Does your business use data to find insights that will help grow your business? If you do, data cleansing is a vital part of making that happen. Data cleansing is also known as data cleaning or scrubbing. It refers to the act of removing duplicate, incorrect, or otherwise corrupted data.
If you find your data has duplicate or incorrect information, whatever analysis you get from that data will be incorrect. By cleansing your data, your business is more likely to have insights that better reflect reality. One way of cleansing your data is by outsourcing the job to a business that has experience in the field.
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ToggleWhat Is Data Cleansing Outsourcing?
Data cleansing outsourcing begins when a business sees that their data isn’t producing the insights they thought it would. The first step is finding a data cleansing service that works for you. After that, the cleansing service will collect the data. The next step entails running that data through cleansing software.
Data cleansing software works by first identifying duplicate or incorrect data in data sets. After identifying the corrupt or incorrect data, the software ‘cleanses’ the data. Data cleansing means deleting, appending, or modifying the data you no longer need.
Data cleansing outsourcing services duplicate your entire data set. By duplicating it, you’ll have a back-up to protect you from any errors that could occur during the cleansing process. That way, if you think the software deleted vital data, you’ll still have the original set.
After the software has cleansed your data, the data cleansing outsourcing service sends back your data. The data should now be free of any duplicate or incorrect data.
When to Use Data Cleansing Outsourcing?
Your business should use data cleansing outsourcing when you notice issues in your business’s internal data practices. For example, if your business is analyzing hundreds of data sets, it may be hard to dig through all of it to weed out the duplicate or incorrect data.
Another example of when you should use a data cleansing outsourcing service is when you notice your data insights aren’t producing positive results for your business. If your data says the busiest day of the week is Monday, but all of your workers complain about Friday being the busiest, there may be duplicate or corrupt data skewing the results.
When your business finds itself facing problems like these, data cleansing outsourcing is the best way to eliminate them. Data cleansing outsourcing ensures that your data analysis will lead to insights that can help grow your business.
Pros of Data Cleansing Outsourcing
Data cleansing outsourcing has a ton of positive qualities! From reducing the amount of time spent on data entry and scaling to large industries easily, data cleansing can help any size business. People cite three common reasons why they needed data cleansing.
Data cleansing’s main job is to create the most accurate data sets possible. You and your team can only find so many mistakes in a data set before getting tired. Outsourcing achieves the most accurate data by using specially designed software. This software finds all the mistakes in your data without spending days upon days doing so.
Data cleansing outsourcing increases efficiency by introducing automation into data collection and cleaning. Automated cleansing software cleans corrupt or incorrect data in seconds. If you didn’t use the software, a person would have to sift through the data sets manually.
Data cleansing outsourcing can give your business a competitive edge by utilizing automation. By using automation, you help your company stay agile. Data cleansing also helps you stay competitive by making sure you only get correct insights that lead to increased business.
Cons of Data Cleansing Outsourcing
Data cleansing outsourcing only has a couple of downsides, but they don’t affect all data cleansing outsourcing services. The first issue that sometimes arises is communication.
Effective communication between you and the data cleansing outsourcing service is essential. If there is any sort of miscommunication, the data cleansing process could be in jeopardy.
If miscommunication becomes a problem, you run the risk of getting the wrong finished product. Let’s say you need a specific problem solved, like extracting a certain data set. If the data cleansing outsourcing service doesn’t have the software to handle such a request, they won’t be able to complete your order. Communication is essential to avoid these issues.
The other problem that can arise with data cleansing outsourcing has to do with security. If your business has data that includes customer or employee information, you need to make sure it stays secure.
Always make sure your data cleansing service provides adequate security for all the files you send them. Making sure they’re a secure organization will help you and your business gain data insights without having to worry about data leaks.
Pricing Models
The price of data cleansing outsourcing can vary depending on a few factors. The primary factors that increase cost are:
- The number of data sets
- The number of errors in the data sets
- What sort of files need extraction
- The number of different files needing combining
- New code needed to help extract or combine data
- Manual work after all automated efforts have failed
The general pricing model includes a fixed rate for the service, plus an hourly rate for any manual work we may need to do on your data sets.
How to Choose a Service Provider
Choosing a data cleansing service depends a lot on what your specific needs are. A quality data cleansing outsourcing service has standardized practices. A solid data cleansing service will keep you up to date on your data and the cleansing process, and the price structure. Relaying this information is vital in keeping both the customer and the service happy.
You should factor in a preferred return on investment, too. Only consider using a data cleansing outsourcing service if the return on investment meets your standards.
As an example, let’s say the mistakes in your data cost you about $10 annually in reduced efficiency. If cleansing your data will cost you $1,000, you should avoid cleaning your data. The return on investment isn’t worth the cost.