Similarities and Differences between ML and Analytics - Rishabh Bhargava

We talked about:

• Rishabh's background
• Rishabh’s experience  as a sales engineer
• Prescriptive analytics vs predictive analytics
• The problem with the term ‘data science’
• Is machine learning a part of analytics?
• Day-to-day of people that work with ML
• Rule-based systems to machine learning
• The role of analysts in rule-based systems and in data teams
• Do data analysts know data better than data scientists?
• Data analysts’ documentation and recommendations
• Iterative work - data scientists/ML vs data analysts
• Analyzing results of experiments
• Overlaps between machine learning and analytics
• Using tools to bridge the gap between ML and analytics
• Do companies overinvest in ML and underinvest in analystics?
• Do companies hire data scientists while forgetting to hire data analysts?
• The difficulty of finding senior data analysts
• Is data science sexier than data analytics?
• Should ML and data analytics teams work together or independently?
• Building data teams
• Rishabh’s newsletter – MLOpsRoundup

Links:

• https://mlopsroundup.substack.com/
• https://twitter.com/rish_bhargava

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