22 October 2021

The Importance of Updated Data

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Synthio.com found that about 67% of businesses are dependent on CRM data to further develop their net income. The figure shows that data has become an aspect that is crucial for the sustenance of an organization. 

Nevertheless, almost all B2B companies (94%) do not feel certain about the accuracy regarding their data. The anxiety isn’t something unreasonable, though. 

In a world where massive volumes of data are generated, some of these data may be irrelevant or even misleading. This is why data cleansing is an important part of a business, and this is where the right analytical tools such as Telkomsel's MSIGHT play an important role in helping businesses have telco data insights so they can make the best decisions.

What is Data Cleansing?

Like the name suggests, data cleansing (also called data cleaning) is a process of correcting and verifying data, making the data records you own as clean as a natural spring. 

When you have a clean database, your organization will work more efficiently, as there will be significant reduction in errors. Your team also wouldn’t have to spend a lot of hours dealing with misinformation or revising works. 

In addition, data cleansing can also help you reach your customers more effectively. 

What would happen if your data wasn’t cleaned? To put it simply, er… utter chaos and mayhem. Incomplete, invalid, duplicate, and misleading data could spawn a number of serious problems. 

Inaccurate consumer data, for example, can lead to inaccurate marketing and sales targeting. Duplicate data may also cause delays in finance reports, making further delays in decision-making. 

If your organization conducts goods delivery, incomplete data may also lead to delivery problems, which would lead to complaints from customers.

Data Cleansing Makes Everything Better

Still not convinced about the importance of data cleansing? Here are some benefits your companies can get with regular data cleaning:

• Better Development. Lack of clean data, for instance, is believed to hinder AI development in the healthcare sector. 

A better set of data can ease your business development, particularly in digitization processes and the use of AI. 

• Better and Faster Decision-Making. Valid data greatly reduces error not only in day-to-day work, but also during the process of making critical decisions. 

Updated sets of data can help business managers decide business direction.

Better Compliance. Data cleaning can even help you comply with GDPR. Proper sets of data can minimize the risk of privacy breach, especially in reaching out to customers.

How Should I Clean Data?

Data cleansing is a very intricate process, which can be overwhelming for some. Eliminating duplicates and irrelevant data, for instance, is a necessary step in data cleansing. 

Some data may also be missing, and this requires immediate attention. Check on the data entry process, and if possible, revise the SOP (many errors result from an improper data entry). 

Also, don’t forget to coordinate with the QA department to validate your data. In the end of data cleansing, you want your sets of data to be valid, accurate, complete, and consistent.

…but it sounds like a lot of work?

Data cleaning sounds like a lot of work because it most probably is. But considering the risk of using improper data, data cleansing is totally worth-doing. 

Manual data cleaning can take a lot of hours, which can delay the completion of other works, so facilitating your data management process with appropriate tools is important. 

A reliable tool such as Telkomsel’s MSIGHT can help business managers to be informed about risk-related information, telco score, and API insights can cut off a lot of workloads during data management.


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