Data cleaning steps and techniques

Clear data means clear business objectives—that should be the goal when it comes to your database.

Fifty-one percent of business leaders consider the current state of their CRM/ERP data to be clean and usable, according to our 2020 Global data management report. We believe the moment data enters your database it should be actionable.

For data to be effective, it needs to be clean. Meaning, your names should be spelled right, and your emails, addresses, and phone numbers should be properly formatted and valid.

Here is your guide to data cleansing—one step at a time.

1. Determine gaps within your data.

The first step in any project is to create a plan. When working to cleanse your data, you need to first understand the current state of your database. Consider a data quality health assessment to determine the accuracy of your records. Curious what kinds of data errors or anomalies could be lurking under the surface? You could have customers over the age of 100 or not even born yet! A health assessment kickstarts your data cleaning process because you know what errors exist to being addressing them.

Now, you can determine next steps. Think about this: What do you want to get out of your data? And, what data processes would be easily adopted by your organization? This brings us to our next step.

2. Select a data quality tool.

Data quality tools are foundational to achieving a healthy database. The technology your organization selects is dependent on the purpose of your data—whether its better understanding your customers or complying with regulations. Here are some tools that can seamlessly be incorporated into businesses processes for cleaner data.

If you want to outsource data cleansing you can leverage:

Batch cleaning process for emails, addresses, and phone numbers.
Email verification in bulk.

Incorporating batch or bulk data cleaning can be a streamlined approach without the cost and time of integrating new technology.

If you are looking to establish ongoing data quality checks, you can integrate data quality software into your existing tech stack.

Real-time email, address, and phone verification automatically ensures accurate contact data is entered into digital forms or shopping carts ahead of entering your database.
Data quality management software can be integrated on the back end of your operation to make sure your users are working with accurate data.

Whether you outsource your data verification or implement processes in-house, you are gaining more control over your data, giving you the opportunity to leverage insights for business initiatives.

3. Sustain quality data.

After you’ve done the work to recognize the gaps within your database and select a tool, now it’s essential to implement steps to sustain your success over-time.

When it comes to maintaining quality data, there are perks to having a data quality management platform in-house. You constantly have control over the quality of data and can be agile when new initiatives emerge. However, it is possible to outsource your data cleansing and still uphold quality—you just need to make sure you find a regular cadence to send out your records for validation.

Taking steps to clean your data is crucial to enabling your business with actionable data. Data created and leveraged in the right way can help your people make better and faster decisions. In turn, you can set yourself on a path toward success.