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About David Hunt Innovator   Data Geek and Analytics Fanatic

10 connections, 0 recommendations, 52 honor points.
Joined APSense since, March 14th, 2020, From New York City, United States.

Created on Jul 26th 2020 06:55. Viewed 146 times.

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