December 12, 2022


The state of the art for engineering in analytics has evolved significantly over the past 25 years. Early on the practice of data modeling emerged as a means to improve performance and make data more accessible and easier to use for authors, analysts and creators. Since the early days much has changed. On the technology side, we have seen advances in traditional relational databases to support analytics, the invention of databases designed specifically for analytics, analytic appliances, and now modern databases in the cloud, designed not only for analytics, but to streamline many of the workflows commonly used to engineer data

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