Why is Data Engineering Important?

Data is one of the most valuable resources nowadays. In 2021 it was estimated that 2.5 quintillion bytes are produced EVERY DAY. With the development speed in 2023, this amount will be much higher. But this is raw data that can only be useful with proper actions.

And this is where data engineering comes in handy - it helps to use this tremendous amount to gather helpful information and plan based on the results.

What is data engineering?

It’s simply an approach to developing information systems. It consists of sourcing, transforming, and managing data from various sources. As a result, the raw data is converted into useful and accessible information. Data engineering can also be combined with artificial intelligence to create order in raw data's chaos.

The everyday job of data engineering is to build systems that can go through with all those actions - and it’s universal for almost all possible industries that gather data.

What does a data engineer do?

Similar to the above, their role is to build information architecture of any data-related ecosystems to be able to process big data with the use of many data management tools and result in creating data pipelines. In their everyday job, they will also use artificial intelligence and machine learning algorithms to make their job more accessible, efficient, and consistent. They also can create user-friendly reports for business departments by using data visualization techniques.

We can divide this job into three types of positions:

1. Generalists - small teams that usually collect data
2. Pipeline-oriented engineers - the pipeline is a workflow that consolidates data from different sources
3. Database experts - they are the ones that design and maintain data warehouses across organizations

Benefitsan of an organization that is data-oriented

Now that we know a bit more about what data engineering is and what a data engineer job can be, let’s take a look at the benefits that it provides for organizations.

Agility & Efficiency

If the data is gathered and analyzed correctly, it can be used to make any business decisions faster and with much more certainty than ever before. It takes much less time to explore the data managed by data engineers - because it is clean, verified, categorized, and unified. So all the time spent to process the data before now can be spent on implementing the changes needed to make a change. This may also mean having better openness to new types of business opportunities.

Revenue growth

As you may guess after reading the previous chapter, implementing data engineering will give you an undoubtedly large advantage over your competition. It simply helps you to make your decision-making process faster and more reliable and be open to innovation that, in modern times, will give you tremendous growth opportunities.

Audiences analytics

Most companies already gather their customer's data (either through google analytics or any other source). But the problem is that collecting the data is simply not enough nowadays. Without the proper analytics (even as simple as demographic ones), it’s useless. This is where data engineering comes in handy, allowing you to understand your current customers better and be sure that your services are tailored to their needs. It will also allow you to identify the key target groups for your organization and select groups that are simply not valuable - which may result in the change of your offer and increased profitability.

Verifying business decisions

I already mentioned that data engineering could be used to make better business decisions faster. But making the decision is just a part of the story. Usually, the most important aspect is the verification of it. And this is again an area where data engineering can bring enormous benefits to the equation. Any decision generates more data, and a complex one. And data engineers can develop systems that automatically verify the results; hence, the organization can draw conclusions quickly and adapt to unpredictable outcomes to make the process even more efficient.

Predictions

It’s no big news that statistics and data science can bring insights into the future. But anyone who took even a beginner's statistics course knows it’s a numbers game. The bigger the statistical sample, the better the prediction results. With data engineering in place, the organization may have access to much bigger amounts of data - but what’s even more important - is a properly prepared one. Thanks to that, businesses can make decisions about the future based on pretty realistic predictions. And thanks to machine learning and artificial intelligence, it will change into an even more reliable way of planning in the foreseeable future.

Summary

As you can see, there are numerous benefits that data engineering may bring to your business. I could not list all of them, as they also depend a bit on the type of organization. Still, if you want to see the effect in just a few words, I would say that data engineering helps to make proper business decisions in a way that was unimaginable before. Hence every organization should implement this way of designing systems into their everyday life - to some extent.

Drop us a line to see how data engineering can help your business grow. At Sunscrapers, we understand the value that comes with this trend and will be able to help you become part of this data-centric revolution.

Read more

1. What is Data Engineering? - Complex guide with examples
2. Who is a Data Engineer?
3. Data Engineering vs. Data Science: comparison
4. Data Engineer, Data Scientist, and Data Analyst: what is the best choice for 2023
5. ​​How to become a Data Engineer?