Given the size of data sets, big data project frequently focus on machine-driven data mining techniques, which automate much of the discovery process in analysis.
- [Instructor] Back several generations in my family tree, … I have some ancestors who were miners. … They would go down to work in the mines early Monday morning … and wouldn't come back up until Saturday night, … it was backbreaking and lung blackening work … that I'm grateful I would never have to do, … but to be perfectly clear, … that's not what we're talking about … when we're talking about data mining, … rather data mining is the practice … of working with large datasets … to find potentially valuable insight. … Think of it this way, computer algorithms, … especially deep learning neural networks … are able to go through millions of images … and automatically identify all of the pictures … with cats in them and show you where the cats are, … they draw the frame around them. … Data mining's a little like that, … but instead of finding cats, … maybe you're trying to find new customers, … or new treatments for diseases, … or students with exceptional potential, … really anything that's important to you …
Author
Barton Poulson
Released
9/19/2019- Identify the components that make up big data.
- Examine how big data has grown over the last few years.
- Explain the importance of using big data in business organizations.
- Distinguish between knowledge requirements for using big data and for understanding data science.
- Justify the need for training on big data within an organization.
- Analyze the factors that go into utilizing big data on a project.
- Differentiate outcomes that are derived from big data from outcomes that are derived from observing behaviors.
Skill Level Beginner
Duration
Views
-
Introduction
-
How big data shapes AI1m 46s
-
-
1. Defining Big Data
-
2. How Is Big Data Used?
-
Big data for applications4m 41s
-
3. Big Data and Data Science
-
4. Ethics in Big Data
-
Big data and privacy5m 52s
-
Data governance6m 2s
-
-
5. Data Logistics
-
An evolving data landscape5m 48s
-
6. Analyzing Big Data
-
Visualizing big data5m 13s
-
Data mining4m 39s
-
Text analytics4m 18s
-
Sentiment analysis4m 48s
-
Predictive analytics4m 7s
-
Anomaly detection3m 59s
-
Conclusion
-
Next steps2m 56s
-
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.
Share this video
Embed this video
Video: Data mining