Data Quality Statistics 2023 – Everything You Need to Know

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Are you looking to add Data Quality to your arsenal of tools? Maybe for your business or personal use only, whatever it is – it’s always a good idea to know more about the most important Data Quality statistics of 2023.

My team and I scanned the entire web and collected all the most useful Data Quality stats on this page. You don’t need to check any other resource on the web for any Data Quality statistics. All are here only 🙂

How much of an impact will Data Quality have on your day-to-day? or the day-to-day of your business? Should you invest in Data Quality? We will answer all your Data Quality related questions here.

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

Best Data Quality Statistics

☰ Use “CTRL+F” to quickly find statistics. There are total 55 Data Quality Statistics on this page 🙂

Data Quality Market Statistics

  • Every year, 25 30% of data becomes inaccurate leading to less effective sales and marketing campaigns Businesses lose as much as 20% of revenue due to poor data quality. [0]
  • For example, if 30 out of 100 records in your analysis is missing the industry feature that you need for your marketing campaign, the completeness of your data is 70%.First, check the number of missing valuesSELECT1 — COUNT. [1]
  • 54% of businesses cite data quality and completeness as their largest marketing data management challenge. [2]
  • 57% of marketers are getting diminished results as a result of misinterpreting data. [2]
  • 33% of elite marketers say having the right technologies for data collection and analysis is the most useful in understanding customers. [2]
  • 87% of marketers think data is an under utilized asset at their company. [2]
  • Approximately 20% of the average US marketing budget is spent on data. [2]
  • Just 7% of B2B marketers have fully automated personalization. [2]
  • 55% of US marketers say privacy rules hurt programmatic targeting. [2]

Data Quality Adoption Statistics

  • Among Fortune 1000 executives, 95% cited cultural factors as blocking big data adoption, compared with just 5% citing technology. [2]

Data Quality Latest Statistics

  • Employees waste up to 50% of their time dealing with mundane data quality tasks 40% of leads contain inaccurate data. [0]
  • 41% of companies cite that inconsistent data across technologies , as their biggest challenge. [0]
  • Only 16% of companies characterize the data they are using as “very good”. [0]
  • In the next hour, 59 business addresses will change, 11 companies will change their name, and 41 new businesses will open 15% of leads contained duplicate records. [0]
  • In 2006, the Office of Management and Budget published Standards and Guidelines for Statistical Surveys requiring that all Federal surveys with a unit response rate of less than 80 percent conduct an analysis of nonresponse bias. [3]
  • Of these, the topranked PC series explain more than 90 percent of the variation in the data, so visualizing them allows us to inspect table. [4]
  • Globally, only modest progress has been made since 2000, with the percentage of deaths registered increasing from 36% to 38%, and the percentage of children aged under 5 years whose birth has been registered increasing from 58% to 65%. [5]
  • According to this estimate, the cost of a poor record is approximately $100 100k bad. [1]
  • Another study by IBM estimated that the annual cost of bad data in the United States is around $3.1T T for Trillion!. [1]
  • The problem was that 90% of these records were missing in the database. [1]
  • Boxplots visualize a distribution by plotting the five important numbers minimum, maximum, 25th percentile, median and 75th percentile of the distribution. [1]
  • smaller than 25th or greater than 75th percentiles where IQR is the distance between 75th and 25th percentiles. [1]
  • Business spend on firstparty data management, processes and integration grew to $5.5 billion in 2019, an increase of 9.8%, while investments in third party data management reached $11.9 billion, an increase of only 6.1% during the same period. [2]
  • Data quality issues costs the US economy an estimated $3.1 trillion per year. [2]
  • Internal data management using a mix of commercial and homegrown tools is set to increase by 40% within two years. [2]
  • Fully outsourced data management will fall by 48% within two years. [2]
  • 62% of US retailers have over 50 systems housing customer data. [2]
  • On average 20% of database records contain contact data with data quality issues. [2]
  • Employee turnover causes approximately 3% of business records to become outdated every month. [2]
  • On average, 65% of contact data generated from online web forms is invalid. [2]
  • By 2025 the amount of data created, collected, or copied in China will increase from 7.8 zettabytes to 48.6 zettabytes, accounting for 27.8% of the data generated globally. [2]
  • During this same period the US share will only account for 17.5% of data generated globally. [2]
  • The amount of data created by consumers doubles every two years, but 99% of new data is never used, analyzed or transformed. [2]
  • In terms of how business leaders interact with data, 70% of time is spent finding data with only 30% analyzing it. [2]
  • Approximately 47% of new data collected by businesses has one or more critical errors. [2]
  • Only 3% of business leaders think their department has an acceptable level of data quality. [2]
  • Companies with a Data Governance program in place increase data analysis time by 2% and register a 31% improvement in data quality confidence. [2]
  • Businesses with a designated Data Governance or Data Management leader show 42% greater confidence in data quality than those without. [2]
  • 70% of US advertisers say confident media spending requires a more transparent and addressable supply chain. [2]
  • 92.3% of businesses maintain databases to host information on customers and prospects. [2]
  • Network security (57.2%), web security and data security (both 55.7%), and fraud prevention (55.2%). [2]
  • Only 21% of CMOs own 90% or more of their tech budget. [2]
  • Nearly one third of high performers (31%). [2]
  • In 2017, a total of 83% of companies said they perform data compliance audits each year. [2]
  • Across the 600 largest companies in the US, 40% have operational CCPA rights portals. [2]
  • Of the 600 largest public companies and 100 largest private companies, only 16% have a ‘DoNot Sell’ website link in response to CCPA. [2]
  • One in three Publishers have no cookie free ID solution in place and 77% authenticate less than 50% of their visitor traffic. [2]
  • Third party cookies found on European news sites have decreased by 22% since GDPR went into effect. [2]
  • 59% of brands and 40% of agencies either have already appointed or plan on appointing a Data Protection Officer. [2]
  • The cost of a data breach to business has increased by 10% in recent years. [2]
  • For consumers who had experienced an online security incident, such as an account hack, data breach or a stolen password, 27% estimated that the incident ended up costing them $100 to $10,000 or more. [2]
  • In 2018 46% of businesses suffered a data breach. [2]
  • That number was only 24% in 2017. [2]
  • 77% of global consumers would stop doing business with a brand that lost their data or used it irresponsibly and 32% opted out of personalized advertising in the past year. [2]
  • The SUPPORT Act also authorizes the Centers for Medicare and & Medicaid Services to match State investments in their PDMP at 100 percent for approved design, development, and implementation activities, for quarters during fiscal years 2019 and 2020. [6]

I know you want to use Data Quality Software, thus we made this list of best Data Quality Software. We also wrote about how to learn Data Quality Software and how to install Data Quality Software. Recently we wrote how to uninstall Data Quality Software for newbie users. Don’t forgot to check latest Data Quality statistics of 2023.


  1. ringlead –
  2. towardsdatascience –
  3. dataservicesinc –
  4. ed –
  5. uber –
  6. nih –
  7. medicaid –

How Useful is Data Quality

The importance of data quality cannot be overstated. When organizations have access to high-quality data, they are equipped to harness the power of information to drive performance and success. Dependable data acts as a reliable compass, providing guidance and direction. It enables organizations to gauge the effectiveness of their strategies, identify areas for improvement, and better understand their customers, industries, and markets.

In the absence of data quality, an organization is merely sailing blindfolded in an ocean of uncertainty. Without reliable and accurate data, decisions are based on guesswork and conjecture rather than evidence. Mistakes that could be easily averted with the right information often go unidentified until it is too late, resulting in inefficiencies and missed opportunities. In today’s fast-paced business environment, the luxury of trial and error is a luxury no organization can afford.

Moreover, data quality is of utmost importance when it comes to maintaining customer relationships and satisfaction. In a world where customer preferences and expectations change rapidly, organizations need to stay ahead of the curve to retain their competitive edge. High-quality data enables organizations to understand their customers, personalize their offerings, and create memorable experiences. It empowers organizations with the ability to address individual needs and preferences, fostering loyalty, and customer satisfaction.

Furthermore, data quality impacts an organization’s ability to collaborate effectively. In an interconnected world, information is shared seamlessly, cutting across organizational boundaries, departments, and even borders. When organizations rely on trustworthy data, they can communicate and collaborate more efficiently, promoting greater coherence and synergy. This improves outcomes and productivity as diverse perspectives are harnessed and aligned towards shared objectives.

However, achieving and maintaining data quality is not without its challenges. The sheer volume and variety of data that organizations generate, collect, and analyze have skyrocketed in recent years. The exponential growth of big data has made it increasingly complex to ensure data quality across multiple sources and platforms. Organizations need to invest in robust data management systems and processes to ensure that data is accurately captured, stored, and shared.

Moreover, data quality necessitates constant vigilance and ongoing commitment. Organizations need to devote resources to monitor and maintain the quality of their data, identifying and remedying shortcomings promptly. They should establish stringent data governance frameworks that enforce data integrity and adherence to quality standards. Additionally, ensuring data quality is a collaborative effort, requiring the engagement and commitment of all stakeholders within an organization.

In conclusion, data quality is an indispensable asset that organizations cannot afford to neglect. It serves as the bedrock upon which successful organizations are built, providing a solid base for reliable decision-making, accurate analysis, and effective operations. Whether it be in gauging performance, understanding customers, or deriving actionable insights, high-quality data serves as the compass that steers organizations towards success. Thus, organizations must prioritize data quality in order to thrive and remain competitive in the dynamic business landscape of today.

In Conclusion

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We tried our best to provide all the Data Quality statistics on this page. Please comment below and share your opinion if we missed any Data Quality statistics.

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