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Best practices for Master Data Load & Validation - Part 2

In my previous blog, you read some of the best practices of preparation of data capture template. As you know, data is the fundamental to all performance metrics in your organization, data accelerates discussions, supports in gaining consensus from stake holders and eases decision making in any organization, you make sure to include all the important data fields in the data template during the tempate preparation phase. Preparation of Data Capture Template continues 
  • Maintain version history for the data templates - this helps you to track the changes, to correct errors without affecting previous changes, to append data in the template etc.
  • Follow easy file nomenclatures - this helps you to easily identity the data templates in future, to communicate better using the file names among the team, to avoid work on wrong files etc.
  • Maintain the data templates in an organized folder structure in a document management system for easy sharing and retrieval.

Validating the data before load

Once you capture the data in the template, you will have a holistic view of the available data. According to Gartner, organizations should consider the below mentioned data quality issues

  1. Existence (whether you have the required data)
  2. Validity (whether your data values fall within an acceptable range or domain)
  3. Consistency (whether the same piece of data stored in multiple locations contains the same values)
  4. Integrity (the completeness of relationships between data elements and across data sets
  5. Accuracy (whether the data describes the properties of the object it is meant to model)
  6. Relevance (whether the data is the appropriate data to support the business objectives)

There are basic validations which you validate directly from the template - whether item or customer record has the key information, whether the data type is alphanumeric or integer, whether the field length is correct etc. But there are validations which you measure from an User's perspective - whether the template data includes all the available vendors and customers , whether the GL account of the storerooms are correct ? whether the customer address is the real address ? whether the item availability in the storeroom matches the actual stock availability etc. Find out all such data quality check list, validate the data, find out issues and correct the data in the template before you load the data into the ERP system. Usually, this will undergo multiple iterations and multiple stake holders will review the data as part of pre load validation phase.

Please add your comments and thoughts on this post. I would continue this topic in my next blog.

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