Life is simpler when data is available in a small and structured manner. Such data can be easily processed using tools that can be used even by non-technical people and easily interpreted by humans. However, as the volume, velocity and variety of data increase, new challenges arise. From storage to transformation to gaining insights, a significant amount of data needs to be processed within a given time frame. This size and scale adds complexity. According to a study, 98% of all data being generated today is unstructured. To process such data, traditional tools and techniques are not enough. We need technologies that are inherently developed to handle large and complex data sets.
Challenges of large data sets
Data engineering teams face several challenges when processing large data sets. Some of these challenges include:
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