
Data Management
Let's Explore Data Cleansing Tools
By TechDogs Editorial Team

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Overview
You must be wondering, why are we talking about coconuts? Don't think too hard; these are the words of Sheldon Cooper from the Big Bang Theory. He is searching for better ways of cleaning up a mess (be it his or someone else's!). Sheldon doesn't want to hear any excuses! Currently, he is searching for ways to clean his data. computer data.
Bazinga! Data Cleansing Tools are here to rescue your inner Sheldon Cooper from the dirty data currently sitting on your computer systems and databases. Data Cleansing Tools are designed to ensure that business data is accurate, organized and up to date.
If your inner Sheldon wants to know everything about Data Cleansing Tools, read on!
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What comes to your mind when you think of Sheldon? An overly intellectual person with a lack of understanding of sarcasm, irony or humor. He also has a strict adherence to routine and most importantly, he’s a neatnik. How on earth can you say, 'dirty sock' and 'relax' in the same sentence? His habit of cleaning and keeping things in order has always urged him to find ways to cleanse his data to avoid errors.
Data Cleansing Tools are the answer to the problems the Sheldon within you faces. Data cleansing is an integral part of data management. It deals with the process of identifying and correcting errors in business data. This may be done to improve information quality, secure sensitive information, or reduce redundancies. These tools are designed to make data extraction easier. They can be customized to suit different needs, depending on whether you're an individual looking for a simple tool or an enterprise-level organization with thousands of users and transactions to manage. #CleaningObsessed
To know all about Data Cleansing Tools, read on to learn all about this software, its working, benefits, importance and future trends!
As Sheldon says, "In difficult moments like this, you should turn to a force greater than yourself."
What are Data Cleansing Tools?

Imagine if you were to find out that your business data was defective and was incorrect. Oh, what would happen? Well, your business strategies wouldn't fit in, your profits would plummet, your reputation might be irreversibly damaged and it would take a very long time for your company to recover! This is precisely why you need to keep your data clean and perfect. Sheldon understood this right from his childhood - the importance of keeping things perfect and correct. However, before hopping directly to the tools, you must know what data cleansing is.
In simpler terms, data cleaning is the process of identifying and resolving corrupt, inaccurate, or irrelevant data. Also, this process will make your data as accurate as possible to make it easier for you to analyze and use it for driving business outcomes. FYI, it's also known as data cleaning or data scrubbing as well and is one of the most crucial stages of data processing that improves your data's consistency, reliability and value. #SayNoToGarbageInGarbageOut
With gigabytes of data being created every second, data cleansing can become time-consuming for any organization. Thankfully, there are tools that can help you with this daunting task!
Data Cleansing Tools do this faster than usual and help you maintain the integrity of your data, so you don't have to worry about it anymore! From removing duplicate contact records (from marketing and mailing lists, databases and spreadsheets by cleaning, correcting and standardizing them) to validating data (from performance reviews, employee feedback and other related HR documents), these tools help you to ensure that your company can trust the existing data they rely on. When you have confidence in your data, you can make decisions accurately and precisely.
After knowing about Data Cleansing Tools, let's learn these tools from the beginning in the following section.
Evolution Of Data Cleansing Tools
As quoted by Howard Raiffa, "A lot depends on the starting point." So, let's start from the starting point of these tools to know them better.
The process of data cleansing has been in use for many years. One of the first methods was developed in the 1930s when computers were used to help companies to maintain their customer data for mailing lists. This method, called 'delete printing,' was inefficient because it required a lot of manual work to clean up the printed delete list.
The next major development came in the 1970s when database tools were developed to help companies update and maintain their customer lists more quickly and efficiently. These database systems had new ways of filtering out erroneous data and preventing errors from entering data sets. However, these early database systems had their limitations, such as requiring structured fields and leaving all the decisions about missing values up to the user.
The early 2000s saw another leap forward with automated processing that got rid of inconsistencies within datasets by using statistical analytics and Machine Learning algorithms that could detect patterns of bad data.
As technology has improved, so have the tools to help us cleanse our data sets. Today we have an endless number of tools and software available at our disposal to ensure our data sets are accurate and up to date.
Now that you know the evolution of Data Cleansing Tools let's know how these tools actually work!
How Do Data Cleansing Tools work?
Sheldon (the physicist) believes in knowing the root cause to solve every issue. Similarly, to solve your data woes, you need to ensure your data is clean and accurate from the root. The techniques used for data cleaning can vary depending on the type of data warehouse your company uses. However, here are some of the steps that you can take to make sure your data is clean and usable:
Step 1: Identify The Critical Data Fields And Collect The Data
Companies have collected a lot of data (consumers, products, metadata, financial transactions, etc.). However, not all types of data are equally valuable for a project or process. The very first step in cleaning up this information is to identify which type of data you need and what fields would be most useful to you.
Step 2: Discard Duplicate Values
Once you collect the data, it's time to figure out what values are inaccurate. Sometimes there are duplicate records that need to be removed. #RemoveTheUnwanted
Step 3: Resolve Empty Values
Data Cleansing Tools can then search each field for missing values and fill in those, allowing data sets to be complete without gaps.
Step 4: Standardize The Cleansing Process
Data cleansing is a process that needs to be standardized. To do so, it's important to make sure you determine which data source will be used the most when it will need doing and by who (in the required order) and how often you'll need to scrub your data.
Step 5: Review, Adapt and Repeat
Review the data cleansing process frequently to find out what has been working well and where there is room for improvement. The review should also include members of different teams that are affected by this process such as customer service, marketing or finance - because you want a well-rounded account for your company's data!
Now that you know the working of these tools, let's know their features in the next section. #TheMostExcitingPart
Features Of Data Cleansing Tools
"All data cleansing tools are not equal" - #TechDogs (Sheldon would surely agree with us!)
We have integrated a list of features that a successful Data Cleansing Tool should possess to make your task a bit easier:
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Profiling And Cleansing Capabilities
Tools should automate metadata recognition and categorization to provide clear visibility into the source of data to spot any anomalies.
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Quality Checks
To maintain data integrity, comprehensive data validation criteria are performed during the data cleaning process. Data quality checks are policies or rules that you may add to your information flow to track and report any errors that occur while processing data. #ErrorFreeData
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Mapping
To correctly map data from source to transformation and then to the destination to ensure that your data is cleansed accurately. These tools can support such functionality with a code-free, drag-and-drop graphical user interface.
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Compatibility
To handle standard data formats and to export cleansed data to various destinations, including SQL Server, Oracle PostgreSQL and Business Intelligence applications like Tableau or PowerBI. This enables your company to gain faster access to analyze high-quality data to make timely decisions.
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Workflow Automation
To automate the entire data cleansing task from data profiling, converting and loading it to its designated destination. #AutomationRules
Now you know the essential features of a Data Cleansing Tool. Let's move ahead to understand the importance of these tools!
Importance Of Data Cleansing Tools

Data is being generated at an astonishing rate. Every day, companies generate an average of 2.5 quintillion bytes of data! This type of data can quickly become unusable if not taken care of in the right way; Sheldon alone generated a few gigabytes of data every day while researching at his university. Who would ever guess that?
Using tools for data cleaning will make for more efficient business practices and quicker decision-making. Data Cleansing Tools ensure that data is accurate and up to date. These tools play an important role in maintaining an efficient and effective system, from removing outdated or inaccurate information that can spoil your marketing efforts to unblocking the data flow to ensure your databases are always up to date. Along with this, it also helps in monitoring errors and providing better reporting to see where the error is originating, making it easier to identify and fix incorrect or corrupt data for future applications.
Data cleansing is one of the best ways to make sure that you can trust the data that your business relies on. Having clean data will ultimately increase overall productivity and allow for the highest quality information in your decision-making.
It's time for a small-time leap to the future to see what these tools will do next!
What Does The Future Hold For Data Cleansing Tools?
Data is what drives decision-making in many companies. Sheldon too feels the same! Any errors in data will have a negative economic impact on businesses. These tools will be integrated with advanced technologies such as Robotic Process Automation (RPA), Machine Learning (ML) and Artificial Intelligence in the years to come and will become exceedingly smart like Sheldon who graduated at the age of 14. RPA tools will keep track of any transformations done by these new toolsets while they maintain process optimization, regulatory compliance and transparency for your company's complicated data environment.
Besides this, automation in data cleansing will come in the form of User Interface (UI) automation as well as schema standardization in the years to come. With UI automation, business users will use the same Graphical User Interface (GUI) where daily operations take place to build automation flows. This way, they can enforce current business rules when building automated processes for data cleansing. While schema standardization will eliminate the time required to reformat and match the raw data so that the business time will be effectively used on value-generating activities. Now that's called some real business!
It’s A Wrap
Understanding data quality and the tools you'll need to collect, manage and convert data sets is crucial for making smart business decisions. This vital tool will help your company build a better and more accurate data culture. Now, your inner Sheldon knows the solution you need to cleanse your data by understanding everything about these tools. Knowing is a part of the fun!
Frequently Asked Questions
What are Data Cleansing Tools?
Data Cleansing Tools are essential software solutions designed to identify and correct errors within business data. They play a crucial role in maintaining data accuracy, integrity, and reliability by addressing issues such as duplicates, inaccuracies, and inconsistencies. These tools are instrumental in ensuring that organizations can trust their data for decision-making processes, marketing efforts, and operational efficiency.
How Do Data Cleansing Tools Work?
Data Cleansing Tools employ various techniques to clean and enhance data quality. These processes typically involve steps such as identifying critical data fields, removing duplicate values, resolving empty or missing values, standardizing data cleansing procedures, and conducting regular reviews and adaptations. By automating these tasks, these tools streamline the data cleaning process, allowing organizations to maintain clean and usable datasets efficiently.
What is the Importance of Data Cleansing Tools?
The importance of Data Cleansing Tools lies in their ability to ensure data accuracy, reliability, and usability. In today's data-driven business environment, maintaining clean and accurate data is essential for making informed decisions, driving business outcomes, and maintaining competitive advantages. These tools help organizations avoid costly errors, improve efficiency, enhance decision-making, and unlock the full potential of their data assets, ultimately leading to improved productivity and business success.
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