Data standardization is the process of transforming data from disparate sources and systems into a consistent format. Standardizing data is a critical step in a data quality process because it makes it easier to identify errors, outliers and other issues within your data sets. It also makes your data easier to analyze and ensures that it is reliable.
What is standardized data?
No matter where your organization is collecting data, it is likely that it’s coming into your system in an endless variety of formats. Inconsistent capitalization, punctuation, obscure acronyms, values in the wrong fields or non-alphanumeric characters in places that they shouldn’t be, are just a few examples of challenges organizations can face when trying to leverage their data as a strategic asset. Standardizing data can help eliminate these challenges by organizing and formatting data in a clear, consistent manner.
For example, a data standardization solution can format all alphabetical characters in ALL CAPS, standardize Str., Street and St. to ST or remove extraneous characters from phone numbers like parentheses and hyphens.
A data standardization process plays a key role in ensuring that your organization has good data quality practices. It defines rules for how values should appear in your database and helps you quickly identify rule violations, thus establishing a consistent level of quality and consistency across your organization.
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