What is Data Cleaning? Why Your Database Needs a Cleanse

Data cleaning robot

Modern-day business is driven by data and information – whether you are a multi-national corporation with thousands of employees or a local tradesman trying to grow your business into more local areas. The problem with all of this data is that it requires regular maintenance to stay accurate and useful to your company. Data scientists spend up to 60 per cent of their time cleansing data, which can sound quite intimidating to a business that doesn’t even have a data scientist!

What is Data Cleaning?

As you collect contacts and leads for your company and store sales data over time, errors and other issues will come up in those data sets. Data cleansing is the process of removing erroneous records and standardising misspellings. The goal is to eliminate problems that would muddy analysis or cause you to spend more money than you need to on marketing. To put this into perspective, here are a few examples.

Example 1

Your dry cleaning business has an extensive database of previous clients. Every time a new company or person does business with you, one of your employees puts in their contact information into a spreadsheet or database. Over time, this list has become huge! However, as you look through it, you notice that there are duplicates with misspellings, and the street names aren’t standardised. You work with data cleansing software to help you validate the addresses on file, remove duplicates, and make sure that all the contact information you have is correct. While doing this, you save yourself money on marketing that would have gone out to incorrect addresses.

Example 2

Your eCommerce brand has been growing over the last few years! Your team has begun pulling in more and more data to base your business and marketing decisions on – but not all of it meets your standards. Some errors in the data mean that the last projections you sent to your leadership board looked a bit off. It turns out that some of the new data sources don’t match the same way you calculate revenue, sales, and other performance indicators. Now your team has the monumental task of figuring out how to clean this data up so you can trust it again.

Data cleansing, by a more technical definition, is the process of preparing information for use or analysis by removing incorrect information and formatting the remaining data in a way that it can adequately be used or analyzed accurately. Data cleaning goes beyond removing incorrect information and makes the data more complete and useable by standardizing data sets and enriching the data by completing missing fields. Data cleansing is a fundamental building block of data science – but don’t let the name intimidate you. The process of scrubbing your data and preparing it for use is critical for every business.

Data Cleansing: The Why

The number one reason you should be cleansing your data is that not doing it costs your company a ton of money. The data-savvy in your company waste their time validating data. You make incorrect decisions based on bad data, and you spend money on marketing campaigns that could have smaller budgets if you had cleaned up your database before.

On the other side of (your business) coin, cleaning up your data can be a hidden gold-mine of opportunity that you’re already sitting on. Validating your data for your marketing database can uncover hidden opportunities, and can deliver better results for your marketing campaigns. 

So to sum up and add a few more reasons, here is the “why” of data cleansing:

  • Make More Money: See higher revenue by taking advantage of your existing opportunities and reduce costs
  • Accurate Insights and Forecasts: Know what is going to happen with your sales with better forecasting and see more opportunities in your data
  • More Efficiency: Save the time of your employees who handle data by taking the burden of correcting records off of them and open up more of their time for analysis. For smaller businesses, save time on any data-entry related tasks.

How to Get Started: The Basics Of Data Cleansing/ Data Scrubbing

Great! So you’re sold on the idea that data cleansing is a critical part of modern businesses – so what are the basics? Every data cleansing project has necessary steps that can help outline where to get started.

Data quality can be broken down into a few categories to evaluate and improve the data sets:

Validity: Data validity can be described as “is this data in the right format?” If you have phone numbers in your database, they may need to follow a certain format to be easily used by any of your calling systems. If a phone number is incomplete or is missing an area code, for example, that entry isn’t valid and needs to be corrected.

Accuracy: A phone number or an address might follow a valid pattern, but it could be a fake number. Accuracy is the next critical step in evaluating data. You need to make sure that the information you have matches reality as close as possible. Data cleansing databases and software can be an excellent way to evaluate the accuracy and validity of your data by matching it with known public databases.

Completeness: Filling in the blanks is another way to cleanse your data. By finding records that are incomplete and enriching the data, you can fill in any holes you may have in your current opportunities.

The Steps Of Data Cleansing

Data cleansing is an ongoing process; whether you use an experienced company like Lead Lists or are taking it in-house, you will find that having a standardised process will lighten the load of your employees and give you access to more and more quality information.

Some tips on getting the most out of your data:

  • Use standardized formats: For dates, names, and addresses begin using standardized formats that can easily be recognized and kept up to date.
  • Reporting: Report on the errors that have been improved and how your database is changing over time.
  • Match Your Data To Outside Databases: Use external databases for public and business records to validate your customer data and addresses - especially before launching a new marketing campaign!

How Long Will Data Cleansing Take?

Data cleansing is an ongoing process that you should continue to maintain frequently. The amount of data you currently have, the resources internally and externally at your disposal, and the current quality of your data will indicate how long your project will take.

A quick customer contact cleanup can take as little as a week if you are using an external tool to validate your records. If you have massive databases with mixed formats of data coming in from multiple sources, a data cleansing project can take much longer and will continue to be part of your company’s workload.

Data Cleansing - A Conclusion

Data scrubbing is an essential part of your business. Having up-to-date, accurate data will save your company money and help your analysts spend their time on insights instead of fixing records.

To learn more about how we can help you get the data your company needs, contact us today.

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