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Exploring NCAA Data with BigQuery
BigQuery is Google's fully managed, NoOps, low-cost analytics database. With BigQuery you can query terabytes and terabytes of data without managing infrastructure or needing a database administrator. BigQuery uses SQL and takes advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
We have a newly available dataset for NCAA Basketball games, teams, and players. The game data covers play-by-play and box scores back to 2009, as well as final scores back to 1996. Additional data about wins and losses goes back to the 1894-5 season in some teams' cases.
In this Google Cloud Lab, we will find and query the NCAA dataset using BigQuery.
Note: you will have timed access to the online environment. You will need to complete the lab within the allotted time.
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| Rating | Not enough ratings |
|---|---|
| Length | 2 weeks |
| Effort | 45 minutes |
| Starts | Jan 24 (117 weeks ago) |
| Cost | $10 |
| From | Google Cloud via Coursera |
| Instructor | Google Cloud Training |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science |
| Tags | Data Science Data Analysis |
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| Rating | Not enough ratings |
|---|---|
| Length | 2 weeks |
| Effort | 45 minutes |
| Starts | Jan 24 (117 weeks ago) |
| Cost | $10 |
| From | Google Cloud via Coursera |
| Instructor | Google Cloud Training |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science |
| Tags | Data Science Data Analysis |
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