What Is Data Engineering and Do You Need It?

In today’s world, data is the key to almost any business’s success.

The more data you process, the more advantages you’ll have over your competitors. You may be surprised to learn that about 2.5 quintillion bytes of business data are generated each day. Using data science, you’ll be able to utilize it according to your needs. But working on massive amounts of data requires resources, like data engineering. So, is it wise to rely on data engineering solely?

To answer this question, you have to understand what data engineering is, when you need it, its functions, and how to utilize it to your advantage. If you are ready to learn more about it, let’s get started!

Data engineering is the process of gathering, structuring, and analyzing data for business purposes. Since data is a valuable resource for any kind of business, it needs to be organized in a way that can be used to make trustworthy business decisions. To do this, you need software engineers (data engineers), who are responsible for preparing and managing data on behalf of the business.

However, the role becomes difficult once the business’s operation size increases. Sometimes, larger amounts of data means hiring more engineers to build a complex data engineering process.

To get the best utility from data engineering, you have to understand the skills required to do the job. Without understanding the roles of data engineers, you can’t create a successful data collection and structure project for your business. After reading the following roles, you might have an understanding of how you should approach data engineering.

  • Small Generalist Team: You can hire a small team of generalist data engineers to do the job. A general data engineer only compiles data and evaluates it for final users. Mostly, small businesses hire this type of engineer when they have to maintain a small database.
  • Pipeline-Centric: Small and medium-sized companies hire pipeline-centric engineers for their businesses. This sort of company has more complex data to compile and study. The team consists of two or more data scientists where a data engineer has expertise in the data distribution system and computer science. Sometimes, they have to create a tool on which data scientists can run metadata with efficient algorithms.
  • Database-Centric: A database-centric engineer is usually found in big companies with a vast amount of data. This sort of engineer mainly works to configure a database system that is very fast in both understanding and transporting. This requires an ETL (Extracting, Transforming, Loading) data process. Database-centric engineers have a good number of data analytics and researchers on their teams.

Having decided on the roles of data engineering you need for your business, let’s have a look at its major functions.

The entire process of data engineering starts by collecting and structuring raw data. But what is raw data? Raw data is the unstructured information your business generates in the form of unstructured numbers, text, images, sounds, videos, etc. For example, your business generates raw customer data like names, addresses, phone numbers, and more. When a data engineer classifies the raw data, it becomes logical.

After organizing the data, it becomes accessible and useful to your business. However, the organization of a small business’s raw data can be easily done using Excel or SQL databases. So, whether you need a data engineer for that is questionable. Even for large businesses, raw versions of data can be contained using various tools.

When you need to access your stored data and utilize it in real time, you need a pipeline system. This system starts with collecting the raw data from the SaaS platform (e.g., CRM tool, email marketing tool). Then the data is compiled to store in data warehouses so that data scientists can analyze it with analytic tools to answer questions such as how to increase the sale of unpopular products. This data can be a list of users who purchased your product this month, their ages, preferences, etc. A data pipeline consists of four factors:

  • Sources of data
  • Reading from the source
  • Filtering the data
  • Sending the data to a data warehouse or data lake

This function requires organizing business data so that a company can meet its goals within the shortest possible time. Data engineers focus on designing algorithms in an efficient way, making analytics much easier. However, certain tools can give accurate results and help companies provide effective decision-making for business goals.

Data engineering positions can be different based on the organization. Sometimes, they have to work as analysts for the company. They evaluate the data to find trends of an outcome and interpret the results to the top management. The results could be a business forecast, previous history, business value, profit margins, etc.

Engineers have to create models to interpret the results of information about your business. They have to ensure the data is clean and ready to use. Figures and models of your venture are used by the engineers to forecast and create effective data models.

Data engineers develop algorithms that ensure the data pipeline is smooth for the analytics team. Logical searches and transporting data to different sections all are based on algorithms.

Data engineers can develop customized analytical tools according to your business’s requirements. They can also develop customized data collection tools using C++, Java, or other programming languages.

Data engineers work as a team along with your data scientists. They can manage your whole analytics team in an efficient and productive way. They can also carry out your team with customized data pipelines and algorithms for your projects.

Previously, organizations depended on data engineers to compile and illustrate big data. Over time, many programs were developed to make it easier for the analytics team. Therefore, it became quite possible to get the same result using modern software tools.

If your business requires the analysis of huge amounts of data, having an understanding of data engineering functions and checking out data engineer hiring costs is recommended. There are several key factors indicating that you require data engineering services:

  • You have three data scientists in your business analytics team.
  • You have 50 active users in your Business Intelligence platform.
  • Your biggest table in the data warehouse hits one billion rows.
  • Your organization requires custom data pipelines and there are three or more to build.

When you decide to employ a specialist for your team, you should think about a couple of aspects according to your needs. Hiring a specialist based on your organization’s size and budget is imperative.

Engineers require a combination of skills consisting of engineering knowledge, data expertise, and database systems. A brief idea of their skill set is given below.

  • Engineering Knowledge: Data engineers must know the programming languages used in the system. The usual languages are Python, Java, C#, and Scala.
  • Expertise in Data: They are required to work in a team where knowledge of algorithms and modeling comes in handy. The ETL process and managing the platforms is compulsory to work with other data scientists. They also need expertise in BI tools and data science and analysis.
  • Database Systems: A specialist designs data storage and builds the entire system. They perform SQL queries on the database to extract necessary data. Database expertise also requires knowledge in other popular tools like Oracle, Panoply, and Redshift.

The salary depends on data engineering skills, experience, and location.

Thus, in the UK, an engineer earns up to £72,000. According to some job sites, the payroll range is between £40,351 to £72,000 annually. In Germany, the salary averages £52,600 annually, whereas in Singapore it’s £37,000, and in the USA, it’s £78,000.

A database application is a program that retrieves information from a database. By using a database application, you can easily store, collect and modify business data in a customized database without the need for a data engineer.

So, if you don’t need to hire a data engineering team or person, then database applications are the best ways to get started with your data management process. Moreover, data security, customization, and flexibility are services every business is looking for from database applications.

Developing a database using the traditional process might be inefficient in terms of cost and time, while database applications can make the processes efficient and productive. Some points on why you may require an online database application are given below.

  • You can control the database on your own accord, giving access to whom you want and customizing reports according to your demand.
  • It’s easily accessible. Multiple users can check real-time information through an online application.
  • You can attach multiple tools to your database. This is useful when you are required to transfer information from one platform to another. Also, you can combine other services to integrate with your own database.
  • It’s a cost-effective solution for your organization.
  • Such applications will be highly secure, so you won’t require security experts for your database.

You might be wondering how you can get your own customized database application. Let’s talk about a database application program and how to utilize it for creating your own customized database application.

Worksheet Systems

Worksheet Systems is cloud-based data management software on which you can create customized worksheets and manage them in your own way. It provides customized solutions, commercial integrations, and streamlined data management to optimize business decisions.

Worksheet Systems has already created a strong presence in data-intensive industries. It provides data solutions to customers who need a service that includes scalability, security, and control.

Also, Worksheet Systems can help you build your customized database application with a few steps:

  • The worksheet system team guides you to specify the design of your database, workflows, and logic required to build your customized application.
  • Get your web-based database application and use it without learning any coding, like Java or CSS.
  • Upload your database application to the cloud and make it accessible for web and mobile users.

Worksheet Systems is a way to create database applications for your business by utilizing customized services with flexibility and error-free results. While the traditional process of hiring a data engineer is possible but expensive and time-consuming, a customized Worksheet Systems database application can solve your problem in a better way. The best result is that your productivity and growth will increase by using database applications.


Worksheet Systems provides you with basic to advanced level data management solutions.

  • It offers Free Forever options where you can use five pages and tables, along with one app, for free. You can use it by just signing up on the platform, payment-free.
  • You can try Pro for £50, where you will get 50 pages, 20 tables, and five custom apps.
  • If you require work on huge data, you can take the Premium module for £100. In Premium, you’ll get 100 pages, 50 tables, and ten custom apps.

Both paid modules are available with a 14-day trial. In addition, they offer fully customized solutions for bigger organizations in their Enterprise module to meet your unique requirements.

In conclusion, data engineering is a practical way to organize large amounts of data for your business. Hence, a specialist or engineer can help you to assemble raw data and construct a system for your data and pipelines. Having a data engineer on your team needs to be justified based on your data volume, structure, and the complexity of the work.

However, a data engineer isn’t always required by businesses; sometimes a database application like Worksheet System is enough. By using Worksheet Systems, you can create your own database without any programming knowledge or high primary costs.