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For more information, check out the best Data Science certification. A data scientist’s job description focuses on the following – Automating the collection process and identifying the valuable data. Furthermore, they construct software applications and computer programs for accomplishing data storage and management.
But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured rawdata since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses.
You have probably heard the saying, "data is the new oil". It is extremely important for businesses to process data correctly since the volume and complexity of rawdata are rapidly growing. The data might be ambiguous if it is manually searched across several sources. Well, it surely is!
However , the traditional methods of executing ETL are increasingly struggling to meet the escalating demands of today’s data-intensive environments. ETL stands for: Extract: Retrieve rawdata from various sources.
The practice of designing, building, and maintaining the infrastructure and systems required to collect, process, store, and deliver data to various organizational stakeholders is known as data engineering. You can pace your learning by joining data engineering courses such as the Bootcamp Data Engineer.
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