Machine Learning in Data Quality Space – Anomaly Detection

Project Description: In the current data age, quality of the data becomes center place for any enterprise data strategy. The issue of poor data quality is hindering organizations from performing to their full potential. Gartner’s data quality market survey estimated that the financial impact caused by data quality issues is in millions. Traditionally organizations have used a combination of manual and automatic methods to tackle this issue in siloed approaches.

This project helps for any time series data / data anomaly detection by using the Machine Learning algorithms. It evaluates various data patterns and detects the anomaly based on thrush hold setup. This solution would be spanned across verticals, E.g., Sales data, Financial data, Customer behavior data.