Best Practices To Follow Before You Implement Data Cleaning


Most of the companies is either working on ERP or CRM that contain large databases. These databases hold crucial customer information and hence, there are high chances that the data can get corrupted. It can contain inaccurate, obsolete, and redundant data that’s of no use thus, causing a lot of problems for your business. Therefore, data cleaning becomes important for your enterprise.

But, before you implement data cleaning and make use the best data cleansing tools for the process it’s critical to take a look at the broader view else you may end up stuck with outdated and incorrect customer data. You must first identify your goals and expectations and then plan to put into action successfully. But, how do we achieve it? You need to keep a few things in mind as you proceed for data cleaning.

Best Practices To Follow Before You Implement Data Cleaning

Inspect your Data

Before you get into the advanced process of data cleansing, restricting imperfect data, and improving data, you must know in what condition your data is. Basically, you must analyse how dirty is the database and the right way to know would be to inspect and measure data quality.

In order to inspect the database, you must know the answers to a few questions for instance; to what level there are duplicated entries, where these duplicate records are originating from, and if the data quality matches the standards of the customers from the Here, it is important to set up a data quality dashboard that will clearly indicate the number of duplicate leads you have, where are the leads originating from, the time when these were created, and so on.

Focus on Data Quality

Quality of the data being used is extremely crucial for a business hence, you should know where do the errors in the data quality originate from and find any inaccurate data. Finding answers to this helps your team analyse the underlying problem and create a project plan accordingly. Speak to individual departments and make them understand how important is a detailed data quality plan as it can help save everyone a lot of money.

Normalize Contact Details at the First Step

Bad data can be disastrous for your business and most of it comes from human mistakes. A well-managed organization should have standards or policies in place that should emphasize how the data made way to the CRM, otherwise you will different versions of the same data and remain attached to the CRM. so, how do you deal with this situation? The answer is normalization (standardization) of the data which creates legal, standardized, and a steady condition for the data to make way to the CRM.

Checking the crucial data at the very first step is important to ensure that all records are normalized as these are updated on the database. This also makes it easier for you to keep a check on the duplicates.

Check if the Data is Correct

Checking if the data is correct in real-time or validating the data accuracy will make sure that your CRM works on data that is clean, accurate and functional.

Therefore, it’s important to check the data validity on a regular basis using fixed verification rules, controls, and procedures established right from the very beginning. Research and find out the best data cleansing tools that can remove impurities from list imports or offer some software that helps verify address. Data Ladder is one such company that efficiently cleans and improves data quality using advanced semantic technology which was previously available only in expensive customized software products. It offers some pretty good tools that works in unison with high-quality data to combine different data sets, smoothly.

Find Out Any Duplicate Entries

Removal of duplicate records is not just important when you start, but it’s extremely crucial for your business and hence should be done on a regular basis. All you need to do is to keeping your current CRM clean and prevent any duplicate information even before it makes way to the system in future. So, find some good data cleansing software for this purpose that will not just find out the duplicates efficiently, but also save a lot of time by saving that manual work.

Match Data

Once you are done with correcting, standardizing and parsing the data, it’s time you must shift it to an efficient data quality matching tool that can easily find out matching data within the CRM and across all data resources. The DataMatch2017 by Data Ladder is a versatile software that helps you with cleansing, improving data quality and de-duplication with finesse.

Develop a Protection Strategy

Protecting your data is equally important as the data continuously corrodes. Therefore, you need to create a protection strategy for your CRM. The phone numbers, emails, and titles keep changing and so there is a high probability that there will be duplicate information and inconsistent data.

Therefore, you should protect your data by continuing duplicate prevention, continuing normalization, and with ongoing practice of filling in the missing data and correcting the data.

Employ External Data Sources

Appending the data is another important step that should be followed once you are done with the standardising, correcting, and cleaning the data of duplicate entries. here you can use a third-party source to append the data. Choose from the best third-party software that are capable of capturing the information straight away from the first-party websites. You can then clean the data and organize the data to offer more complete details relevant to business analytics and intelligence.

Successful data cleansing will make sure that you have detected and removed any major errors and any deviations in single data resources and also when bringing multiple resources together, and when you have made use of the best data cleansing tools to lower manual validation. Clean data is a ticket to your company’s growth in a faster and consistent manner so, follow the best practices before you implement data cleansing.

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