13 Reasons to Opt for Data Cleansing Services
Data cleansing services are required to make sure that your database has clean, crisp data for effective business. You need good quality data for analyzing the data file and the reason for this is not hard to determine.
Data collection and data entry is done extensively through a manual process. Data researchers spend a huge amount of time going through statistics or talking to people to build their database. This method increases the chances of spelling mistakes or incorrect entry in a particular field. The ratio of errors doubles up when there are multiple people collecting and entering data in the database. More often than not, employees who undertake these jobs lack proper training.
These are one of the reasons you need clean data and failing to do so can risk your business from arriving at wrong conclusions. And, although cleaning data by opting for data cleansing services isn’t difficult, you need to have patience as you may come across some files having missing data or variables that you are unfamiliar with, such as the art of data cleansing.
Most data scientists notice the need for data cleansing first hand. Here are 13 reasons why you should opt out for data cleansing services.
1. Remove spelling mistakes
Like we pointed it out earlier, spelling mistakes can occur if there are multiple people updating the database. This makes your data lake murky and becomes useless. Data cleansing is required to tackle this problem. To have good quality data you need to do spellcheck and eradicate the errors. You need to make sure that you mention the right spelling of towns, cities or villages. There may be instances that the name of a village or a town is spelled in different ways and this is where you need to identify different spellings and make sure that only one spelling is used consistently.
2. Remove multiple representations
There may be instances where a single word may be abbreviated in multiple ways. For example, India may be abbreviated as ‘IND’ or ‘IN’. You need to maintain a single abbreviation for India if you want clean data. You will have to replace all the other abbreviations and maintain a single style throughout.
Sometimes it may also happen that the same abbreviation is used in an upper case as well as lower case. In this case, also, your data will read the same thing as two different variables. Therefore, it becomes important here to follow a single structure in the entire data set and use effective data cleansing techniques to get rid of dirty data.
3. Use one style/format
Following a single metric system in a database is important. If you find that weight, in your database, has been defined as pounds as well as kilograms, you will have to clean your data. Data cleansing services are to be used to carrying out a single format throughout especially in complex areas where a date is mentioned in different formats. In cases where you find the format of the date to be date-month-year as well as month-date-year, you must clean data and put a single format in place.
4. Eliminate duplication
Duplication usually happens when a number of surveyors are used for data collection and data entry. More often than not, they do not realize that the data they are entering is already present in the database. Duplicate entries like these corrupt the results and thus need to be pulled out from the dataset.
5. Recognize missing information
If the key values of a database are missing, data analysis is sure to take a backseat. This can usually happen in the case of oversight or by mistake. You need to use data cleansing services and identify the missing values, go back to the data pulling source and fill in the missing information.
6. Correct range values
Data cleansing services provide you with clean data which means that the researchers have checked and removed typo errors while entering the range values. For example, while analyzing the data of a school you might find that the column created for students with 80-90 marks includes a student’s marks to be 800 even when the student has actually scored 80 marks and the extra 0 is a typo error. If you do not correct such mistakes your analysis will go haywire.
7. Remove redundancy
While analyzing the data you may come across a record which is not relevant to your analysis. With data cleansing services this data can be deleted even before you start your analysis. However, it is important for you to focus on the key variables only and not on the entire data file and churn the benefits of data cleansing.
8. Save Money
Purchasing marketing automation services are costly and so you wouldn’t want to waste your money on customers who are not interested in your product. Send an email to a person who never opens up your mail means wasting your money. Data cleansing helps you eradicate irrelevant data which in return saves your money.
9. Save Time
Sending emails to your contacts that are no longer valid or available proves in wasting the time of your staff. By having a clean data you can be sure that the time and productivity of your staff does not go for a toss and only the customers that may add value to your business are contacted.
10. Improve customer engagement
It has time and again been highly recommended that you clean your database if you want to increase your clicks, open rate and conversions. By putting the data cleansing services in place your marketing will become more efficient and the numbers will be more accurate.
11. Improve marketing tactics
When you can identify your contacts and when you understand what they want, your work will become easier and the marketing strategies will be more effective. With clean data, you can tailor your emails accordingly and convert customers to leads.
12. Save your reputation
Don’t let your emails land directly in the spam folder. This happens when you have dirty data and you send emails to people who are not interested in your business, they will mark your emails as spam. This harms your reputation as a business and no one wants to deal with an over-eager organization.
13. Avoid natural decay
It is an unfortunate truth that the data which you have collected today has an expiry date. Having a clean database makes optimum use of the data that you have collected and you can reach the right person at right time.
Data cleansing services aid businesses to reach out to potential customers at the right time and generate a lead. It is, therefore, very important that you put this service into practice and make the maximum out of the data that you have.