Why is Data Cleansing Necessary and What are it's Techniques?

It’s no longer a secret that data is the backbone of a business. Reliable data is crucial to make the best business decisions. However, having data isn’t enough to lead a successful business. Poorly managed data will only waste time and resources and may lead to more damage than benefit.

To remove trash from data and make it highly usable, the very first step (after data collection) is data cleansing. When a company uses data for marketing, sales, or to maintain customer or business records, cleansing is a very integral part of it. If not cleaned correctly, it can lead to a considerable loss in several aspects for small and large businesses. This is where the role of appropriate data cleansing comes in. 

Here is a guide for data processing where importance, effective techniques, and much more are covered.

Importance of Data Cleansing in Today's Era

You can easily accumulate a lot of personal data on your PC and in today’s era. Mortgage information, legal names, birth dates, tax information, credit card, or banking information can be stored in different forms on your PC or other storage devices. Data cleansing becomes highly important when your business has a vast database stored in different forms and should not be avoided or delayed. If information is stored in hard-copy format or scattered in different types of files and different styles (excel, PDF, charts, texts, images, etc), it becomes complicated and highly unproductive to find and use the data. Your business will not only face difficulties but may also face data loss, equivalent to treasure loss in today’s era.

That’s where data cleansing and data enrichment services come in handy and eliminate all the above problems and beyond. It also ensures you have only the important and most recent documents/files. And when needed, you can locate it with just a few clicks. It also decreases security risks, such as data breaching, by ensuring that you don’t keep significant personal information on your devices.

Effective Data Cleaning Techniques

• Error Fixing

With a high volume of data, a lot of errors are expected. Errors as minor as typing mistakes can make the complete section useless. Most such errors can be fixed by using AI in the form of spell-checking or auto-correct. Also, inconsistent formatting is a primary type of error found in data.

• Proper Formatting

This is highly crucial for AI and machine learning modules. You can’t feed irregular or heavy formatting to these modules. Gathering data from different sources and in different file formats often leads to distinct formatting. It’s crucial to always remove all types of formatting from all documents and files. This way, you will be able to start from zero.

• Data Type Conversion

One of the most common data types that require cleaning is numbers. It’s a common practice to mention numbers by typing alphabetically, but they should be numeric to be processed. Alphabetical words are classified as strings and hence cannot be processed by analysis algorithms. This stops mathematical equation processing. The same goes for the dates, if stored as text, and should also have uniform formatting like DD-MM-YYYY.

How Do Companies Cleanse Your Data?

• By Removing Duplicate Contacts

It’s achieved by using deduplication tools and different companies use different de-duplicators. The good thing about this is it needs to be done only once. Companies like email verification tools also use data validation tools to determine data validity.

Companies have started using a central database to collect all data in one place to avoid duplicacy in the future. This should be done once existing data is cleansed.

• By Fixing Missing Data

By removing the entries, having missing values, or if the missing information is available elsewhere, fill it up from the dataset. If it doesn’t work for companies, then the next thing they do is flag it as MISSING DATA. 

• By Keeping Data Up-to-date

As per the study by Vainu, about 30% of a company’s data will become out-of-date or irrelevant in just one year after it’s collected. This is being minimized by sending frequent reminders to their customers to update their information. When logging in to banking sites, OTT platforms, or just your regular email, these companies prompt you to check the information and either accept it as CORRECT or click UPDATE to regularly get the latest and relevant information. Other methods include using parsing tools for scanning all incoming emails and making changes accordingly. 

Outsourcing Data Cleansing to a Services Provider 

• • Cost-Effective
    
    
  • No Need to Spend on Resources
    
    
  • Allows Companies to Scale Up
    
    
  • productivity of skilled resources
    
    
  • Outsourcing makes you competitive

Conclusion

It’s time-consuming to clean a lot of business data, but skipping or even delaying data cleansing can cost you much more than you can estimate. If your business is facing difficulties handling or cleaning the data, outsourcing it to data cleansing companies in India can save a lot of time and effort. Also, if your existing in-house staff isn’t able to cleanse data up to the required quality, this problem can be eliminated by outsourcing data cleansing services.

Also, once you have clean data, you only need the right tools for analyzing it and facilitating improved business decisions. Outsourcing can expedite this process and streamline overall decision-making.