Data science and software engineering are similar in many ways. However, dig deeper, and you’ll find key differences in their type of work, in the professionals working in these fields, and how they execute their projects. Data Science vs. Software Engineering Fields What is Data science? If you ask five data scientists to define data […]
How do you manage data science projects? Is it software? Is it research? Or maybe, simply magic? This four-part post is an overview 10 ways projects are or could be managed. To start, we’ll explore ad hoc project management, waterfall, and CRISP-DM.
What is CRISP-DM? Jump to… What are CRISP-DM’s Phases? Is CRISP-DM Agile or Waterfall? How Popular is CRISP-DM? Should I use CRISP-DM? What are other KDD Approaches? Where can I learn more? The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that naturally describes the data science life […]
What is Waterfall? Waterfall, also referred to as the classic life cycle or traditional project management, originated from manufacturing and construction and was applied to software engineering projects starting in the 1960s. A waterfall project flows through defined phases such as shown in the diagram to the right. Some waterfall models include variations of these […]
Waterfall is the classic highly-structured project management approach that dates back to antiquity and was common in software 10 – 20 years ago. Realizing the need for a process specific to data mining, CRISP-DM was defined in the late 1990s. Both approaches could be applied to data science. Waterfall, traditional software development life cycle (SDLC), and predictive […]