CloudOps & DataOps Engineer Aleksandra Shumkoska explains how ensuring a more effective developer experience can help you move closer to becoming a data-driven organization.
We’re all aware of the massive amount of data that’s being generated on a daily basis. That’s only going to get bigger as we shift more and more to a digital world. Big data can bring many benefits to any business but raw data doesn’t have any real value unless it’s made available in the right way, at the right time. That’s where data engineering comes in. It’s the core of a data-driven organization.
By applying a versatile set of techniques, data engineers help to transform data and bring it closer to stakeholders, making it available for exploitation. By exploiting data assets, the data can speak for itself. In other words, we can utilize significant analytical insights from the data to enable better-informed decisions. And this can be applied in many different areas, of course, such as risk management, operational efficiency, product development, and so on. We have all this data at our disposal, so why not use it to our best advantage?
I started my career as an ERP software engineer. As ERP software is all about data, I worked heavily with databases, which I enjoyed. However, after a couple of years I wanted to challenge myself with something new. Data engineering was exactly what I was looking for. Four years later, I’m part of an international team of data experts.
I’ve led and participated in the design and development of data platforms for large organizations in finance, fintech, digital media, sports betting, and other sectors. This has enabled me to build expertise across a diverse technology stack and become experienced in developing more efficient and automated data pipelines for both batched and streaming data.
Working with the DataOps.live platform has meant taking those experiences to another level. It enables the more automated and efficient delivery of data, which can be managed in a centralized manner. In business terms, you reduce the time and resources required to ensure a more effective data delivery process. More effective data delivery means more effective data science, which in turn leads to more effective decision making, risk management, product development, and so on.
Being an effective data engineer requires diverse skills. For example, understanding databases and database operations. Or to be more precise, understanding different types of data storage. You need coding skills, meaning experience in at least one high-level programming language. This goes hand-in-hand with other development methodologies like containerization, version control, and CI/CD. Building data pipelines is a central responsibility of a data engineer, and requires a strong understanding of ETL concepts. And as we often work closely with data scientists, a basic understanding of machine learning is a ‘nice to have’.
Given these multiple requirements, DataOps.live has been specifically designed to make a data engineer’s life easier. It’s a single platform that manages your database, your data pipeline, your testing and production environment, your change log, and so on... Before using DataOps.live, I had to develop all of that from scratch: an extremely time-consuming process that required an extensive effort from both data and DevOps engineers. Having all this brought together in a single tool increases productivity, means new developers can be up-and-running fast, and enables you to focus your efforts on more value-added activities.
At the same time, DataOps.live helps data product owners to address unmet requirements. It provides greater agility, scalability, and reusability. Advanced automation and testing mean faster working and higher quality. It’s a smarter way to apply key product development principles to data projects.
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So, how can you become a more data-driven organization? First, you need to define your data strategy clearly. That is, defining the processes and rules that specify how you will manage, analyze, and act upon business data. The next step is enabling access to that data. The right sections of data should be accessible by the right people, depending on the objective. But having such access is not enough. The data also needs to be maintained, kept clean and up-to-date. Meanwhile, data consumers should be skilled to use the data appropriately, which means investing in staff awareness and education to increase data literacy.
Most importantly, you have to invest in the right tools. This includes having the ability to test your data extensively, because a true data-driven culture is founded on being able to trust your data. Of course, there are simply some things that humans cannot do without technology to assist us, at least not to the levels of speed, quality, accuracy and security that we want. This means investing in the most effective and reliable tools available, to move further and faster towards that goal of becoming a data-driven organization.
Based in North Macedonia, Aleksandra has been with DataOps.live since May 2022. Previously a Senior Software Engineer with Scalefocus, she studied for an Engineer’s Degree in Informatics and Computer Engineering at the University of Ss. Cyril and Methodius. Connect with Aleksandra here: https://mk.linkedin.com/in/aleksandra-shumkoska-270330b7
