Data Cleansing

What is Data Cleansing?

Data cleansing - which is sometimes also called data scrubbing - involves identifying and correcting (or removing) corrupt, inaccurate, incomplete, or irrelevant data within your dataset. The goal? To enhance the quality of the data, making it accurate and relevant for your current customer base. This serves a whole ton of purposes, such as:

• Data analysis: Clean data will mean you can grab more accurate and reliable results in analysis and data-driven reporting.
• Machine learning: Training models with data you know is top-notch leads to better predictions and performance.
• Pitch-perfect CX: Tip-top customer data ensures targeted marketing and personalized customer experiences always meet their mark. 
• Fraud prevention: Identifying and removing invalid or suspicious data helps combat fraudulent activities, which can be rife with data entry.

Learn more on this topic: What is data cleansing, and why is it so important?

What does data cleansing involve?

Data cleansing is clearly an important and wide-ranging business process, aiding with customer experience, delivery, data quality, and analytics, amongst others. But what does it actually involve? Here are the main components to know about:

• Error finding: The basics first. Data cleansing starts with finding inconsistencies, typos, missing values, outliers, and other issues in the data.
• Data validation: Then, it involves checking that data against predefined rules or external reference sources to ensure it's accurate and consistent - eg, that an address really does exist at a physical location.
• Correction and filling: This is the process of actually fixing those errors found. It usually involves inputing missing values based on valid data points, or removing completely erroneous records.
• Standardization: This means ensuring your data is consistently formatted, according to predefined rules or industry standards.
• Deduplication: Lastly, data cleansing often also involves eliminating duplicate records to avoid skewed results, inaccurate analytics, and wasted storage space. Learn more: What is data deduplication?
  
  

Why is Data Cleansing Important?

Data cleansing is key for all aspects of your business' day-to-day activities. Here are the core advantages we think are most important to keep in mind:

• Improves data quality: Making sure your data is accurate, complete, and reliable for further use, cleansing will skyrocket your overall data quality. 
• Nifty analysis and insights: Knowing you're working with cleansed data, you'll be able to trust your analytics more and make valuable data-driven decisions. 
• Enhance efficiency and productivity: Reduces manual efforts spent on data correction and manipulation, allowing your team to focus on what they're best at.
• Reduces costs: Minimizes errors and rework related to poor data quality, such as the painful cost of redelivery if your parcels don't reach your customer.
  
  

What are the types of data cleansing?

• Parsing: Parsing is a fancy way to describe the process of breaking down data into smaller components for easier analysis and manipulation. Learn more: Data Parsing (Glossary item)
• Pattern matching: As it sounds! Matching involves identifying and correcting data based on predefined patterns or rules, in order to ensure consistency.
• Fuzzy matching: Identifying potential duplicates or similar records even with minor variations. Learn more: What is fuzzy matching?
• Clustering: Clustering involves grouping similar data points together to identify outliers or anomalies - a good way to identify fraudulent or false inputs.
  
  

Overall, data cleansing is a crucial step in any data-driven process. By ensuring your data is clean and accurate, you can unlock its full potential and extract valuable insights for better decision-making and improved outcomes.

While data cleansing is an intricate process, spanning a lot of existing business functions and ample data analytics, the good news is that there's an easy solution - use Loqate's Data Cleanse! Our easy-to-install solution takes care of both data cleansing and maintenance, at the push of a button. Get started today by booking a demo with our friendly experts, or find out more on our Data Maintenance page.