Data Cleansing and Standardization

Data cleansing aims at transforming dirty data into clean data in accordance with your business data objectives.

Reltio Connected Cloud deals with a large amount of data that accumulates on a daily basis. The data is not considered useful if you cannot make good use of it. A common approach to deal with large volumes of data is to regularly perform data cleansing and data standardization.

Transforming dirty data to clean data has several aspects.

  • Data Standardization - Have your data follow a certain format and rules for consistency.
  • Data Enrichment - In addition to standardization, fill in missing data such as zip codes, Geo-positioning, and so on.

Data Cleansing

Data cleaning is the process of identifying incorrect, irrelevant, and incomplete data and then replacing or modifying the data appropriately. Only when you cleanse your data, you can use it to gain insights that help your company to make better decisions.

Reltio supports out-of-the-box cleanse functions for Address, Phone, Email, Name, String, and some custom cleanse functions. All of these cleanse functions are typically pre-configured and already functional in the tenants you receive with your subscription. However, each of the functions can be tailored as per the requirements.

Data Standardization

Data standardization, on the other hand, is the process of transforming data (available in different formats) to a standard format as defined by the customer. Standardized data follows a certain format and rules for consistency. It is enhanced in terms of the efficiency and also boosts the filtering capability.

Understanding Data Cleansing and Standardization