One of the keys to success for any organization is data. It is data that can give you a real competitive advantage and ultimately help you reach immense levels of success and accomplish all your goals. 

Thanks to the huge boom in technology over the last decade specifically, capturing large amounts of data has never been easier. In fact, pretty much every company has so much data that they do not quite yet know what to do with it. 

This brings many companies to an interesting dilemma of actually having to figure out how to store such large quantities of data and do so in a way that is organized efficiently and effectively. 

This is where having a modern data stack can be a real game-changer for many organizations. When they are dealing with millions and billions of data that is being generated for them, there needs to be an extremely efficient and automated way to do this so that there can be minimal human error and maximum output.

Data transformation is essentially using modern tools and technology to create incredibly insightful data stacks for your company to use. 

As we progress well into the future, the importance of data is not going anywhere. If anything, it will become more and more essential for organizations to optimize the way they can collect, store and utilize data.

To help you get on board with all things that involve data transformation, we have created the ultimate guide so that you can get up to speed and start making the most of your data too!

What is Data Transformation?

So you have a ton of data. But what are you actually doing with it? Data transformation is the art of being able to take data you have collected and convert it into a data stack that drives your business—whether that be decision making, audience segmentation, or strategies.

But do not worry, data transformation is something that is not manual. In fact, it uses the incredible advancements of technology to make your life easier and instead relies on AI and automation to do the data transformations on your behalf.

As a result, data transformations will allow you or anyone else that has access to the software tool to get the data sets they specifically need for their own job objectives. The tools that are available currently are so intelligent that for most data sets it will only take a matter of seconds, even if you have an enormous amount of data for the program to sort through. 

How Does it Work?

Data transformation is designed to identify changes and aggregations in data sets. It works with the likes of data warehouses to sort through the data that is cataloged within and convert it into data sets that are useful and practical for companies. Here are the steps involved. 

Step 1: Discovering the Data

First, the data must first be discovered. This is done by using various data profiling tools or scripts to sort through and understand the nature of the data and the structure of the data. From here, millions of data can easily be sorted through and discovered in an automated way. 

Step 2: Map Out the Data

The next step is to actually collate the various data accordingly. This means connecting and matching the data in a way that makes sense in terms of themes, audience segments, or results. It is this step that will really make it easy to get robust data sets in the future. 

Step 3: Generating Code

All software will need some level of coding to it. This is where you will rely on the expertise of your own in-house technology team or an external agency to support coding this. The coding script is going to help ensure the data transformation is both accurate and automated well into the future. 

Step 4: Execute the Code

Once you have developed the code, you will want to then implement it in a way that actually kickstarts the data transformation. Give yourself the time to review the data and the results, looking for any abnormalities or errors along the way. It is rare a code is perfect right away, so make sure you have some leniency with this all. 

What are the Benefits?

Finally, you will want to make sure that the data transformation you have implemented is actually benefiting your company.

 Benefits of data transformation done right include an enhancement of data quality, a reduction of data errors, and a much more high-speed process in collecting data sets.

 The data transformation process plays a critical role in ultimately producing data sets that will drive businesses to success and support decision-making. 

Conclusion

Getting started on implementing data transformation is an important step in ensuring your data collection efforts are maximized and that you stay relevant in the decade of data!