How to Check the Accuracy of your Database

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Asad Zulfahri
Asad Zulfahri



Just like every pilot has a pre-flight checklist to ensure no important tasks are forgotten before takeoff, so too should business owners carry out checks before working with data.

You might need to sync new apps, send a large email campaign, or create a business intelligence dashboard. However you plan on using your data, you need it to be accurate.

Data accuracy works hand in hand with data completeness and consistency as key ingredients for achieving data integrity, which maximizes the value of every database.

With accurate data, you can trust the correctness and rationality of your data, comfortably sync it with other apps, and create valuable business insights. And without it, you risk your business's time, budget, and resources fixing the negative consequences of bad data.

One of the most effective and simple ways to ensure the accuracy of your data is with a data accuracy check.

A data accuracy check, sometimes called a data sanity check, is a set of quality validations that take place before using data. For example, syncing data between apps, starting a new marketing campaign, or turning data into business insights. Data accuracy checks include cleaning data, merging duplicates, and ensuring data is organized in the correct structure.

To help you maintain a high level of data accuracy and integrity, read on for the key components to include in every effective data accuracy check.

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Data Accuracy Checks Are Part of Good Data Management

Before you carry out a data accuracy check, first make sure your database is in otherwise good shape. After all, regular data accuracy checks work best alongside wider data management best practices. These include:

  • Secure and reliable systems for data storage, backups, and transfers
  • Adherence to data protection regulations such as GDPR
  • Documented processes to reduce human error
  • Check constraints to require new data to be inputted in a certain format

With these best practices at the foundation of your data management strategy, you minimize the effort required for data accuracy checks and receive the highest value from your database.

What to Include in a Data Accuracy Check

You can think of a data accuracy check as the final step before moving, integrating, or working with your database in another way. To help ensure that nothing falls through the cracks, here are the key steps to include in every data accuracy check.

1. Cleaning data

The most important first step in a data accuracy check is making sure you have clean data. With data purging, you can remove data that is inaccurate, incomplete, duplicated, outdated, or unnecessary. It only takes one rotten apple to spoil the pantry, and the same goes for your database too. Working with poor-quality data can cause more harm than good, so take the time to remove data that doesn't serve your business now and your future self will thank you later.

2. Data merging

Once you've removed the most obvious poor-quality data from your database, turn your attention to duplicate data. With find and merge software, you can identify duplicate contact records that can safely be merged. Here are some of the best options for finding and merging duplicate contacts:

  • HubSpot's deduplication tool - Use AI to find duplicate contacts and companies in your CRM.
  • Google Contacts and iCloud - If you're using these apps for contact management, both offer useful built-in dedupe features.
  • Dedupely - This app works with HubSpot, Salesforce, and Pipedrive to flag possible duplicates for first name, last name, email, company name, and other properties. It also finds duplicates by exact, fuzzy, and similar matching to detect issues that other systems miss.

After using find and merge software, take a few minutes to manually check that your data looks as it should and that there aren't duplicates left behind.

3. Organizing data

A final part of your data accuracy check is to make sure your data is in the right structure for integration or analysis. When you sync or move data, it's important to make sure that all relevant original properties go with it.

One of the most straightforward ways to organize your data is with tags, labels, or list memberships. This means you can maintain accurate segmentation after integrating data to other apps, creating reports, or using it for automation.

After a Data Accuracy Check

Once you've completed your data accuracy check, you can breathe a little deeper and put your data to work without panicking at the sight of the "go" button.

A data accuracy check also paves the way for other data management best practices, including creating a two-way sync between your apps. This is your easiest way to sync data from the most authoritative source to your other apps, such as from your CRM to your email marketing app or automation software. It creates a single source of truth in every app, so you always know you're looking at the most accurate version of your data.

Maintain the Integrity of Your Database

Before putting your data to work, check that you can comfortably answer these three essential data accuracy questions:

  • Is my data clean?
  • Is my data free of duplicates?
  • Is my data organized in the correct structure?

Data accuracy checks are just one part of the parcel of maintaining a high-integrity database. By cleaning data, merging duplicates, and organizing data with a clear structure, you can optimize the value and impact of the insights at your fingertips.

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Topics: Integrations

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