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Relying on intuitions and drawing conclusions is not your sole job as a data engineer/scientist. You must learn to understand the "why" and "how" of your intuitions, and tie it up with evidence.
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🤓"Errors using inadequate data are much less than those using no data at all"
- Charles Babbage, Inventor and Mathematician
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✅ Here are some popular myths and facts about Data Science you didn't know.
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👉 “A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.”. ��
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The strength of a hypothesis depends on the number of facts it covers.
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I just released a New video on the #DataProfessor #YouTube channel: Quotes #4 on Big Data and Data Science
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I just released a New video on the #DataProfessor #YouTube channel: Quotes #3 on Big Data and Data Science
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I just released a New video on the #DataProfessor #YouTube channel: Quotes #3 on Big Data and Data Science
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I just released a New video on the #DataProfessor #YouTube channel: Quotes on Big Data and Data Science (Part 2) https://t.co/Ooum6qoouM
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I just released a New video on the #DataProfessor #YouTube channel: Quotes on Big Data and Data Science (Part 1: Quotes 1-10) https://t.co/ZreQiqKu37
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“Without a grounding in statistics, a Data Scientist is a Data Lab Assistant.”
- Martyn Jones
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“Being a data scientist is not only about data crunching. It’s about understanding the business challenge, creating some valuable actionable insights to the data, and communicating their findings to the business.”
―Jean-Paul Isson
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A data scientist is a person who is better at statistics than any software engineer and is better in software engineering than any statistician.
Josh Wills
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