Cleaning up

Is your database clean? Were you aware that a bad database can hamper your business? Before we start to know something, we need to know the purpose of the same. And to know the purpose of anything, we need to first know the source of that thing. Thus, in this article, we will discuss the need for data cleansing followed by highlighting the process for doing the same.

In today's fast-growing economy, digitalisation is no longer an option; rather it has become an inevitable process through which businesses choose to connect with their potential clients. The customer is the backbone of a business. So to store and manage information of the customers easily and efficiently, organisations use digital databases. But, as we all know, with every advantage there comes a disadvantage too. And in using a database, the most terrible disadvantage is the occurrence of dirty data. Yes, databases can also become dirty when inaccurate, incomplete or inconsistent data emerges and here data cleansing comes to the rescue.

Need for Data Cleansing

It is obvious for businesses to do cost-cutting and they don't even put money on anything till they find it to be an investment. Duplicate information or outdated materials have become a source of torment for companies, so more and more organisations are investing in the same.

Data Cleansing is a process of alteration to retain only accurate data. Following here are the reasons for data cleansing becoming an essential part of businesses-

Profitability Index-Spotting and rectifying the database can help companies to increase their revenue. Useless data causes businesses to waste their money on uninterested consumers which they can easily skip by maintaining only that data which are relevant for them to grow. Data cleansing helps businesses to know their potential customers, thus, reaching them quickly and conveniently, which is the most important part of business strategy.

Rate of Productivity- An organisation becomes a successful business because of its hard-working and intelligent employees. The social media and marketing team is responsible for showcasing the talent of the organisation in such a way that target consumers get attracted to them. Identifying the potential customers, encouraging and engaging them to purchase the product by promoting the brand through continuous brainstorming ideas, is not a cakewalk. If marketing executives find the details of the clients incorrect and full of duplication, then it becomes a tedious task for them and decreases their productivity. Clean data make employees use their work hours productively. Data cleansing also assures a reduction in the risk of fraudulence.

Efficient Decision Making- Low-quality data leads to misinformation which makes our decisions ineffective. To make large-scale choices, businesses rely on data and leaders of social media depend on databases to communicate with their precious clients. Clean data is an aid in the overall decision-making process. When money and effort get wasted, it imparts a negative effect on the organisation.

Process of Data Cleansing

The purpose of data cleansing is to replace, modify or delete the data set that has irrelevant, incorrect or incorrectly formatted information. Before starting the process, ask your team members- What is the purpose of our data cleansing? Follow up with- What is our plan to execute the data cleansing process?

From this article, you must have the answer to the first question. Now we can move on to getting the answer to the second question. Let us operationalise our response in the following steps-

Make a Strategic Plan- Sit with your team leaders and discuss the following in order. First, establish the key performance indicators of data quality. Next, rationalise a method to track the health of your database in real-time. Finally, introspect by investigating the source of your dirty data.

Standardise your Data Entry- As we all know prevention is better than cure, the same applies in the case of your database too. Prevention can be done when you know the sources of the disease. One of the sources of dirty data is data entry. It is significant to check the important data at the point of entry as it ensures that you have put standardised information into your database and that too without duplicity.

Rigorous Data screening and Scripting- Appropriate tools and software must be used for the job at hand. Screening and scripting ease your task, identifying duplicate data, making your business cost-efficient and saving you time and energy.

Analyse the Data- This step provides information for business intelligence and analytics.

Analysing the data and communicating the whole process with your team makes your organisation stronger while targeting potential customers. Data cleansing is a time-consuming activity but automation makes data cleansing efficient and easy. Businesses which think data cleansing can be done manually are likely to fall into the trap of dirty data. Manual cleansing means more unhygienic data as human errors emerge, leading to an unending loop of dirty data. Automation, on the other hand, creates and configures data cleansing task within a few minutes.

Conclusion

When different departments of an organisation enter relatable information into separate silos, duplicity is natural and it becomes difficult to detect. Each department is responsible for its own inaccuracies and dirty data can remain hidden for years. And the situation worsens when organisations try to search for unclean data manually and then try to make their database hygienic through manpower.

Data is forever changing and shifting, so it is advisable that we keep only recent and accurate information. Updated information bounces back as a key business asset. No one likes to get irrelevant information. Mails becoming spam can damage the reputation of the business.

This is a simple yet intelligent guide to keeping your database hygienic. Now it is time to take steps to maintain your brand's integrity and esteem.

Views expressed are strictly personal