Data Cleaning Features of ERP Solutions
Designed to help organizations improve the quality and accuracy of their
data, and to ensure that the
information in the ERP system is reliable and useful for decision making.
Duplicate Record Detection
Identifies and removes duplicate records from the ERP system, preventing data redundancy and inconsistency. The duplicate record detection algorithm typically uses a combination of attributes to identify duplicate records, such as names, addresses, phone numbers, and email addresses.
Standardizes data formats, values, and terminology to ensure consistency across the system.It can convert different date formats into a common format or standardize product names to make them consistent throughout the system. This improves data quality and helps ensure that data is usable and consistent across different departments.
Validates data against business rules and external sources to ensure accuracy. For example, it can validate customer addresses against postal services' databases to ensure that they are valid and deliverable. This helps to prevent errors, inconsistencies, and data quality issues.
Reconciles data from multiple sources, such as legacy systems, to ensure that all relevant information is included in the ERP system. It maps the data from different sources and reconciles the differences, ensuring that the data is consistent and up-to-date across the system.
Enriches data with missing or additional information to improve its accuracy and usefulness. It can enrich customer data with demographic information, such as age, gender, and income, to improve customer segmentation and targeting.
Corrects errors, typos, or outdated information in the ERP system. It can automatically correct errors, such as typos or spelling mistakes, and update outdated information, such as contact information. This ensures that the data is accurate and up-to-date.
Automated Data Cleaning
Automates data cleaning tasks, such as duplicate record detection and data standardization, to save time and improve accuracy. It can also schedule data cleaning tasks to run automatically, reducing the need for manual intervention and ensuring that the data is always up-to-date.