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Overview
Data visualizations are a powerful tool used by auditors to perform risk assessments. Data is analyzed to look for anomalies. Typically, auditors import data from an Excel spreadsheet to produce the visualizations. For this activity we will use a Tableau screenshot of data visualization. To save time and focus on the analysis of data for auditing purposes, you will analyze data from the visualization rather than create actual data visualizations.
Directions
Open the screenshot of the Data Visualization provided in the
Supporting Materials
section below. The file will display data from an Excel spreadsheet, which has been transformed into a data visualization using Tableau software. Use the screenshot along with the Module Two Data Analytics Cash Data Set Excel spreadsheet in the Supporting Materials section to answer questions for each criterion.
Specifically, you must address the following:
- Examine expenditures to look for anomalies.Which day in March shows the largest amount of expenditure for the bank account ending in 4190?
- Examine transactions to identify transaction types.What type of transactions are paid through the bank account ending in 3176?
- Examine the interactive capability to analyze transaction amounts.What is the transaction amount for the commission occurred on March 4?
- Examine cash internal control to analyze internal controls for cash expenditures.When looking at the bank account ending in 3176, what is the largest daily expenditure in March 2019?Why do you think the expenditure is significantly larger compared to those on other days in March?
- Review auditing procedures to analyze weekend transactions. Hint: Use the Data Analytics Calendar in the Supporting Materials section to help you analyze the weekend transactions.What transactions do you observe over the weekends based on the total amount shown in the visualization or bank accounts ending in 4190?What might larger or smaller total amounts for the weekends indicate?
What to Submit
- A completed Module Two Data Analytics Activity Template using Microsoft Word.
Supporting Materials
The following resources support your work on the assignment:
- Module Two Data Analytics Cash Data Set (Excel file)
- Module Two Data Visualization Screenshot (Word file)
- Module Two Data Analytics Calendar
ACC 411 Module Two Data Analytics Activity Template
Directions: Complete this template by replacing the bracketed text with the relevant information.
Using the provided Data Visualization Screenshot and Data Analytics Cash Data Set, answer the following
questions for each criterion:
1. Examine expenditures to look for anomalies.
A. Which day in March shows the largest amount of expenditure for the bank account
ending in 4190?
[Add content here.]
2. Examine transactions to identify transaction types.
A. What type of transactions are paid through the bank account ending in 3176?
[Add content here.]
3. Examine the interactive capability to analyze transaction amounts.
A. What is the transaction amount for the commission occurred on March 4?
[Add content here]
4. Examine cash internal control to analyze internal controls for cash expenditures.
A. When looking at the bank account ending in 3176, what is the largest daily expenditure
in March 2019?
[Add content here.]
B. Why do you think the expenditure is significantly larger compared to those on other
days in March?
[Add content here]
5. Review auditing procedures to analyze weekend transactions.
A. What transactions do you observe over the weekends based on the total amount shown
in the visualization or bank accounts ending in 4190?
[Add content here]
B. What might larger or smaller total amounts for the weekends indicate?
[Add content here]
Question Five Hint: 3/2, 3/3, 3/9, 3/10, 3/16, 3/17, 3/23, 3/24 and 3/30, 3/31 are all weekends.
Data Analytics Cash Data Set
Trans_Date Amount
Bank Account
Type of Trasactions
1/1/2019
-13366 BOA-134579654190 purchases
1/1/2019
-10004 BOA-134579654190 purchases
1/1/2019
-11403 BOA-134579654190 purchases
1/1/2019
-25646 BOA-134579654190 purchases
1/1/2019
-10943 BOA-134579654190 purchases
1/1/2019
-15949 BOA-134579654190 purchases
1/1/2019
-8377 BOA-134579654190 purchases
1/1/2019
-19206 BOA-134579654190 purchases
1/1/2019
-17014 BOA-134579654190 purchases
1/1/2019
-27131 BOA-134579654190 purchases
1/1/2019
-10057 BOA-134579654190 purchases
1/1/2019
-15471 BOA-134579654190 purchases
1/1/2019
-1360 BOA-999078453176 travel expenses
1/1/2019
-19136 BOA-134579654190 purchases
1/1/2019
-866 BOA-999078453176 travel expenses
1/1/2019
-734 BOA-999078453176 travel expenses
1/1/2019
-25453 BOA-134579654190 purchases
1/1/2019
-23704 BOA-134579654190 purchases
1/1/2019
-10331 BOA-134579654190 purchases
1/1/2019
-5958 BOA-134579654190 purchases
1/1/2019
-16452 BOA-134579654190 purchases
1/1/2019
-1855 BOA-999078453176 travel expenses
1/1/2019
-16362 BOA-134579654190 purchases
1/1/2019
-17790 BOA-134579654190 purchases
1/1/2019
-5756 BOA-134579654190 purchases
1/2/2019
-3360 BOA-134579654190 purchases
1/2/2019
-10039 BOA-134579654190 purchases
1/2/2019
-15726 BOA-134579654190 purchases
1/2/2019
-13710 BOA-134579654190 purchases
1/2/2019
-9253 BOA-134579654190 purchases
1/2/2019
-22603 BOA-134579654190 purchases
1/2/2019
-2919 BOA-134579654190 purchases
1/2/2019
-604 BOA-999078453176 travel expenses
1/2/2019
-26864 BOA-134579654190 purchases
1/2/2019
-861 BOA-999078453176 travel expenses
1/2/2019
-16064 BOA-134579654190 purchases
1/2/2019
-17113 BOA-134579654190 purchases
1/2/2019
-3811 BOA-134579654190 purchases
1/2/2019
-452 BOA-999078453176 travel expenses
1/2/2019
-22126 BOA-134579654190 purchases
1/2/2019
-18328 BOA-134579654190 purchases
1/2/2019
1/2/2019
1/2/2019
1/2/2019
1/2/2019
1/2/2019
1/2/2019
1/2/2019
1/2/2019
1/2/2019
1/2/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
1/3/2019
-18254 BOA-134579654190
-19023 BOA-134579654190
-18240 BOA-134579654190
-24639 BOA-134579654190
-18998 BOA-134579654190
-17035 BOA-134579654190
-11367 BOA-134579654190
-6229 BOA-134579654190
-2891 BOA-134579654190
-16921 BOA-134579654190
-17693 BOA-134579654190
-16661 BOA-134579654190
-4376 BOA-134579654190
-17904 BOA-134579654190
-13928 BOA-134579654190
-9494 BOA-134579654190
-16235 BOA-134579654190
-23149 BOA-134579654190
-9571 BOA-134579654190
-24247 BOA-134579654190
-10523 BOA-134579654190
-26532 BOA-134579654190
-4078 BOA-134579654190
-26898 BOA-134579654190
-27034 BOA-134579654190
-6005 BOA-134579654190
-21059 BOA-134579654190
-924 BOA-999078453176
-7509 BOA-134579654190
-9181 BOA-134579654190
-14504 BOA-134579654190
-25099 BOA-134579654190
-4131 BOA-134579654190
-6573 BOA-134579654190
-9990 BOA-134579654190
-13528 BOA-134579654190
-7494 BOA-134579654190
-26924 BOA-134579654190
-25886 BOA-134579654190
-3404 BOA-134579654190
-6788 BOA-134579654190
-10808 BOA-134579654190
-15437 BOA-134579654190
purchases
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travel expenses
purchases
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purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
1/3/2019
1/3/2019
1/3/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/4/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
-1107 BOA-999078453176
-4901 BOA-134579654190
-19119 BOA-134579654190
-9712 BOA-134579654190
-17705 BOA-134579654190
-23847 BOA-134579654190
-13578 BOA-134579654190
-5893 BOA-134579654190
-25073 BOA-134579654190
-18714 BOA-134579654190
-17366 BOA-134579654190
-24461 BOA-134579654190
-456 BOA-999078453176
-20021 BOA-134579654190
-1689 BOA-999078453176
-13515 BOA-134579654190
-9628 BOA-134579654190
-17240 BOA-134579654190
-26375 BOA-134579654190
-2325 BOA-134579654190
-14774 BOA-134579654190
-8303 BOA-134579654190
-16064 BOA-134579654190
-18923 BOA-134579654190
-25947 BOA-134579654190
-2349 BOA-134579654190
-25772 BOA-134579654190
-6716 BOA-134579654190
-6254 BOA-134579654190
-4036 BOA-134579654190
-19372 BOA-134579654190
-22542 BOA-134579654190
-19626 BOA-134579654190
-16858 BOA-134579654190
-13051 BOA-134579654190
-25004 BOA-134579654190
-14065 BOA-134579654190
-950 BOA-999078453176
-16655 BOA-134579654190
-13292 BOA-134579654190
-24842 BOA-134579654190
-20010 BOA-134579654190
-21847 BOA-134579654190
travel expenses
purchases
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purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
travel expenses
purchases
travel expenses
purchases
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purchases
purchases
purchases
purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/5/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
-8379 BOA-134579654190
-6648 BOA-134579654190
-6300 BOA-134579654190
-6333 BOA-134579654190
-25383 BOA-134579654190
-14068 BOA-134579654190
-10810 BOA-134579654190
-3637 BOA-134579654190
-16481 BOA-134579654190
-19771 BOA-134579654190
-13795 BOA-134579654190
-14324 BOA-134579654190
-4837 BOA-134579654190
-5283 BOA-134579654190
-24558 BOA-134579654190
-25330 BOA-134579654190
-1587 BOA-999078453176
-3459 BOA-134579654190
-4395 BOA-134579654190
-19652 BOA-134579654190
-8815 BOA-134579654190
-10503 BOA-134579654190
-9441 BOA-134579654190
-11812 BOA-134579654190
-24790 BOA-134579654190
-10790 BOA-134579654190
-5158 BOA-134579654190
-27259 BOA-134579654190
-3305 BOA-134579654190
-15034 BOA-134579654190
-2688 BOA-134579654190
-25886 BOA-134579654190
-3834 BOA-134579654190
-24642 BOA-134579654190
-20468 BOA-134579654190
-13295 BOA-134579654190
-25492 BOA-134579654190
-23558 BOA-134579654190
-10801 BOA-134579654190
-4588 BOA-134579654190
-15238 BOA-134579654190
-20084 BOA-134579654190
-13435 BOA-134579654190
purchases
purchases
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purchases
purchases
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purchases
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purchases
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purchases
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purchases
purchases
travel expenses
purchases
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purchases
purchases
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/6/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/7/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
-20825 BOA-134579654190
-26929 BOA-134579654190
-26997 BOA-134579654190
-20211 BOA-134579654190
-23693 BOA-134579654190
-1941 BOA-999078453176
-8053 BOA-134579654190
-11714 BOA-134579654190
-26513 BOA-134579654190
-8945 BOA-134579654190
-13027 BOA-134579654190
-24130 BOA-134579654190
-22415 BOA-134579654190
-7415 BOA-134579654190
-13204 BOA-134579654190
-9751 BOA-134579654190
-8146 BOA-134579654190
-16878 BOA-134579654190
-17794 BOA-134579654190
-1711 BOA-999078453176
-12320 BOA-134579654190
-2609 BOA-134579654190
-3853 BOA-134579654190
-6861 BOA-134579654190
-19141 BOA-134579654190
-12863 BOA-134579654190
-1414 BOA-999078453176
-10707 BOA-134579654190
-11737 BOA-134579654190
-15282 BOA-134579654190
-25111 BOA-134579654190
-3715 BOA-134579654190
-11826 BOA-134579654190
-8551 BOA-134579654190
-5378 BOA-134579654190
-18641 BOA-134579654190
-6541 BOA-134579654190
-25867 BOA-134579654190
-10081 BOA-134579654190
-18305 BOA-134579654190
-13887 BOA-134579654190
-19041 BOA-134579654190
-18515 BOA-134579654190
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1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/8/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
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1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/9/2019
1/10/2019
1/10/2019
1/10/2019
1/10/2019
1/10/2019
1/10/2019
1/10/2019
1/10/2019
1/10/2019
-11470 BOA-134579654190
-2995 BOA-134579654190
-18590 BOA-134579654190
-22481 BOA-134579654190
-23821 BOA-134579654190
-22591 BOA-134579654190
-7775 BOA-134579654190
-12974 BOA-134579654190
-20137 BOA-134579654190
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-21459 BOA-134579654190
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-10222 BOA-134579654190
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-11558 BOA-134579654190
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-19129 BOA-134579654190
-5651 BOA-134579654190
-2910 BOA-134579654190
-24529 BOA-134579654190
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1/10/2019
1/10/2019
1/10/2019
1/10/2019
1/10/2019
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1/11/2019
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1/11/2019
1/11/2019
1/11/2019
1/11/2019
1/11/2019
1/11/2019
-6839 BOA-134579654190
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-11487 BOA-134579654190
-5154 BOA-134579654190
-26003 BOA-134579654190
-13245 BOA-134579654190
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1/13/2019
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1/14/2019
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1/16/2019
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1/18/2019
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1/20/2019
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1/24/2019
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1/26/2019
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1/27/2019
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1/29/2019
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1/31/2019
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2/7/2019
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2/24/2019
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2/25/2019
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3/8/2019
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3/9/2019
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3/11/2019
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3/12/2019
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3/14/2019
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3/16/2019
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3/18/2019
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3/20/2019
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3/20/2019
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3/20/2019
3/20/2019
3/20/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
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3/21/2019
3/21/2019
3/21/2019
3/21/2019
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travel expenses
purchases
travel expenses
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travel expenses
purchases
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travel expenses
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3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/21/2019
3/22/2019
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3/22/2019
3/23/2019
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3/23/2019
3/23/2019
3/23/2019
3/23/2019
3/23/2019
3/23/2019
3/23/2019
3/23/2019
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purchases
purchases
purchases
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purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
3/23/2019
3/23/2019
3/23/2019
3/23/2019
3/23/2019
3/23/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/24/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
-6252 BOA-134579654190
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purchases
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purchases
travel expenses
purchases
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travel expenses
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travel expenses
purchases
purchases
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purchases
purchases
purchases
travel expenses
purchases
purchases
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
3/25/2019
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3/25/2019
3/25/2019
3/25/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/26/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
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purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
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purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
purchases
purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/27/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
-18417 BOA-134579654190
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purchases
purchases
travel expenses
purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
travel expenses
travel expenses
purchases
purchases
purchases
purchases
purchases
purchases
travel expenses
purchases
purchases
purchases
purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/28/2019
3/29/2019
3/29/2019
3/29/2019
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3/29/2019
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3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
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3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
3/29/2019
-17809 BOA-134579654190
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purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
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purchases
purchases
purchases
purchases
purchases
purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
travel expenses
purchases
purchases
purchases
3/29/2019
3/29/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
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3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/30/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
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purchases
purchases
travel expenses
purchases
purchases
purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
travel expenses
purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
salary
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
3/31/2019
-22310 BOA-134579654190
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purchases
travel expenses
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
purchases
Module Two Data Visualization Screenshot
Di…
