It’s no secret. We are officially living in the era of big data. Nearly every business—especially large-scale enterprises—collects, stores, and analyzes data for the benefit of growth. In most daily business operations, managing data is a norm, using tools such as:

• Databases
• Automation systems
• CRM platforms

If you have worked in any company for some time, then you’ve probably encountered the term Data Normalization. A best practice for handling and employing stored information, data normalization is a process that will help improve success across an entire company.

Here is everything you need to know about data normalization along with some tips on how to improve your data effectively.

What is data normalization?

Data normalization is generally considered the development of clean data. Diving deeper, however, the meaning or goal of data normalization is twofold:

1. Data normalization is the organization of data to appear similar across all records and fields.
2. It increases the cohesion of entry types leading to cleansing, lead generation, segmentation, and higher quality data.

Simply put, this process includes eliminating unstructured data and redundancy (duplicates) in order to ensure logical data storage. When data normalization is done correctly, you will end up with standardized information entry. For example, this process applies to how URLs, contact names, street addresses, phone numbers, and even codes are recorded. These standardized information fields can then be grouped and read swiftly.

Who needs data normalization?

Every business that wishes to run successfully and grow needs to regularly perform data normalization. It is one of the most important things you can do to get rid of errors that make running information analysis complicated and difficult. Such errors often sneak up when changing, adding, or removing system information. When data input error is removed, an organization will be left with a well-functioning system that is full of usable, beneficial data.

With normalization, an organization can make the most of its data as well as invest in data gathering at a greater, more efficient level. Looking at data to improve how a company is run becomes a less challenging task, especially when cross-examining. For those who regularly consolidate and query data from software-as-a-service applications as well as for those who gather data from a variety of sources like social media, digital sites, and more, data normalization becomes an invaluable process that saves time, space, and money.

Are you ready to harness the power of data? See how DataOps with BMC can transform your analytics.