What is data validation?

Data Science, AI and ML
#1

Data validation means checking the accuracy and quality of source data before training a new model version. It ensures that anomalies that are infrequent or manifested in incremental data are not silently ignored. It focuses on checking that the statistics of the new data are as expected (e.g. feature distribution, number of categories, etc).

Different types of validation can be performed depending on objectives and constraints. Examples of such objectives in the machine learning pipeline are below – ​​​​​​​

  1. Are there any anomalies or data errors in the incremental data? If yes, raise an alert to the team for investigation.
  2. Are there any assumptions on data that are taken during model training and are getting violated during serving? If yes, raise an alert to the team for investigation.
  3. Are there significant differences between training and serving data? Or, Are there differences between successive data that are getting added into training data? If yes, raise an alert to investigate differences in training and serving code stack.​​​​​​​​​​​​​​

Output from the data validation steps should be informative enough for a data engineer to take action. Also, it needs to have high precision as too many false alarms will easily be lost credibility.

#2

Data is fundamental for any business process and it must be verified before analyzing or merging it with the master database. The data validation process ensures that the data is complete, non-redundant, meet quality standards, and is formatted as per the structure of the database.

Validating data is a crucial step required to maintain the integrity of the databases. With validation, databases become consistent, relevant, and more accessible to different departments. Data validation services play an important role in:

  • Implementing email marketing campaigns efficiently
  • Accelerating decision-making process
  • Reducing the costs of the campaigns
  • Generating higher ROI from each campaign
  • Augmenting overall operational efficiency

Data validation services ensure that businesses can trust their data to be accurate, dependable for decision making, and rich in insights. Since data is the most valuable asset for many businesses; they are an imperative part of their success journey.