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Data Mapping Rules

Data management1/5/2026Intermediate Level

Specific instructions defining how data fields from a source system correspond to fields in a target system, ensuring accurate data transfer and transformation.

What is Data Mapping Rules? (Definition)

Data mapping rules are instructions that tell a system how to move information from one source to another. These rules connect fields between different databases so the data lands in the right place. They handle tasks like changing field names or switching data types, such as turning text into numbers. Rules can also merge multiple fields into one or use logic to decide which data to move. In a PIM system, these rules are essential for bringing in product data from an ERP or a supplier. They ensure the information matches the internal structure perfectly. WISEPIM uses these rules to format your data to meet the requirements of different webshops and marketplaces. This automation saves time and prevents manual entry errors.

Why Data Mapping Rules is Important for E-commerce

Data mapping rules are instructions that tell software how to connect information between different systems. They ensure that a product name in a supplier file ends up in the correct name field on a webshop. Accurate rules prevent errors like missing prices or incorrect technical specs. These mistakes confuse customers and lead to fewer sales. Well-defined rules help businesses add new products to their catalog much faster. They also reduce the need for manual data entry. Systems like WISEPIM use these rules to keep product information consistent across every sales channel. This automation allows companies to grow their online presence without losing data quality.

Examples of Data Mapping Rules

  • 1Link an ERP field called 'Item_Description' to the PIM field 'Product_Name' and automatically capitalize the first letter.
  • 2Convert a supplier's weight from kilograms to pounds by applying a math rule during the import process.
  • 3Combine two separate source fields, such as 'Size' and 'Unit', into a single 'Product_Size' attribute like '10 cm'.
  • 4Create a rule that sends a product status as 'Available' to your webshop but labels it as 'In Stock' for an external marketplace.

How WISEPIM Helps

  • WISEPIM includes a flexible tool to set rules for how product data moves. This helps you manage complex data flows when importing or exporting information.
  • The system automatically changes data formats and combines fields based on your needs. This removes the need for manual data entry and complex spreadsheets.
  • Clear mapping rules keep your product details consistent across every sales platform. This prevents errors and ensures customers always see the correct information.
  • You can quickly connect new suppliers or sales channels to your system. This speed helps you get products to market faster and reach more customers sooner.

Common Mistakes with Data Mapping Rules

  • Skipping tests before you go live, which leads to wrong product data appearing on your website.
  • Ignoring errors in your original data, which allows mapping rules to move those mistakes into your new system.
  • Failing to write down how your rules work, making it hard for your team to update them later.
  • Making rules too complex when simple ones would work, which makes the system harder to manage.
  • Planning only for the short term, which forces you to rebuild your rules every time your data changes.

Tips for Data Mapping Rules

  • Create clear data models for your source and target systems before you write any mapping rules.
  • Test your rules with common and unusual data to ensure every transformation works correctly.
  • Write down every rule. Explain why it exists and how fields connect from one system to another.
  • Work with the people who own the data to ensure your rules follow your business needs.
  • Automate repetitive mapping tasks to save time and prevent mistakes caused by manual data entry.

Trends Surrounding Data Mapping Rules

  • AI-driven data mapping: Leveraging AI and machine learning to automate the discovery of mapping relationships and suggest optimal transformations.
  • Real-time data validation during mapping: Integrating automated checks within mapping processes to prevent invalid or inconsistent data from reaching target systems.
  • Low-code/no-code mapping interfaces: Providing business users with intuitive visual tools to define and manage data mapping rules without extensive technical knowledge.
  • Dynamic and adaptive mapping: Developing rules that can automatically adjust to minor changes in source data schemas, reducing manual intervention.
  • Enhanced traceability and governance: Tools offering better visibility into data lineage and rule execution for compliance and auditing purposes.

Tools for Data Mapping Rules

  • WISEPIM: Provides robust data mapping capabilities for transforming and syndicating product data to various e-commerce channels and marketplaces.
  • Akeneo: A PIM solution that offers flexible data modeling and extensive mapping features to standardize and enrich product information.
  • Salsify: A Product Experience Management (PXM) platform with powerful data syndication and mapping tools to manage product content across all channels.
  • Informatica PowerCenter: An enterprise-grade ETL (Extract, Transform, Load) tool known for its advanced data integration and complex mapping functionalities.
  • Microsoft Azure Data Factory: A cloud-based ETL and data integration service that facilitates the creation, scheduling, and orchestration of data mapping pipelines.

Related Terms

attribute mappingdata transformationdata ingestiondata validationproduct data harmonization

Also Known As

attribute mapping rulesdata transformation rulesfield mapping rules