Difference between revisions of "IS428 2016-17 Term1 Assign3 Liang Bing"
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For the prox data table, I trim the employee Id out from their prox card id. | For the prox data table, I trim the employee Id out from their prox card id. | ||
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+ | After that, I used '''"VlookUp"''' formula to look for the employee Id from the employee List.xlsx in order to pair up employees' record and the employees' respective office and their department. For example, the employee whose employee ID is vawelon is in office 1070 and is belongs to the facilities department. | ||
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− | + | I have also created one more field to extract the floor which the employees' office located. | |
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+ | [[File:VA3 LB dataManu6.png]] | ||
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+ | Moreover, the data collected from mobile robots and the data collected from fixed prox card readers have different ways to express their locations. i.e. the mobile robots use the coordinate (x,y) for their location when a reading was recorded, while the fixed reader use the zone for their location. This made it inconvenient to combine the mobile readers' data and the fixed readers' data for a overall visualization of the employees' activities. Therefore, it is either the fixed readers should have the x,y data or the mobile readers should have the zone it is located in order to ensure the 2 set of data being matched. | ||
− | + | I chose to assign | |
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==Task 1== | ==Task 1== |
Revision as of 13:10, 22 October 2016
Data Exploration & Data Manipulation
The Employee List.xlsx data file does not provide enough insights by itself. Since the prox data detected by the sensors were collected from these employee's card, it makes more sense to combine employees' information with the prox sensor data so they together provide more information.
To integrate the Employee List.xlsx file and the other two sensor data files, I used Microsoft Excel.
The prox ID contains the employees' names and a 3 digits number starts with "00". I created a new column in Employee List.xlsx to store the employees' prox ID without the 3 digits number, this is done by combining the first letter of the employees' last name and the employee's first name.
For the prox data table, I trim the employee Id out from their prox card id.
After that, I used "VlookUp" formula to look for the employee Id from the employee List.xlsx in order to pair up employees' record and the employees' respective office and their department. For example, the employee whose employee ID is vawelon is in office 1070 and is belongs to the facilities department.
I have also created one more field to extract the floor which the employees' office located.
Moreover, the data collected from mobile robots and the data collected from fixed prox card readers have different ways to express their locations. i.e. the mobile robots use the coordinate (x,y) for their location when a reading was recorded, while the fixed reader use the zone for their location. This made it inconvenient to combine the mobile readers' data and the fixed readers' data for a overall visualization of the employees' activities. Therefore, it is either the fixed readers should have the x,y data or the mobile readers should have the zone it is located in order to ensure the 2 set of data being matched.
I chose to assign
Task 1
What are the typical patterns in the prox card data? What does a typical day look like for GAStech employees?
Floor 2 has more employees than that of Floor 1 and 3
Task 2
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.
Task 3
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.
Task 4
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.