A comprehensive guide to data integrity for businesses

Whether you’re responsible for a large corporation or a startup with a small team, 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 ins and outs of data integrity? This quick guide will walk you through.

Think of the ambitious rollout of Aadhaar, India's biometric digital identity system. If the demographic data collected for crores of citizens contained inaccuracies, such as incorrect names or dates of birth, it could have led to individuals being denied essential government and private services, with far-reaching consequences.

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 organisation time, money, and reputational damage. Salesforce and Tableau’s State of Data and Analytics report, based on the survey of over 10,000 analytics, IT, and business leaders around the world, including India, 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. 96% of analytics and IT leaders in India agree that AI's outputs are only as good as its data inputs. In other words, the ability to capitalise 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. If you invest the time and effort to build trust in your data, it can become a competitive advantage. Royal Enfield, an iconic motorcycle brand with a global legacy of more than a century, has walked the talk on this. It unified its sprawling data - over 1.7 crore customer profiles – from 80+ diverse data streams and 820 data fields including purchases, preferences, intent, and behavioural footprint – into 90 lakh unique, unified customer profiles with Data Cloud. This single source of truth harmonises data previously scattered across dealer CRMs, ERP, and digital platforms.

Tapping into this richer customer understanding, Royal Enfield now uses Marketing Cloud to deliver highly targeted and contextual communications at scale across the customer lifecycle. This has led to a 100% improvement in customer engagement rates, and a 50% drop in communication volumes, translating into a clear ROI boost.

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 organisations 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 360 and AI, the food giant analyses behavioural 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.