Twelve Myths About Data Science (2017)
36mBeginner2017-01-10
Authors
Ben Sullins
Data Geek, Tech Consultant
Course details
In this course, Ben Sullins debunks 12 common misconceptions within the field of data science. Busy engineers, data miners, programmers, and other systems specialists who want to bolster their skills can benefit from Ben's succinct, practical insights. Separate data science fact from fiction, and learn what big data actually is, and why—contrary to what media coverage often suggests—it's not a singular thing. Ben also explains why big data can't instantly yield great insights, how to make analytics clearer, when to replace your relational databases, and more.
Skills covered
Data EngineeringData AnalysisData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOne-Off
Concepts
Introduction
- Welcome
Twelve Myths
- Big data will instantly yield great insights
- Big data will make analytics easier
- Big data will be easy to set up
- Big data will replace my relational databases
- Big data is one thing
- Big data is cheap
- Big data systems are fast
- Big data is the IT team's job
- My dev team shouldn't care about big data
- Big data can be handled by data scientists
- Big data will eliminate the need for X
- Big data is necessary
Conclusion
- Next steps