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Transformation Use cases

Overview

Data transformation is a crucial step in ETL (Extract, Transform, Load) pipeline, enabling businesses to convert raw data into meaningful insights. DataHub provides a flexible and scalable environment to handle transformation processes efficiently.

When working with unstructured data, Bold Data Hub helps ensure that data is cleansed, standardized, enriched, and structured for accurate analysis and reporting.

Below are some typical transformation use cases you can consider:

List of transformation

Data Cleaning and Standardization
Date and Time Adjustments
Categorization and Mapping
Enriching Data
Aggregation and Summarization
Data Validation and Transformation Rules
Data Pivoting and Reshaping
Handling Data Anomalies
Customer Journey Analysis