Data Cleansing_ What It Is, Why It Matters & How to Do It

1. Title: Data Cleansing: What It Is, Why It Matters & How to Do It Having multiple old email addresses, duplicate contacts, and misspelled names can severely hinder your team's outbounding marketing efforts. After all, your company's CRM tool or marketing software is only as strong as the data it's made of. Data of any kind collected over time will inevitably change. The best way to handle this change is to implement a solid data cleansing strategy to ensure your data is fresh and trustworthy. İf you want insights from your data that are more accurate and useful for your business, then make certain that people on your team can keep up with the rate of change in it. What is data cleaning?

2. database cleaning service is the process of modifying or removing inaccurate, duplicate, incomplete, incorrectly formatted, or corrupted data. By deleting data, we are creating datasets that are resilient and easy to use for people who might rely on those datasets to make important decisions about a particular topic, like learning about future trends and opportunities for growth. While deleting data from a dataset may seem counter-intuitive, the ultimate goal of data cleaning is to make your dataset as accurate as possible. This can be done by fixing spelling and syntax errors, identifying and deleting duplicates, correcting mistakes like mislabelled or empty fields, standardizing how data is entered or combined from multiple sources, etc. Why is data cleaning important? Clean data is like a squeaky-clean house; it's good for business. Consider that a dataset in need of cleaning might not contain accurate information, ultimately leading to inaccurate conclusions and decisions. This costs time and money, but it also impacts employee morale. When employees cannot rely on the data for fear of inaccuracies, that can affect their conduct, resulting in lower quality services or products—and harmful interactions with customers. Now that we're more familiar with data scrubbing, let's look at some steps and techniques that help us get started when cleaning data. 1. Remove duplicate contacts Duplicates are usually caused by inconsistent data entry and multiple channels that capture contact information. One of the easiest ways to remove duplicate contacts on Gmail is to create a filter with a query. If you've never done a de-duplication, you might have to manually scan your list and make the needed changes or edits. Thankfully if you implement company-wide data entry standards and commit to quality data, you will only have to do this once. 2. Correct structural errors Structural errors refer to typos, unusual naming conventions, inconsistent abbreviation, capitalization, or punctuation, and other errors that usually result from manual data entry and lack of standardization. For example, "Not

3. Applicable" and "N/A" might show up as separate categories on your screen but should have been analyzed as the same. 3. Address missing data Missing data is unfortunate. Some ways you can address this issue include: Remove the misleading entries. Enter the missing values based on the database. Put the flag on missing data. These solutions are not perfect, but they might minimize the negative impact on your data. 4. Keep your data fresh It's a good idea to keep your email lists updated by using a few tactics. Do this by using email-scrubbing tools, which scan all incoming emails and update contact information as it comes in. If an individual gets a job with a different company, address data is instantly changed to reflect their new position. It's also smart to delete all email addresses that have bounced or opted out of correspondences — this kind of information is probably found in most current email marketing tools. This is good practice for keeping your data fresh, but it also helps you avoid spam folders in mailboxes. 5. Standardize data entry All of the steps above will be useless if you don't implement company-wide data entry standards. To avoid having employees entering and inconsistently storing data, create rules dictating whether all values should be lowercase or uppercase, the unit of measurement that numerical data is entered in (feet or inches, etc.), and what fields are needed to be completed when creating a contact record. It would also be useful to screen for duplicate contacts before starting on new ones, so make sure your employees know how to check for duplicates before creating a new contact. Make sure everyone knows which applications to use when entering data as well. For more services, you can visit our website. We have the best outbounding marketing team. We also provide a database cleaning service.