
Data Engineering with AWS
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Along with the rise of new data types and increasing data volumes, we have seen an increase in the ways that organizations look to draw insights from data. Machine learning in particular has become a popular tool for analytics, enabling organizations to automatically extract metadata from unstructured data sources, which can then be analyzed with traditional analytic tools:
As we saw in the previous section, enterprise data warehouses have been the go-to repositories for storing highly structured tabular data sourced from traditional run-the-business transactional applications. But the lack of a well-defined tabular structure makes unstructured and semi-structured data unsuitable for storing in...