Data Normalization Services
It’s safe to say that we live in the era of big data. Collecting, storing, and analyzing information has become a top priority for organizations, which means that companies are building and utilizing databases to handle all that data. In the ongoing effort to use big data, you may have come across the term “data normalization.”
Data normalization is essentially a type of process wherein data within a database is reorganized in such a way so that you can properly utilize that database for further analysis.
Crezvatic helps companies normalize their data or business information sourced from various places, making sure that the data are in the correct format with data values portrayed in the correct fields. An essential aspect of data maintenance, data normalization provides standardized and consistent labels for selectable fields.
With our data normalization services, we assist our customers with:
- Removing redundant / repetitive data
- Making sure that data is logically stored and data dependencies make sense
- Reducing redesign efforts when extending the structure of the database
- Making the data model more explanatory to end users
Custom Data Normalization Processes at Crezvatic
Tailored to specific customer requirements, Crezvatic has developed various procedures and techniques to normalize the significant fields in marketing and transactional data.
Any open text field can be challenging. In any case, we consider that categories of data which defines the buyer persona or have an impact upon business procedures are the best candidates for data normalization.
We transform your huge data into a standardized list to empower you to take actions that would otherwise be tricky to perform correctly.
For example, data such as name and name components [including prefix, suffix, middle names and titles, etc.], job title, job function, organization, industry, state, country, or platforms/technologies impact lead generation and nurturing. Therefore, correctness and consistency through data normalization are critical in such cases.
A major part of our data normalization work flow-in from our data migration projects comprising consolidating legacy data sources and subsequently migrating the data into CRM systems like SalesForce and Zoho, etc.