Data augmentation adds value to base data by adding information derived from internal and external sources within an enterprise. Data is one of the core assets for an enterprise, making data management essential. Data augmentation can be applied to any form of data, but may be especially useful for customer data, sales patterns, product sales, where additional information can help provide more in-depth insight.
Data augmentation can help reduce the manual interventation required to developed meaningful information and insight of business data, as well as significantly enhance data quality.
Techopedia explains Data Augmentation
Data augmentation is of the last steps done in enterprise data management after monitoring, profiling and integration.
Some of the common techniques used in data augmentation include:
Extrapolation Technique: Based on heuristics. The relevant fields are updated or provided with values.
Tagging Technique: Common records are tagged to a group, making it easier to understand and differentiate for the group.
Aggregation Technique: Using mathematical values of averages and means, values are estimated for relevant fields if needed
Probability Technique: Based on heuristics and analytical statistics, values are populated based on the probability of events.
Guide To Data Visualization
- Insight from business intelligence programs can be difficult to digest in numerical form. This guide covers the factors one should consider when selecting and implementing a data visualization solution.
Data Visualization Product Selection Tool
Insight from business intelligence programs can be difficult to digest in numerical form. Visual representations help people comprehend such information, and encourage a wider range of insight.