Join Barton Poulson for an in-depth discussion in this video Types and skills in data science, part of Big Data Foundations: Techniques and Concepts.
When people talk about big data in newspaper articles…or professional conferences, it's easy to get the idea…that data scientists are not just people…who have domain expertise,…who understand statistics and can program.…Instead, they often start to sound like omnicient…and omnipotent super humans who can do anything…and do it instantly and effortlessly.…Of course, it's not the real picture.…As with any other domain there is a large range of skills…involved in data science beyond the three mentioned earlier.…A great report called, "Analyzing the Analyzers:…"An Introspective Survey of Data Scientists and Their Work"…goes over this in detail.…
It's a short 40-page book by Harlan Harris, Sean Murphy…and Marck Vaisman that was published…by O'Reilly Media in 2013.…It's available in print or as a free e-book…from O'Reilly or Amazon.…In it, the authors surveyed about 250…data science practitioners.…They asked them how they identified themselves…and how they clustered skills…that are relevant to data science.…Each of these classifications was then subject to…
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- What makes big data "big"
- Understanding how big data impacts consumers, businesses, and research
- Exploring the intersection of data science and big data
- Facing big data's ethical challenges
- Understanding the sources and structures of big data
- Storing big data
- Prepping big data for analysis
Skill Level Beginner
Duration
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Introduction
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Welcome1m 13s
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What Is Big Data?
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2. How Is Big Data used?
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3. Big Data and Data Science
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4. Ethics in Big Data
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Challenges with anonymity5m 51s
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5. Sources and Structures of Big Data
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Machine-generated data4m 20s
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Structured data2m 47s
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Unstructured data5m 50s
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6. Storing Big Data
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7. Preparing Data for Analysis
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Challenges with data quality3m 38s
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Additional Vs of big data4m 41s
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8. Big Data Analysis
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Predictive analytics5m 20s
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Big Data Visualization4m 17s
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Conclusion
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Next steps1m 58s
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Video: Types and skills in data science