How different types of data transformation drive business value

Businesses today have access to a wealth of data, giving them valuable insights to help them make more informed decisions. But with so much data to work with, trying to make sense of it all can be tricky. That’s why many businesses may benefit from transforming their data to help them get the most out of it. But what exactly is data transformation? How does it work? And what types of data transformation methods are out there? Read on to find out.

What is Data Transformation?

Data transformation is the process of converting data from one format to another. This typically involves transforming raw data into a format that is clean, validated, and ready to use. The resulting transformed data is then more usable to humans and computers. Data transformation is an integral part of the data management process, such as data integration, data migration, data warehousing, and data preparation.

Understanding Data Integration

Data transformation is just one of many steps in the data integration process. The two primary data integration methods are ETL (Extract, Transform, and Load) and ELT (Extract, Load, and Transform). ETL involves extracting the raw data from the source, transforming the data on a secondary processing server, and then loading that data to the target data warehouse.

ELT, on the other hand, changes the order of events, by loading the raw data directly into the target warehouse. Then the data is cleansed, enriched, and transformed inside the data warehouse. ELT is a relatively new concept that was made possible by the advent of cloud-based data warehouses.

Benefits of Data Transformation for Businesses

Transforming your data yields many benefits, especially for businesses that gather and analyze large amounts of data on a regular basis. And in light of the recent COVID-19 pandemic, studies show that over 80 percent of businesses are accelerating their digital transformation efforts, which includes utilizing higher amounts of data.

Some of the many benefits of data transformation for businesses include:

Improved organization

Transformed data is easier for both humans and computers to use. It has a clear, defined structure, and is stored in a way that is easily accessible and manageable.

Better data quality

Transformed data is free of noisy, unnecessary data. This eliminates a number of quality assurance issues such as value misrepresentation, missing values, and data inconsistency. Thus, the data is more trustworthy, reliable, and accurate.

Faster decision making

Having access to higher quality data makes it easier to reach evidence-based conclusions. By speeding up the decision-making process, businesses can respond accordingly to rapid changing market conditions and time-sensitive events like emergencies.

Improved device and system compatibility

With the freedom to transform data into all kinds of formats, this helps businesses create data that is compatible with all kinds of devices, operating systems, and other technology infrastructure. This means the collected data can be transformed in different ways to serve multiple purposes.

Is Data Transformation Right For Your Business?

If your business is struggling to translate your existing data into actionable insights, data transformation could be for you. Of course, this means choosing the right type of data transformation method and knowing exactly what kind of outcomes you hope to achieve by modifying your data. Consulting data science experts can also help you develop a clear data transformation strategy.

Whether you plan to store your data onsite, in a physical data warehouse, or in the cloud, it will also have an impact on which transformation strategy is right for your business. Furthermore, the data transformation process should be carried out in a way that does not slow down your other operations. By doing so, you’ll be able to initiate meaningful change in your business and generate data that can help you improve in areas that matter most to you.