Our 4 Blogs with Data Science viewpoints ranging from New-School Data Science to Old-School Statistics & Econometrics Have Answers, Questions, and Discussions:
1) For Businesses: A strategy to translate your valuable data into profitable insights, revenue-generating tactics, proactive forecasts, and real-time financial reporting. Synergistic data science uses methods from across sciences and industries, so you gain new customers, boost loyal customer spend, cut operational and marketing costs, improve employee motivation, and lower customer and employee turnover. Synergistic data science helps solve a variety of business problems better than the typically seen unidimensional approaches.
2) For Data Science Beginners & Pros: Leverages old-school and new-school approaches to create a diverse blend empowering better accuracy, robust consensus forecasts, and broader vision into Big Data science. Old-School practitioners learn how to begin using new-school data mining, machine learning, and AI to yield holistic “answer sets” instead of unidimensional answers. New-School practitioners learn science-based techniques to better analyze and clean datasets, map theory into improved hyperparameter tuning, and create consensus approaches that offer improved out-of-sample forecasts.
3) For Scientists: A practical process and methodology used to mix approaches from behavioral/business sciences with engineering/computer sciences. Using this powerful mixture, the synergistic approach to “data science” yields increased accuracy and robustness of results. Synergy leverages “hard science” techniques born from how objects behave and “soft science” techniques born from how people behave into cross-disciplinary breakthroughs. These approaches can be structured to apply to everything from markets and sociology to astronomy and meteorology. Synergy can embrace quantified or unquantified problems. The holistic methods include both stochastic and non-stochastic paths to an “answer set” that has measurably better accuracy than unidimensional techniques.
4) A Glossary of terms: Translates new-school terminology into old-school terminology and vice versa. Often we see that the same word is used differently between old and new.
NOTE: Some articles in each blog may be based on AI queries. We may have edited the AI response and used that as a post. In all cases, AI comments, posts, or quotes are sourced to AI. Large parts of the data scientist’s job will ultimately be performed by automated rule-based modeling systems. One reason this site exists is to provide input to such systems.
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Dr. Dean G. “Gordy” Fairchild (CEO, Synergy Data Science)
