Foundational Methodology for Data Science
December 1, 2017
There are numerous rapidly evolving technologies for analyzing data and building models. In a remarkably short time, they have progressed from desktops to massively parallel warehouses with huge data volumes and in-database analytic functionality in relational databases and Apache Hadoop.
As data analytics capabilities become more accessible and prevalent, data scientists need a foundational methodology capable of providing a guiding strategy, regardless of the technologies, data volumes or approaches involved.