What Is Data Standardization?

Learn the basics of Data Standardization, with a clear definition and examples of how Data Standardization makes it easier to leverage your data.

What Is Data Standardization?
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Data standardization allows you to take data from different sources and systems and convert it into one standard format. This makes it easier for users to analyze the data. With data standardization, you can get clearer analytics, better reports, and more consistent data from all of your sources.

Typically, businesses have data stored in the cloud, databases, data warehouses, and other sources. This data is likely disparate and fragmented. With data standardization, you can ensure all of this data is easily readable and able to be analyzed. In this article, we’ll dive deeper into what data standardization is and why it’s important.

Why Is Data Standardization Important?

There are a number of reasons that you should be implementing data standardization. Understanding your data and making it simple to comprehend is necessary for any business. With data standardization, you can achieve the following results.

Consistent, unified data formatting: With data standardization in place, your data will all be formatted in a consistent manner. This gives your team peace of mind that the data they’re seeing is the right data.

Identifying errors and issues: Data standardization helps you identify errors and missing links in your data, so you can restore your data and make sure it’s accurate.

Removing irrelevant data: When you standardize all of your data, the unimportant or unnecessary data can be removed, ensuring everything that is important and relevant is what is available.

In short, data standardization cleans up your data and makes it much easier to process. If you’re using any data reporting tools or analytics tools, it’s essential for your data to be easy to collect and process. With data standardization, you can count on all of your reports being accurate, high quality, and as clean as possible. Data standardization makes it so that everyone — from your data team to your employees and even your data software — can understand the data that’s coming in.

Key Examples of Standardizing Data

To better understand data standardization in action, let’s take a look at a few key examples of what standardizing your data can do and how it can impact your business.

Unifying Siloed Data in Your Company

Data silos are not desirable. When you have a data silo, the data in that collection can’t be accessed by other teams. If you want your team to be interconnected and everyone to have easy access to the data needed for their roles, you need to unify siloed data across your company.

Unifying your data silos will make sure collaboration between departments is simple. It makes sure your data is consistent across your company and that everyone can get the same overview of data when they need to.

When you unify your siloed data using data standardization, you not only break down these barriers, but you also make it so the data can be found by team members quickly. Eliminating data silos is the best way to give every team all of the data that’s important in your organization.

Simplifying Data Governance

Data governance is essential for businesses that use big data. With data governance, you can control who can access data and how they can use it. This ensures that data is secure, that it’s accessible to the right team members, and that the data in your system is of the highest quality.

Creating a data governance strategy isn’t an easy task, but it can be made easier with data standardization. Data standardization simplifies the data governance process and helps you more clearly define the processes and your data governance implementation.

Data Team Efficiency and Throughput

Data standardization is a huge boon to your data team. When they’re working with consistently formatted, high-quality, accurate data, they can increase their efficiency and throughput significantly. Not only does having consistent formatting make their job easier, but the increased level of accessibility also ensures that they can always get the data necessary for their work.

Data teams will no longer have to parse through messy and fragmented data to get what they’re needing. They won’t have to pull disorganized data from silos to find the right information. They’ll be able to do their jobs more efficiently and more effectively than ever before.

Sharing Data Among Systems, Departments, and Partner Organizations

Data standardization also makes it easy to share your data between systems, departments, and the partner organizations you want to have access to your data. This opens up the barriers between data sources and makes it simple for everyone to use the data as they see fit. It also makes sure that any new data collected from these sources is formatted properly regardless of where it’s coming from.

One Platform for Standardization Across All Your Data

If you’re looking for a platform that can help you standardize all of your data across your data sources, Narrator can help. Narrator is a self-service analytics platform that makes it easy for anyone in your organization to access data-driven reports and analytics with simple queries.

Narrator allows you to sync all of your datasets, creating a single unified source of truth that your team can use. Your data team won’t need to respond to every request for data reports, because the self-service and analysis features are so easy for team members to use. This saves your data team time, it saves your other team members time, and it makes for a more efficient, data-driven business overall. If you’re interested in giving your team powerful self-service analytics tools, then choose the Narrator Data Platform.

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