With the market constantly expanding and evolving in the last decade, there have been drastic changes in the role of a data engineer. In the time when the industry is shifting to cloud data and scalable processing, it clearly denotes the frequent collection of data. To manage such sophisticated infrastructure, data engineering consulting services tend to be a necessity.
The growing number of responsibilities, available tools, and significance clearly means that it can sometimes become challenging to define the role of data engineers. Well, the only way to understand data engineering is first to understand “engineering”. Data engineers are the ones holding expertise in designing and building pipelines that can transport and transform data in a format that can be used by the end-users.
These are the pipelines that need data from several sources and gather them in one warehouse as a single source. It might sound extremely simple and effortless, but the reality is it requires high-end knowledge and expertise. In the modern landscape, finding a data engineer is a real struggle for companies. However, if you still do comprehensive research, you can find the best choices.
Three Most Valuable Trends That Can Change the Role of a Data Engineer
There is no denying that to acquire the best data engineering services, there is a need for the team to have knowledge of a lot of things. They need to develop proper practices in SDLC, information security, business domain and principles of data architecture. Apart from these, there is always a need for having comprehensive knowledge of the latest industry trends.
Since the sector is evolving at an unprecedented pace, having a proper understanding of the analytic development can become helpful for the organisation. So have a look at the following to acquire some more details about the three changes in Data Engineering.
The Transformation to Cloud
In the current scenario, the cloud is perhaps the only name taken up by the organisations. Some of the most influential organisations like government and finance, who were always away from embracing it, have started understanding its importance.
It is of no surprise that the computing market has moved higher. Only in these 4 years, the need has doubled from approximately $114B, and which has reached a whopping $236B. Over the past few years, Amazon Web Services was the only name to lead the market, which now enjoys 33% of the market share. Later, Google Cloud Platform, which has 6% and Microsoft Azure which has 16% of the market share, are slowly catching up the pace.
Growth of Open Source
In the past days, when data engineering was dominated by closed source and proprietary tools, this is definitely not the case now. These days it is more about the demand for open source tools. In many instances, it has been witnessed to have preferences in the data organisations.
Open-source libraries like Tensorflow and Spark have now become a common choice for organisations. Since these are available, organisations can now minimise the product or vendor lock-in.
Expansion of Data
There is no doubt that in the modern days, when the cloud is taking over the organisation, it has increased data generation. More than ever, data disposal is more now, which is why it becomes crucial for engineers to have a complete understanding of the way to scale them.
Currently, there are over 90% of the total global data has been created within these few years. This, therefore, makes it inevitable for the data engineers to have competency in using the range of tools that can become helpful for them to assess and organise the vast data that is present within the organisation.
Bottom Line:
In the last few decades, most companies have undergone digital transformation. The significant number of data that the organisations have produced only makes the data infrastructure more complicated. In such a scenario, obtaining data engineering solutions from Neuronimbus can be a valuable choice. With some of the top data engineers in their team adept in using the latest tools, they mitigate the complexity and ensure smooth processing.
In the coming time, this is nowhere to change but to evolve. Therefore obtaining help from some of the excellent data engineers can help to enjoy the constant growth.
