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Data is one of the most important assets of any business. Businesses use data to fix various issues occurring in the company, such as customer relations, product development and website-related processes. Data generated from various sources about customer preferences, bills and shipping and other behavioral information helps businesses to obtain an overall and comprehensive view of their customers.
Nowadays, data is available to us in enormous amounts and is increasing ten folds over time. And managing data in such big sizes is not easy for any enterprise. Companies of all sizes, big or small have data in substantial amounts, and to make that data accessible and readable, we need data engineering.
In layman terms, data engineering organized unstructured and unfiltered raw data to make it easy for other people and systems to use that data. According to TechEela, data engineering revolves around designing and creating data pipelines to work upon data analysts and data scientists. These pipelines collect data from various sources and store them in a warehouse, representing data in uniformity. TechEela has also covered a beginner’s guide to understand what is data engineering too.
Although it sounds like an easy job, a lot of skill is required for this role. That is why data engineers are in such high demand these days and are available in noticeably short supply. The term ‘data engineering’ was evolved to define a different role from working with traditional ETL tools and was developed with its tools and techniques to manage the ever-increasing data size. As data kept increasing exponentially, data engineering became a part of software engineering, whose emphasis was essentially on data. Data mining, data warehousing, data modelling, data visualization, data crunching, data infrastructure, and metadata management are said to be its processes.
Need for Data Engineering
To conclude, data engineering is needed to create pipelines, identify business trends to extract valuable insights and information from the data. Without data engineering, there won’t be the advancements in technology that we see today.
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