Data preprocessing is the process of cleaning, annotating, labeling and preparing data before any use. This process helps to improve data quality, remove unwanted noise or errors, and make the dataset suitable for AI training. Our data pre-processing service covers a few stages as listed below.

Data Cleaning

Removing duplicates, and errors while handling missing values from data is an essential step in preprocessing data. Filtering out specific information such as PII (personally identifiable information) is also critical in establishing a set of robust data that you can use for multiple purposes.

We are accustomed to this data cleaning process where we have the experience of cleaning over three million datasets for a single project.

Data Annotation or Labeling

Oftentimes, data that has been retrieved requires additional annotation and labeling tasks. This can help to bring deeper meaning and sense to the data points to assist in retrieval and AI learning. Our service includes the provision of data annotation and labeling work for text or images, including metadata.

{

"text": "I love this product! It's amazing.",

"sentiment": "positive"

}

Our data annotation fee is competitive as we have access to global data annotating talents.

Data Export After Preprocessing

Once the data has been processed, we can also export your data in your desired format such as specific database format (relational or vector), CSV, JSON,  XML and more.