As businesses generate and accumulate large amounts of data, it becomes a herculean task to remove unwanted or inaccurate data. While modifying such data sets requires effort, identifying and removing them are not easy either. Data cleaning identifies incorrect data and modifies it according to requirements. Data that is cleaned will then need to be transformed into a standard format so that it can be used easily in the future. This process is known as data standardization.Data cleaning and standardization help businesses to get rid of clutter in their databases, improve system performance, generate better insights, and have a standardized format of data that can be recognized, shared and used across departments.In this article, let us take a look at what data cleaning and standardization is, in detail, and learn how these processes help businesses.What does data cleaning entail and why are these steps necessary?1. Data cleaning recognizes errorsThe first step towards cleaning data is to identify errors and inconsistencies. For example, this involves identifying mistakes in email addresses, phone numbers, ensuring that names are all written correctly, etc. Identifying and rectifying errors in datasets is performed by comparing data with various reliable sources. Error identification is an important aspect of data audit.For example, making sure that the email address field does not have "2" symbol twice, or making sure that there is no space between characters of an email address. Cross-checking mobile phone numbers are typed in correct format, and are of the specified limit of characters.The Australian National University has a detailed page about data cleaning and identifying errors.2. Remove duplicate dataMany businesses suffer from duplicate data entries, which cause a lot of confusion and operational errors. Duplication of data can be minimized when software programs are integrated but they cannot be eliminated completely. Data cleaning ensures that duplicate entries of data are removed, so that your database is free from multiple duplicate entries.If you use an ERP and a CRM, both the tools may collect customer information, and create multiple copies of customer data. This can prove to be confusing, especially when contact details or updated or changed. Data cleaning ensures that only the latest and most recent changes to data are retained, while deleting previous entries.According to this article, duplicate data results in inefficient marketing, missed sales opportunities, underwhelming customer satisfaction scores, reduced productivity, and other issues.3. Validate scrubbed and corrected dataOnce incorrect data is identified and corrected, and duplicate entries are deleted, it is important to validate remaining data for accuracy as a last step. This is done with the help of data cleaning tools that analyze data in bulk. Validation ensures that your final copy of data is error-free, most-recent, and accurate.Once data is validated, final versions are communicated to various departments that may use the data. This ensures that all business processes are efficient and that efforts are not wasted.More than 60% of companies surveyed had a data health score of "unreliable", while 28 out of 100 emails were not delivered to the addresses they were sent.What is standardization of data and how is it done?Once data is cleaned and made ready for use, it needs to be standardized into a common format that can be used by various entities. Data standardization ensures that all your information is stored on platforms that are recognizable by various users. Data standardization ensures advanced analytics, collaboration with external and internal agencies, and other processes take place smoothly. Once standardized, data is stored in a common data model (CDM) format. This format varies depending on the industry you are in.To standardize data, we need to first clean it and understand the data entry points. Next, we need to choose data standards so that unruly data sets can be written into a commonly recognizable format, also known as CDM, as discussed before. Finally, data needs to be mapped into matrices so that it is indexed for future use.Some of the most important benefits of data cleaning and standardization can be summarized below:
What do you need to do specifically to clean your data and standardize it?Firstly, you need to recognize the fact that all data is rife with inaccuracies and errors. Once you recognize this, you can either choose to manually correct, clean, and standardize data, or use one of the many automated tools. Automated tools come with many disadvantages. As they are software programs, they often run through the data in bulk and will not be as accurate as a specialized team of professionals who use both manual and automated tools to clean and standardize data. Thus, hiring an agency that specializes in data cleaning and standardization is a better idea. This is because:
If you would like to learn more about data cleaning or standardization, and how engaging in them will help your business, do not hesitate to contact us. We specialize in cleaning and standardizing all kinds of data, while you can focus on your core business activities.