With most industries relying on data today for their business growth, data has become one of the most critical assets in the 21st century. However, ensuring data accuracy and quality is one of the biggest challenges for organizations of any size today.
The fundamental problem with data quality is fairly straightforward. If your data is of low quality, then the decisions taken by your organization, based on that data, will be worthless. Thus, data cleansing or cleaning is critical to ensure an acceptable level of data integrity which will ultimately lead to high-quality data and better decision making.
Now, you might have come across several data cleansing companies or vendors who offer data cleansing services, but wouldn’t have actually availed the services. Well, you aren’t the only one; so don’t worry!
In this three-part guide, we will get all your doubts cleared by talking about data cleansing, different types of data issues and finally some of the best data cleansing practices that you can implement right now.
What is Data Cleansing or Cleaning?
In simple words, data cleansing or cleaning is the process of identifying and fixing any issues with your data set. The sole objective of data cleaning is to fix any data that is incorrect, inaccurate, incomplete, duplicated, or even irrelevant to the objective of the data set. This is typically accomplished by replacing, modifying, or even deleting any data that falls into one of these categories.
Though it does and can involve deleting information, it is focused more on correcting, updating and consolidating data. Good data drives good decisions and that’s what data cleansing services help you with; managing and streamlining your data to make your business more agile.
What are the different types of data issues?
Let’s have a look at some of the common ways your data may not be supporting your business needs:
Duplicate Data: Sometimes there can be more than 2 or more identical records. This may cause misrepresentation of inventory counts/duplication of marketing collateral or unnecessary billing activities.
Conflicting Data: This happens when there are same records with different attributes. For example, a company with different versions of addresses may cause delivery issues.
Incomplete Data: The data can have some missing attributes. For instance, payrolls of employees may not be processed due to their missing social security numbers in the database.
Invalid Data: This happens when data attributes are not conforming to standardization. For example, 8 digits phone number records rather than 10 digits.
Why is Data Cleaning Important?
Data quality is of central importance to enterprises that rely on data for maintaining their operations. Consider, for instance, businesses need to make sure that right invoices are mailed to the right customers on right email ids. Thus, to make the most of customer data and boost your brand value, you must focus on data quality.
Besides, below is the list of a few benefits that data cleansing brings along.
Boost Customer Acquisition
Organizations that keep their databases in shape can maintain lists of prospects with the help of accurate and updated data. This, in turn, increases the efficiency of their customer acquisition and reduces its cost.
Make Sense of Data Across Different Channels
Data cleaning clears the way for managing multichannel customer data seamlessly. This allows organizations to find opportunities for successful marketing campaigns and new ways of reaching their target audiences.
Improve Decision-Making Process
Without recourse to data cleaning services, you will end up making bad decisions and eventually suffer financial losses. Nothing helps to boost a decision-making process like clean, accurate data. Good and updated data supports analytics and business intelligence while providing organizations with resources for better decision-making and execution.
Increase Employee Productivity
When the databases are clean and well-managed, they ensure high productivity of employees who can benefit from the information in a wide range of areas such as customer acquisition or resource planning. Businesses that actively improve their data consistency and accuracy experience an improvement in their response rate and revenue.
Reduce Compliance Risk
Inaccurate and bad data can lead to your business jeopardizing your GDPR compliance efforts. This happens when you send emails to the customer(s) who have removed their consent for receiving marketing emails. This action will be a clear breach of data protection laws on consent. Leverage data cleaning services to avoid such violations and remove corrupt data that hampers your GDPR compliance. You can also protect identifiable information within your maintained database, which includes but not limited to trade secrets, marketing efforts, and business partner interactions.
Avoid Costs of Errors
Data cleansing is the single best solution for controlling and avoiding costs that arise when organizations are busy processing errors, correcting the incorrect data, or troubleshooting.
Outsource Data Cleansing Services for a Better Future
Cleaning your database is a painstaking task. It does not just take a good chunk of your time but resources too. Fortunately, several data cleansing companies help you in managing all facets of data cleansing and data quality management while ensuring error-free customer data within your database.
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