Data is all around, and it is constantly growing. This is perhaps more the case for companies and businesses than any other entity! It is just one reason why the need to set up data cleaning, or cleansing, is becoming more and more critical. Have you ever considered data cleaning automation before?
Data quality is a chief concern for US businesses. It’s thought the US economy loses $3 trillion each year due to dirty data. That data may be confusing, hard to find, or simply out of date. Statistics also show that human error is to blame for many data hygiene problems!
So – how can data cleansing automation help to turn things around?
What is Automated Data Cleaning?
As the phrase suggests, an automated data clean occurs without human input.
For example, you may use an autonomous program to recognize inaccurate data. You may use it to find duplicate records or ensure data of specific type files away in a practical manner.
Data cleaning automation often requires running scripts. However, not everyone analyzing data cleanliness may know how to set up such scripts.
Therefore – is running scripts the best way to clean data autonomously? Maybe not.
How to Clean Data Autonomously – and Efficiently
Many business owners find that running scripts can be pretty complex. Besides, it is challenging to scale up automated cleaning through scripts alone.
Script building requires expert knowledge. This isn’t always something that a business operator will necessarily have. Scripts are also relatively inefficient. There is always going to be a requirement for someone to activate them!
Therefore, true automation should remove this need. Script automation can also confuse matters. It is not always seamless to see who has ownership of tasks this way!
Through these problems, cleaner, more user-friendly UI automation was born. UI automation effectively takes away the need to go deep into the code. This means everyone can start cleaning data!
By building automated cleaning into a simple UI, there is less risk of confusion. You’re also likely to avoid human errors making matters worse.
UI-based software, such as WinPure, can help to automate cleaning in a straightforward way. There is no need for programming experience! This means business owners will not need to hire specialists or data scientists to run these processes.
With data cleanliness being such a huge problem, it makes sense to simplify things. Crucially, it also means users can quickly scale cleansing up and down whenever they need to!
The Benefits of Automating Data Cleanses
Let’s consider some further benefits to automating data cleanup.
Boost Productivity and Efficiency
Automating data cleaning means there is less risk of data being irrelevant or duplicated. This means agents can avoid contacting the same customers multiple times!
It also means that agents can find information easier. Of course, this means that they can effectively complete more projects in a given timeframe.
Free Up Critical Time
Less time spent manually filling and cleaning data is always a boon. By automating the process, you free up availability for other tasks and processes.
The less time companies spend on menial tasks, the better. Data cleaning, while crucial, is repetitive. Repetitive manual work can lead to human error. It is simply not worth the risk!
Automating data cleans automatically provides business owners with the tools they need to operate confidently. By delegating this work to a program, they can rest easy without the fear of human error.
This, in time, will likely result in more confident business decisions. As automated cleansing can scale up and down, it can also change and evolve with you.
Many business owners have more confidence in machines than people! For data-intensive tasks such as these, relying on programs is likely the better option.
As we know, dirty data is expensive. Therefore, any cleaning solution is likely to save money. However, automation can take these savings one step further.
Automated data cleansing removes the need for specialist data scientists. Because of this, there is no need for additional expert hires. There is also no need to spend excessive money training staff. Automation requires little guidance!
It’s Always Updating
It’s not easy to know precisely when data is starting to ‘decay.’ While talented data scientists will likely know the signs, everyday operators might not.
Smart programs and UI automation can learn how to spot dirty data. They can continue to update and learn in the background.
Therefore, automated cleaning programs will know what to look for and how to remedy problems. There is no need for excessive training or education.
Automated Cleaning is Simple to Use
Providing one uses a UI-based system, autonomous data cleaning is effortless. It is easy enough to set tasks running in the background to ensure all records stay up to date.
How to Make Automatic Data Cleaning Work for You
WinPure offers a scalable, automated cleaning solution that runs in the background. Easy to configure and set up, it is a suite that adapts to your needs and data sources.
WinPure Clean & Match Enterprise offers an automation module you can toggle at any time. Run the setup wizard and create a bespoke cleaning plan to help tidy up your schedules.
What’s more, you may use Clean & Match Enterprise to automate schedules. Therefore, users will not have to intervene at all to run these cycles. You can even install our data cleansing schedules into your Windows shell. It’s built to work seamlessly with Microsoft’s OS!
Within only a few weeks of use, you will soon notice a difference in your operation. You may not know just how dirty your data is! You will not be alone – as many companies are still struggling.
If you would like to try WinPure Clean & Match for yourself, make sure to download our free trial. Make data cleaning automation your priority – and close down confusing siloes for good.
Download our WinPure Clean & Match free trial, and see for yourself how our award-winning software can help your company achieve overall operational efficiency by automating your data cleansing and data matching tasks.
Last Updated on 31st March 2021 by admin