What is Health Informatics
26 March 2022
In an era where big data consumption is exploding, companies increasingly require experts capable of dealing with large amounts of data such as customer information, competitive research, and product performance results. They also need professionals to build and manage their increasingly complex websites and apps. Since data is probably the most valuable resource, the world has - according to the World Economic Forum, the world's data was worth about $3 trillion in 2017. Ultimately, these needs have led to the creation of two exciting technical fields: data engineering and software engineering. While these two fields can overlap sometimes, they have different areas of specialization.
It is not uncommon for different roles in technology to share similar responsibilities, from data scientists to data architects. Apparently, slight differences between these titles can lead to confusion. In fact, those who are not familiar with technology might confuse terms like "data engineer" and "software engineer" since both rely heavily on programming skills. It is possible that some might even think both types of engineers perform the same functions.
However, software engineers are usually largely inactive when it comes to data infrastructure. Their primary focus is on building user-friendly web applications. On the other hand, a data engineer is responsible for maintaining large datasets and creating structures for storing them. Even though each profession has a common background in information management, the responsibilities of software engineers and data engineers are incredibly different. Throughout this article, you will learn about the differences between data engineering and software engineering and how both roles are essential for an organization.
Let's begin with data engineers.
A data engineer is responsible for designing, implementing, maintaining, and securing an organization's data infrastructure. Depending on the size and scope of the organization, "data infrastructure" may take on different meanings; a smaller company may rely on small-scale, low-maintenance databases, while larger organizations manage their data across multiple on-premises and cloud-based data platforms.
Regardless of the scale of the project, the objective is the same: to generate quality data for use in business-critical analytics or reporting. Data engineers are fundamental to all organizational data initiatives since they ensure that data has been appropriately stored, cleansed, or integrated. Therefore, in the modern, big data era, it is imperative for data engineers to remain up-to-date on new trends as data engineering best practices are constantly changing.
In order to become a successful data engineer, you should have a thorough understanding of programming languages, databases, and cloud technologies. The following is a list of the most important skillsets and tools a data engineer should possess.
As we have already discussed data engineers, let us now turn our attention to software engineers.
The main difference is that data engineers manage the data infrastructure, whereas software engineers design and develop the software. In more detail, software engineering is a branch of computer science that falls into two main categories: applications and systems software engineers.
You are responsible for developing internal or external applications or platforms that users can access. The application software engineers will work with developers, product managers, designers, and marketers to perpetually tweak the product and release updates.
As a systems software engineer, you are responsible for creating and maintaining an organization's computer systems. For example, you may have to set up networks, create operating systems for applications that interface with users, or maintain IT documentation.
A further noteworthy distinction in software engineering is between "front-end" and "backend" development. In contrast to the front-end, which comprises all the development work involved in creating an intuitive user interface, the backend consists of the server and system maintenance to deliver information to the user. While application software engineers may be interested in both front-end and backend engineering, systems software engineers are strictly involved in the latter.
Several disciplines comprise software engineering, including requirements elicitation, software design, software configuration management, software engineering models and methods, software quality, and core coding and mathematical concepts. The field is highly technical and requires a deep understanding of programming languages and a sharp focus
However, a good software engineer will also possess solid interpersonal skills despite their technical nature. To determine the final, prioritized list that a software engineer and her team will need to complete, the software engineer needs to collect requirements from various stakeholders throughout the organization.
Among your responsibilities as a software engineer are working with sales representatives, quality assurance staff, and developers. The following summarizes the most important skillsets and tools that software engineers should possess.
Essentially, data engineers look into the practical applications of data collection and help with data analysis. Typically, they are tasked with processing large data sets and establishing the structures that efficiently house data as well as building, maintaining, and securing big data. Also, data engineers will need to be proficient in programming languages like SQL. Before moving into data engineering, data engineers typically began their careers as software engineers. Since software engineers are proficient in computer programming, they are responsible for designing and developing operating systems and for front-end and back-end development. Even though some software engineers are heavily reliant on data, it is not guaranteed that they will be dealing with data analysis as part of their career tasks.
In an organization, it can be challenging to determine which title is most appropriate for a data engineer versus a software engineer. Therefore, it is critical to understand the typical background and responsibilities associated with these roles to choose the most appropriate candidate. However, teams would often benefit from having both software and data engineers. In any case, these roles should be seen as complementary rather than interchangeable.
There might be a similarity in salaries and knowledge between software engineers and data engineers, but their roles and responsibilities in the workplace differ. Even though some software engineers are involved with data infrastructure, their roles remain distinct from those of data engineers. In contrast to data engineers, software engineers take a macro view of things. Ideal candidates for the data engineer role have experience in machine learning, big data, and pipeline building. It is important to note that the title "software engineer" can refer to various positions, including backend engineers, development engineers, database engineers, and full-stack engineers.