What Is Data Transformation? Here’s Everything You Need To Know

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Data transformation definition: Data transformation is the process of converting and structuring data into a new format that a business can analyze, process, and use for growth.



It’s no secret that you need data to make informed business decisions. If you want to optimize your marketing strategies, you need data to fuel your insights.

Not all data you collect can initially make sense, though. Enter data transformation.

Think of data like carbon. It may need to undergo high heat and investor database before it can turn into a precious diamond. Similarly, data needs transformation before it becomes valuable information for your business. If you want to know more about data transformation, you’re in the right place.

This blog post will go through these topics:

What is data transformation?
5 benefits of data transformation
4 challenges of data transformation
5 data transformation techniques
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What is data transformation?
Data transformation is the process of converting, cleansing, and structuring big data into a new format that a business can use to analyze, process, and aid in decision-making. Data transformation helps companies grow, and companies often use it to convert data so it matches the destination’s format.

For example, let’s say your heavy equipment rental business runs lead-generation campaigns on search and social media. Because your lead data have different sources, their formatting and fields are not the same.

In addition, reports from different marketing channels may have different terms for the same metrics. To combine performance data from both channels, you need data transformation to collate and aggregate them.

A data transformation process can be performed manually, automatically, or a combination of both.