Join Barton Poulson for an in-depth discussion in this video Data science without big data, part of Big Data Foundations: Techniques and Concepts.
- If you argue that big data requires…all of the three V's:…volume, velocity and variety at once…to count as big data proper…then it's entirely possible to be a data scientist.…A person with domain expertise…and statistical knowledge and encoding skills…without touching big data.…We'll look at a few of these possibilities.…First, let's review our Venn diagram of data science.…This again shows on the top right we have statistics,…on the bottom we have domain knowledge…and on the top we have coding.…
Taken together those class to data science.…We also have a Venn diagram for big data.…Where we have volume and velocity and variety,…and again, depending on who you ask…you need to have all three of them at once…to have big data.…So let's take a look at data science…for just one V at a time.…So we're talking about statistics…and domain knowledge encoding…but with just velocity or variety or volume.…The first example we want to look at is…volume of data…without any remarkable velocity or variety.…
So, this would mean a very large…
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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
What Is Big Data?
2. How Is Big Data used?
3. Big Data and Data Science
4. Ethics in Big Data
Challenges with anonymity5m 51s
5. Sources and Structures of Big Data
6. Storing Big Data
7. Preparing Data for Analysis
8. Big Data Analysis
Next steps1m 58s
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