Difference between revisions of "IS428 2016-17 Term1 Assign3 Jonathan Eduard Chua Lim"
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#Describe up to five observed relationships between the proximity card data and building data elements. If you find a causal relationship (for example, a building event or condition leading to personnel behavior changes or personnel activity leading to building operations changes), describe your discovered cause and effect, the evidence you found to support it, and your level of confidence in your assessment of the relationship. | #Describe up to five observed relationships between the proximity card data and building data elements. If you find a causal relationship (for example, a building event or condition leading to personnel behavior changes or personnel activity leading to building operations changes), describe your discovered cause and effect, the evidence you found to support it, and your level of confidence in your assessment of the relationship. | ||
| − | == HVAC Information and its Significance== | + | ==HVAC Information and its Significance== |
==Data Cleaning== | ==Data Cleaning== | ||
| − | == == | + | ==Findings: What are the typical patterns in the prox card data? What does a typical day look like for GAStech employees?== |
| − | == == | + | ==Findings: Describe up to ten of the most interesting patterns that appear in the building data. Describe what is notable about the pattern and explain its possible significance == |
| − | == == | + | ==Findings: Describe up to ten notable anomalies or unusual events you see in the data. Prioritize those issues that are most likely to represent a danger or a serious issue for building operations.== |
| + | ==Findings: Describe up to five observed relationships between the proximity card data and building data elements. If you find a causal relationship (for example, a building event or condition leading to personnel behavior changes or personnel activity leading to building operations changes), describe your discovered cause and effect, the evidence you found to support it, and your level of confidence in your assessment of the relationship.== | ||
| + | ==Visualisations== | ||
| + | |||
==Tools used== | ==Tools used== | ||
| + | |||
==References== | ==References== | ||
| + | |||
==Comments and Feedback== | ==Comments and Feedback== | ||
Revision as of 21:04, 20 October 2016
Contents
- 1 Problem and Motivation
- 2 Questions
- 3 HVAC Information and its Significance
- 4 Data Cleaning
- 5 Findings: What are the typical patterns in the prox card data? What does a typical day look like for GAStech employees?
- 6 Findings: Describe up to ten of the most interesting patterns that appear in the building data. Describe what is notable about the pattern and explain its possible significance
- 7 Findings: Describe up to ten notable anomalies or unusual events you see in the data. Prioritize those issues that are most likely to represent a danger or a serious issue for building operations.
- 8 Findings: Describe up to five observed relationships between the proximity card data and building data elements. If you find a causal relationship (for example, a building event or condition leading to personnel behavior changes or personnel activity leading to building operations changes), describe your discovered cause and effect, the evidence you found to support it, and your level of confidence in your assessment of the relationship.
- 9 Visualisations
- 10 Tools used
- 11 References
- 12 Comments and Feedback
Problem and Motivation
Questions
As an expert in visual analytics, you have been hired to help GAStech understand its operations data. In this assignment, you are given two weeks of building and prox sensor data. Can you use visual analytics to identify typical patterns of and issues of concern?
You will be asked to answer the following types of questions:
- What are the typical patterns in the prox card data? What does a typical day look like for GAStech employees?
- Describe up to ten of the most interesting patterns that appear in the building data. Describe what is notable about the pattern and explain its possible significance.
- Describe up to ten notable anomalies or unusual events you see in the data. Prioritize those issues that are most likely to represent a danger or a serious issue for building operations.
- Describe up to five observed relationships between the proximity card data and building data elements. If you find a causal relationship (for example, a building event or condition leading to personnel behavior changes or personnel activity leading to building operations changes), describe your discovered cause and effect, the evidence you found to support it, and your level of confidence in your assessment of the relationship.
