A comprehensive guide to data integrity for businesses

Whether you’re responsible for a multibillion-dollar corporation or a startup with a handful of employees, maintaining data integrity is important for keeping your company on a sound financial footing and in step with your customers’ needs. But do you understand the nuances of data integrity? This quick guide will walk you through.

In simple terms, data integrity is the accuracy, completeness, reliability, and consistency of data you store over time and across formats. Data integrity builds trust within your organization and with your customers and stakeholders.

Before we get into the benefits of data integrity, let’s take a look at its four essential elements.

• Accuracy: Your data should be free of errors, which can happen whenever you type a field or command in your database or CRM system, or while transferring data between systems.
• Completeness: Your data should have all the necessary parts you need to make the best decisions and meet your customers’ needs. A missing price entry in your sales system, for instance, can translate into lost sales and lost customers for life.
• Reliability: Reliable data is data that remains stable over time, giving you similar results when conditions stay the same. Unreliable data can lead to incorrect conclusions in your research, analysis, and decision-making.

Consistency: Your data is consistent if it is represented the same way across systems and over time, unless you change or update it intentionally.

In 1998, after nine months in orbit, NASA’s Mars Climate Orbiter burned up as it entered the Red Planet’s atmosphere. The fiery destruction of the $327 million spacecraft was the result of a simple unit conversion error between engineering teams — one team used metric units, the other imperial.

The lesson of that disaster is that inconsistent, inaccurate, or incomplete data can cost your organization time, money, and reputational damage. A recent survey of businesses by Salesforce and Tableau found that mistrust of data is widespread. Only 45% of marketing, 42% of sales, and 40% of service decision-makers trust their data. As businesses increasingly rely on data to operate effectively and interact with customers, the mistrust can chip away at a company’s bottom line.

Clean, trusted data is also a prerequisite for AI-powered apps. Eighty-six percent of analytics and IT leaders agree that AI's outputs are only as good as its data inputs. In other words, the ability to capitalize on AI starts first and foremost with ensuring the quality and integrity of your data.

Building and maintaining data integrity—data that is accurate, complete, reliable, and consistent—is not merely a nice-to-have. It’s a necessity if you want to stay competitive and compliant, build trust within and outside your company, and avoid reputational damage. Below are the top three benefits of data integrity.

Clean, trusted data is essential in every industry. One obvious example is healthcare, where research and clinical data drives decisions about patients, treatment plans, and the development of new therapies. Financial institutions depend on accurate, trustworthy data for financial projections, risk management, and compliance, as well as for their reputations. And NASA relies on data precision and accuracy for the success of its missions and the survival of its spacecraft and crews.

If you invest the time and effort to build trust in your data, it can become a competitive advantage. Williams-Sonoma, for example, has collected years of customer data, such as online transactions, and uses Data Cloud to store and clean it. When the data shows customers may be ready to purchase an air purifier table based on their past purchase of an air purifier, Marketing Cloud triggers emails tailored to those customers.

But there’s another important benefit to trustworthy data: higher employee productivity. According to Gartner, high-quality data can increase productivity by as much as 20%. Imagine if IT didn’t have to rush to do data cleaning before every meeting and instead could focus on innovation. Or if your analytics teams finally found the time to dig up insights and drive predictions.

The benefits of trustworthy, high-quality data ripple across the entire enterprise.

Data accuracy and reliability have long been essential elements for data-driven decisions and for running a business effectively. Now that advances in AI and generative AI (GenAI) are happening so fast, the need for quality data is even greater. Nearly 9 in 10 analytics and IT leaders we surveyed said new developments in AI make data management a priority. Yet 78% reported that their organizations struggle to drive business priorities with their existing data.

Launching AI and GenAI apps without trustworthy data is like pouring diesel into a gas tank. Your car may start but it will stall as soon as you shift into drive. For your AI apps, bad data can translate into unreliable chatbot suggestions for service teams, incorrect product recommendations for marketing, and inaccurate forecasts for leadership.

General Mills is one example of a company that harnesses the power of good customer data and AI to drive precise marketing emails and ads. Using Data Cloud and AI, the food giant analyzes behavioral and purchase data, makes product recommendations, and determines the optimal time to send email. General Mills has increased its known-site users 170% year over year, tripled customer engagement, and increased “buy now” clicks by 40%.

As a business leader, you are the custodian of your customers’ information and data. Whether you maintain personally identifiable information (PII) such as Social Security numbers, financial records, or patient data, there’s an obligation — and often a regulatory requirement, such as the General Data Protection Regulation (GDPR) — to safeguard and maintain it. The cost of noncompliance can be astronomical. Last year, Facebook owner Meta was fined 1.2 billion euros for transferring the personal data of European users to the U.S. without sufficient data protection.

Poor data will slow you and your teams down and cost your company money. Stay on top of data integrity to reach data-based decisions quickly, power your AI apps, stay compliant with regulations, and keep your company’s reputation intact.