What is data cleaning?

Data cleaning, also known as data scrubbing, is the process of ensuring the data set is correct and accurate. During this process, the records are checked in terms of accuracy and consistency and are either repaired or deleted as needed. This can happen within a single set of records or between multiple sets of data that need to be merge or cooperate.

Simple process

In its easiest form of data cleaning, it includes a person or persons reading a set of records and verifies their accuracy. Mandreate and spelling errors are corrected, data on incorrect designation are properly marked and filed and incomplete or missing items are completed. These operations often clean up outdated or invaluable records to prevent space to take up and cause inefficient operations.

Complex process

In more complex operations, data can be cleaned with computer programs. These programs can check data with different rules and procedures of the Decided on the user. Could be nAstaven to delete all records that have not been updated in the previous five years, fix all the wrong words and delete any duplicate copies. A more complicated program could be able to fill in the missing city based on the correct postal code or change the prices of all items in the database to another type of currency.

advantages

Data cleaning is very important for the effectiveness of any data dependent on data. For example, if some of the clients do not have exact phone numbers in the database, employees cannot contact them easily. If the client's e -mail addresses were not correctly formatted, as another example, an automated e -mail system could not send the latest coupons and special stores. The task of cleaning data is to ensure that the data within the system is correct for the system to use the data. Inaccurate or incomplete records are not much of anyone.

whenever you need SPFulfill two data systems, data cleaning is even more important. If the company has two branches that work with many of the same customers, the data in each branch must not only be complete and accurate, both branches must also have the corresponding data. When the customer updates their phone number with one branch, the data in the second branch must be updated with the same information to ensure the highest efficiency. Data cleaning works not only to ensure that the data is accurate, but also that they are consistent between different records.

Whenever a lot of data is stored, errors must be swayed into the system. The aim of data cleaning is to minimize these errors and make data as useful and as important as possible. Without this process, errors and errors can be regularly made, leading to less effective work and more complications.