SQL 2019

SQL 2019

One significant challenge with maintaining a large, enterprise data estate, leveraging multiple data sources, both structured and unstructured, is the inherent performance issues related to data flow and data movement.  While traditional extract-transform-load (ETL) processes still have relevant business and technical use cases, the delays and performance degradation often encountered with these processes can be significant, time consuming, resource challenging and carry the potential for significant technical debt.   While newer extract-load-transform (ELT) processes alleviate this in some instances, it can still present technical challenges in the quest to be nimble and responsive to the business in providing quality data across the enterprise.  Where the use case for traditional ETL or ELT processes is not as strong or compelling, there may be other options. Other issues inherent in traditional data warehousing, large enterprise data estates are managing sensitive data sets from multiple locations, storage costs from maintaining multiple large data sets in a variety of formats on various platforms, as well as significant data governance complexity. What is another option for addressing these challenges?  Enter...
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