Topic 1 Question 146
You work on the data science team at a manufacturing company. You are reviewing the company’s historical sales data, which has hundreds of millions of records. For your exploratory data analysis, you need to calculate descriptive statistics such as mean, median, and mode; conduct complex statistical tests for hypothesis testing; and plot variations of the features over time. You want to use as much of the sales data as possible in your analyses while minimizing computational resources. What should you do?
Visualize the time plots in Google Data Studio. Import the dataset into Vertex Al Workbench user-managed notebooks. Use this data to calculate the descriptive statistics and run the statistical analyses.
Spin up a Vertex Al Workbench user-managed notebooks instance and import the dataset. Use this data to create statistical and visual analyses.
Use BigQuery to calculate the descriptive statistics. Use Vertex Al Workbench user-managed notebooks to visualize the time plots and run the statistical analyses.
Use BigQuery to calculate the descriptive statistics, and use Google Data Studio to visualize the time plots. Use Vertex Al Workbench user-managed notebooks to run the statistical analyses.
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コメント(5)
- 正解だと思う選択肢: B
Vote B. You can do all of the task in vertex AI workbench while minimizing computational resources.
👍 3imamapri2023/02/03 - 正解だと 思う選択肢: C
C. Use BigQuery to calculate the descriptive statistics. Use Vertex AI Workbench user-managed notebooks to visualize the time plots and run the statistical analyses.
BigQuery is a powerful data analysis tool that can handle massive datasets, making it an ideal solution for calculating descriptive statistics for hundreds of millions of records. It can also perform complex statistical tests for hypothesis testing. For time series analysis, using Vertex AI Workbench user-managed notebooks would be the best solution as it provides a flexible environment for data exploration, visualization, and statistical analysis. By using the two tools together, the data science team can efficiently analyze the sales data while minimizing computational resources. Its C not B
👍 3TNT872023/03/07 - 👍 1TNT872023/03/07
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