Is Data Cleansing And Data Scrubbing Same?
Data cleansing and data scrubbing are often used interchangeably which makes one wonder if both methods do the same work. This brings us to a question which is usually asked, ‘is data cleansing and data scrubbing same?’ The answer is, yes! Data cleansing and data scrubbing mean improving the quality of data by removing errors and inconsistencies from the database.
Data scrubbing or data cleansing is a process that involves altering data in the storage resource given for ensuring that it is correct and accurate. There are different ways to pursue data scrubbing in various data storage architectures and software. Most of these architectures depend on the careful review of the database and protocols that are associated with any particular data storage technology.
You can call the data cleansing process as data cleaning or data scrubbing since they all mean the same thing.
If you have the same doubt in your mind, ‘is data cleansing and data scrubbing same?’, you can instead know what it is also confused as. Data purging where useless or outdated data is deleted from the data set is sometimes compared to data cleansing. However, even though data cleansing deletes old, duplicate or incomplete data, it is different from data purging since data purging mainly focuses on clearing the spaces for recording new data whereas, data cleansing or data scrubbing deletes data with errors and inconsistencies for maximizing the accuracy of data in the database. A data scrubbing or cleansing method uses parsing or other methods to get rid of typographical or syntax errors or fragment of records. If you analyze the data carefully you can notice how merging multiple data sets can lead to duplication of data. In cases like these, you can use data cleansing to fix the glitches.
To put it in a simpler word, data cleansing can be defined as transforming raw data into polished, usable data. This is similar to extraction oil from natural gas and deposits or diamond from the coal mine and so on. The simple process of extracting separates the material required and thereafter it can be refined or polished. Then further ahead of the line these materials can be used in different applications with more downstream processes.
In today’s age of data cleansing or scrubbing, the information is extracted from the data lakes similar to the extraction of diamonds or oil. This extracted information can be used and refined for different applications.
This process can be represented by data cleansing where data scrubbing, data cleaning, and data purification are just an alternative name for the term. The technologies used for data cleansing or data scrubbing should have the capacity to handle a large amount of data that keeps on growing with every passing minute. These data records come in different structures and formats and are known as big data. Big data consists of bad data which requires to be scrubbed or cleaned for achieving better data analysis and save a lot of time and money.
When you look at the definitions of both data cleansing and data scrubbing, you may find some words which aren’t similar but in the end, both methods do the same thing. If you don’t want to use data cleansing and go ahead with data scrubbing, it will still do the same thing of scrubbing the data and then throw in clean, good quality data at you. The process is similar, the data cleansing techniques and steps are similar but just because people feel that scrubbing involves cleaning data aggressively they face such a confusion.
Call it data scrubbing, data cleaning or data cleansing, it will still involve all the data cleansing steps to arrive at a polished and usable data. From removing errors to filling missing information, you are going to get a good quality dataset which will eventually save the time and money of your business.
‘Is data cleansing and data scrubbing same?’ yes, this question, no matter what their definition is, will remain yes because the process and the results of both the methods are similar and you can hardly differentiate one with the two. To put matters to rest, if you want someone to scrub your data instead of cleaning it, you are still going to get the same data cleansing services.