Data Quality Statistics 2023
– Everything You Need to Know

Data Quality Statistics 2023: Facts about Data Quality are important because they give you more context about what’s going on in the World in terms of Data Quality.

LLCBuddy editorial team scanned the web and collected all important Data Quality Statistics on this page. We proofread the data to make these as accurate as possible. We believe you don’t need to check any other resource on the web for Data Quality Facts; All are here only 🙂

Are you planning to form an LLC? Thus you need to know more about Data Quality? Maybe for study projects or business research or personal curiosity only, whatever it is – it’s always a good idea to know more about the most important Data Quality Statistics of 2023.

How much of an impact will Data Quality Statistics have on your day-to-day? or the day-to-day of your LLC Business? How much does it matter directly or indirectly? You should get answers to all your Data Quality related questions here.

Please read the page carefully and don’t miss any words.

On this page, you’ll learn about the following:

Top Data Quality Statistics 2023

☰ Use “CTRL+F” to quickly find statistics. There are total 6 Data Quality Statistics on this page 🙂

Data Quality “Latest” Statistics

  • According to the CRVS systems, since 2000, there has only been a minor improvement throughout the world, with the proportion of deaths reported rising from 36% to 38% and the percentage of children under the age of 5 whose births were reported rising from 58% to 65%.[1]
  • According to Gartner, by 2022, 70% of enterprises will closely monitor data quality levels using metrics, increasing it by 60% to drastically lower operational risks and expenses.[2]
  • To solve difficulties with data quality, over half of respondents, 48%, said they utilize data analysis, machine learning, or AI solutions.[3]
  • Regarding the shortage of resources mentioned by more than 40% of respondents, there is at least some reason to believe that artificial intelligence and machine learning might give the situation a little boost, according to O’Reilly.[3]
  • According to O’Reilly, more than 60% of respondents selected “Too many data sources and inconsistent data,” followed by “Disorganized data stores and lack of metadata,” which was selected by just under 50% of respondents.[3]
  • Over half of respondents, 48%, claim to employ data analysis, machine learning, or AI solutions to solve challenges with data quality.[3]

Also Read


  1. nih –
  2. gartner –
  3. oreilly –

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