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Tailor made for your data quality migration needs, iData provides 100% assurance of your migrated and transformed data. Find out more
 

 

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How did we do? Client Testimonial

" Excellent collaboration as always the resource supplied was ideal for our requirements."

Paul Turner
Test Manager, Irwin Mitchell LLP
 

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What are the key steps to Data Validation?

What are the key steps to Data Validation?

What are the key steps to Data Validation?

First of all - What is Data Validation? 

Data validation provides the mechanism for checking the accuracy quality and authenticity of your data, typically performed prior to moving or migrating data.
Data validation can also be considered as a form of data cleansing, by assuring that your data is complete. Cleansing highlights blank or null values and assures that data unique and contains distinct values that are not duplicated.

Often, data validation is used as a part of processes such as ETL (Extract, Transform, and Load) where you move data from a source database to a target data warehouse so that you can combine and merge it with other data for analysis. Data validation’s key role is to help ensure that when you perform analysis, your results are as accurate as they can be. 

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What is Data Extraction?

What is Data Extraction?

What is Data Extraction?

Data extraction involves retrieval of data from many different sources. It is common for companies to extract data in order to process it further, migrate the data to a data repository such as a new CRM, data warehouse, data lake or to further analyse it.

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