Data Quality

What is it?


Data Quality refers to the accuracy, consistency, completeness, and reliability of data within an organisation. There are several different aspects of data quality: 

  • Data should be accurate and reflect the real-world values it represents. 
  • All necessary data should be complete, with no missing information. 
  • Data should be consistent within itself and across different systems or datasets. 
  • Data should be up-to-date
  • Data should be valid and conform to the defined formats, standards, or business rules. 
  • Data should be unique. There should be no duplicate records unless explicitly allowed. 
  • Data should be relevant to its intended purpose. 

Data Quality is key to using data to make critical decisions and, ultimately, derive value from it. Good Data Quality practice ensures that data is fit for its intended purpose. 



Why is it important?


Why is it important? 

The quality of an organisation’s data will affect the accuracy of analysis and insights derived from that data. Bad data will lead to misinformed decisions that can affect a business's bottom line. 

 

Moreover, poor data quality can lead to a loss of trust among employees in the accuracy of reports, insights, and analysis in their technology systems, affecting end-user uptake and leading to inefficient processes. 

 

Externally, ineffective technology processes caused by poor data quality can lower the reputation of an organisation if it puts out inaccurate reports. In regulated industries, this can even lead to financial penalties. 

 

With good Data Quality protocols, businesses can avoid these risks and make better-informed strategic decisions that drive growth and efficiency. 

 

How Amino can help you deliver 

Amino has delivered many successful Data Quality initiatives to organisations. These go hand-in-hand with Data Governance initiatives. Moreover, assessing an organisation’s data quality often reveals new opportunities to exploit existing data in new and innovative ways, adding even more value. 


Please contact us to discuss how we can help you with your Data Quality requirements. 





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