Data normalization is the process of removing duplicate data from a database thereby maintaining its consistency and efficiency. It involves dividing complex tables into simpler ones to better define the relationships between several entities.

With the help of data normalization services, perfect segmentation can be achieved as it is easier to define the correlation between data. Without normalization, it is not possible to implement segmentation and effective working of a database. It allows business majors to get proper insights into their business and establish an ideal target market.

Process of data normalization

Data normalization is mainly concerned with providing a robust structure to a database that offers improved customer profiles.
It takes into account at a three-step procedure;

1. Understand data and identify the fields to be normalized

The first step towards data normalization is to develop a thorough understanding of data. It is a very difficult process to determine the layout of what actually normalized data would contain. Organizations must know which data fields are crucial for their business and can be the best candidates for normalization. For instance, starting with job titles is a pretty good option to finalize data fields. As job titles are an important aspect of a company’s database, normalizing can help in improving its standard value.

2. Determine data entry sources from where the data has been collected

It is important to determine the source of data entry. Whether they are forms, list, surveys or any other forms of information. This data entry sources would help in qualifying and segmenting data into various categories. It develops an analysis of which fields need normalization and which ones can be ignored. For example, for contact details, data entry sources will be able to determine how contact discovery services provided information to the organization. Hence, the organization would get potential variables to normalize the contact field.

3. Establish a normalization matrix

When the relevant information is gathered, inconsistent data is now mapped to the standard list developed. The entries in the form of an open text field are matched with segmented data. After the standard has been set, and the match has been found, the corresponding data entry is written into the normalized data value. Now segmentation is performed on the basis of that particular field of data. There is no need to provide a data point with entry.

IBCCONNECT provides compressive data normalization services to its clients allowing them to maintain the integrity of their data across various inconsistencies. Our services provide this functionality to help you save time and money.