Data Science Methodology: Best Practices for Successful Implementations
Marian University will be offering a degree program in Business Analytics starting Fall 2016. Many of our new courses draw heavily from Data Science. In the domain of Data Science, solving problems and answering questions through data analysis is standard practice. Often, data scientists construct a model to predict outcomes or discover underlying patterns, with the goal of gaining insights. Organizations can then use these insights to take actions that ideally improve future outcomes.
The flow of methodology illustrates the iterative nature of the problem-solving process. As data scientists learn more about the data and the modeling, they frequently return to a previous stage to make adjustments, iterate quickly and provide continuous value to the organization. Models are not created once, deployed and left in place as is; instead, are continually improved and adapted to evolving conditions.
You can download the White Paper here: https://form.jotformeu.com/61126366826357
Sources: Data Science Central, IBM
The flow of methodology illustrates the iterative nature of the problem-solving process. As data scientists learn more about the data and the modeling, they frequently return to a previous stage to make adjustments, iterate quickly and provide continuous value to the organization. Models are not created once, deployed and left in place as is; instead, are continually improved and adapted to evolving conditions.
You can download the White Paper here: https://form.jotformeu.com/61126366826357
Sources: Data Science Central, IBM
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