Upload your CSV or Json files and choose from a range of text cleaning and normalization tasks, including precise phone number and company name normalization. No registration required.
So why use a
The processes of text cleaning and normalization play a pivotal role in enhancing data matching capabilities. Text cleaning involves refining raw data by standardizing formats. Normalization ensures that data adheres to consistent structures, facilitating accurate and efficient comparisons.
When it comes to data matching, these practices become essential. For example, in the context of company name and phone number normalization, standardizing formats allows for more precise matching between datasets. This improves the accuracy of identifying and linking related information across various sources.
The synergy between text cleaning and normalization contributes significantly to the effectiveness of data matching processes, ultimately leading to more reliable and insightful analyses.
When you need to do fuzzy matching on high-volume data in real-time, you need a built-for-purpose technology: enter Tilores.
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