Difference between revisions of "IISSS608 2017-18 T3 Assign Vigneshwar Ramachandran Vadivel- Data Cleaning"
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<ul>Once we transform our data we can explore the communication pattern and growth of the company with this merged dataset. | <ul>Once we transform our data we can explore the communication pattern and growth of the company with this merged dataset. | ||
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=<div style="font-family: Courier;">Aggregated Suspicious Communication Data= | =<div style="font-family: Courier;">Aggregated Suspicious Communication Data= | ||
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− | To create the edges csv file: | + | To create the edges csv file:<br> |
1. Concatenate communication data for all different transactions into one source of information.<br> | 1. Concatenate communication data for all different transactions into one source of information.<br> | ||
2. Change column data type of "From" and "To" from continuous to nominal.<br> | 2. Change column data type of "From" and "To" from continuous to nominal.<br> | ||
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6. Use the tabulate function to count the number of times the concatenated cell appears in the column - this helps to find out the weight of the unique direction of communication.<br> | 6. Use the tabulate function to count the number of times the concatenated cell appears in the column - this helps to find out the weight of the unique direction of communication.<br> | ||
7. Update the table with the weight of the column. Change the column name to "Weight".<br> | 7. Update the table with the weight of the column. Change the column name to "Weight".<br> | ||
− | To create the nodes csv file: | + | To create the nodes csv file:<br> |
1. Merge the company index with the combined file together and find out the unique nodes present in the edges csv file.<br> | 1. Merge the company index with the combined file together and find out the unique nodes present in the edges csv file.<br> | ||
2. Name the column "id", so that Gephi can detect the ids of the nodes.<br> | 2. Name the column "id", so that Gephi can detect the ids of the nodes.<br> | ||
3. Add the label as name of the employee involved in the transaction.<br> | 3. Add the label as name of the employee involved in the transaction.<br> | ||
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Revision as of 10:08, 3 July 2018
Communication Data
Using Tableau prep all the four data can be merged and transformed into our necessary format.
The date format of the data has been given in Unix epoch timestamp beginning from May 11, 2015 at 14:00. To transform this into our timestamp value we can derive the following calculated field
Network Data
- Once we transform our data we can explore the communication pattern and growth of the company with this merged dataset.
For our later part of the analysis the data has to be transformed in such a way that it would be readable on Gephi for basic network visualisations. Using the insider kasios suspicious data, I
The following flow shows the data processing involved in this process using Tableau prep,
Aggregated Suspicious Communication Data
To create the edges csv file:
1. Concatenate communication data for all different transactions into one source of information.
2. Change column data type of "From" and "To" from continuous to nominal.
3. Rename columns "From" and "To" to "Source" and "Target".
4. Create a column "Type" and ensure that all the fields of the column are filled with "Directed" - This helps to specify the direction of the communication.
5. Create a new column with the formula "Source || Target", as this concatenates the Source and Target column.
6. Use the tabulate function to count the number of times the concatenated cell appears in the column - this helps to find out the weight of the unique direction of communication.
7. Update the table with the weight of the column. Change the column name to "Weight".
To create the nodes csv file:
1. Merge the company index with the combined file together and find out the unique nodes present in the edges csv file.
2. Name the column "id", so that Gephi can detect the ids of the nodes.
3. Add the label as name of the employee involved in the transaction.