Answers to Questions on Data Science (Quora)
Quora (https://www.quora.com/) is a great platform to get direct answers from global voices on a broad range of topics.
Over the past five years I have posted a number of answers to questions concerning data science:
- How do data scientists build trust in their work with their business partners?
- If a data scientist spends 90% of their effort on data preprocessing, why do all courses focus mostly or solely on models?
- Is there a growing concern in the data science community that models can be hacked or gamed?
- Do we need more data or more science in data science?
- What are some alternative and contrasting definitions of feature engineering in machine learning?
- Which is the older methodology for data mining crisp DM or Semma?
- What are the common pitfalls to avoid in picking data science roles?
- Is the normalization part of the process of feature engineering?
- What are the basics to learn in statistics for data analytics?
- How can AI predict personality traits from everyday digital plain text journal datasets?
- How can I move from information security to the data science domain?
- Should I first deal with the outliers and then perform the data transformation (imputing, scaling, etc.) or the other way around?
- As a data scientist or enthusiast, do you participate in data science competitions to show your skill to the world?
- As a data scientist, how would you explain the confusion matrix to a marketing manager?
- Who has more chance of getting a job comfortably, data science generalists or data science specialists?
- Which is the best outlier detection technique in data science?
- How do I improve cybersecurity with data science?
- How would you describe what a data scientist does in equation form?
- What is the most difficult to find attribute in a good data scientist?
- Is it tough to get into data science? How can I land my 1st job in data science?
- As a data scientist, what are some common misconceptions about what you actually do?
- Is Big Data just glorified statistics?
- Why are support vector machines less famous than neural networks?
- Is data science difficult?
- What are the most interesting findings based on data analytics in your field of work or interest?
- What do people put on data science resumes that they think will give them an advantage, but in fact are either irrelevant or actually harming their chances?
- How do data scientists cause themselves needless pain?
- How do you Learn Data Science If You’re Broke?
- What exactly machine learning engineers don’t know about data scientists?
- I’m 75, is it too late to start learning Data Science?
- As a data scientist, what bothers you about how your field is portrayed in the press?
- Which data management system is the most suitable one for big data and data science projects?
- As a Data Science student, what can I do in this year to increase my chances of finding a career in this field?
- What is the difference between classification and clustering in a data mining environment?
- What’s the most humbling thing you’ve seen a data scientist do?
- As a data scientist, have you ever had to label data in order to solve a problem at work?
- As a data scientist, how do you feel about the fact that a very large part of your technical work has to do with data pre-processing (collection, cleaning etc)?
- How can I analyse the data I collected from the interview method of research?
- Can a machine learning engineer work in the job profile of a data scientist?
- What is the most fascinating research being done in data science?
- As a Data scientist, which field of data science do you use the most in your work?
- Who “invented” data science as a distinct subject from machine learning and statistics?
- What are the various ways to tune data before we prepare the model?
- In the next decade or two, will the development of AI prevent data science/quantitative analytics from being viable career paths for humans?
- Why have we not been able to find a perfect data structure, that does not need mining?
- How do you create an application without knowledge of data science, such that you’re able to analyze data points in retrospect?
- What are the intersections between the fields of data science and complex systems?
- Between Data Analytics and JavaScript, which skill is more valuable and why? If you had to study one of them, which one would you choose?
- What is the difference between Data Analytics, Data Analysis, Data Mining, Data Science, Machine Learning, and Big Data?
- How do you judge a good Data scientist with just 5 questions?
- What are concrete examples of Data Scientist missions within companies?
- What is a math intensive data mining topic that I can use for my senior research project?
- What steps do you follow to validate your data analytics models?
- How often do data scientists give presentations?
- Data Science: How can I best calculate the impact of a deal being ran on Amazon?
- What are the steps to become a data scientist from easiest to hardest?
- How would you suggest to a franchise where to open a new store?
- Why are startup companies not using SAS?
- Do Data Scientists use different programming languages for different tasks?
- What areas of data science or machine learning are growing in importance?
- Which companies are considered dream companies for data scientists and data engineers to work for?
- How important are social skills for a Data scientist?
- How would a data scientist solve this business problem?
- Why do most data scientists have out-dated skills from the 90s?
- What is the future of data analysis?
- What are the most valuable skills to learn for a data scientist now?
- How much does actually knowing statistics/ML matters for a data scientist who wants to get paid?
- Why don’t data scientists make higher salaries than software engineers?
Analytics Methods
SCTR7: Data Science and Analytics 
May 15, 2020 at 08:48
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