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2-Working-With-Data/06-non-relational/assignment.md
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## Instructions ## Instructions
The [Coco Cola Co spreadsheet](CocaColaCo.xlsx) is some missing calculations. Your task is to: The [Coca Cola Co spreadsheet](CocaColaCo.xlsx) is missing some calculations. Your task is to:
1. Calculate the Gross profits of FY '15, '16, '17, and '18 1. Calculate the Gross profits of FY '15, '16, '17, and '18
- Gross Profit = Net Operating revenues - Cost of goods sold - Gross Profit = Net Operating revenues - Cost of goods sold
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- Documentation on the [AVERAGE function](https://support.microsoft.com/en-us/office/average-function-047bac88-d466-426c-a32b-8f33eb960cf6) - Documentation on the [AVERAGE function](https://support.microsoft.com/en-us/office/average-function-047bac88-d466-426c-a32b-8f33eb960cf6)
1. This is an Excel file, but it should be editable in any spreadsheet platform 1. This is an Excel file, but it should be editable in any spreadsheet platform
[Data Source credit to Yiyi Wang](https://www.kaggle.com/yiyiwang0826/cocacola-excel) [Data source credit to Yiyi Wang](https://www.kaggle.com/yiyiwang0826/cocacola-excel)
## Rubric ## Rubric

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4-Data-Science-Lifecycle/14-Introduction/README.md
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### Managing Data ### Managing Data
As you work with data you may discover that some of the data needs to be cleaned using some of the techniques covered in the lesson focused on [data preparation](2-Working-With-Data\08-data-preparation) to build accurate models. When new data arrives, it will need some of the same applications to maintain consistency in quality. Some projects will involve use of an automated tool for cleansing, aggregation, and compression before the data is moved to its final location. Azure Data Factory is an example of one of these tools. As you work with data you may discover that some of the data needs to be cleaned using some of the techniques covered in the lesson focused on [data preparation](2-Working-With-Data\08-data-preparation) to build accurate models. When new data arrives, it will need some of the same applications to maintain consistency in quality. Some projects will involve use of an automated tool for cleansing, aggregation, and compression before the data is moved to its final location. Azure Data Factory is an example of one of these tools.
#### Securing the Data ### Securing the Data
One of the main goals of securing data is ensuring that those working it are in control of what is collected and in what context it is being used. Keeping data secure involves limiting access to only those who need it, adhering to local laws and regulations, as well as maintaining ethical standards, as covered in the [ethics lesson](1-Introduction\02-ethics). One of the main goals of securing data is ensuring that those working it are in control of what is collected and in what context it is being used. Keeping data secure involves limiting access to only those who need it, adhering to local laws and regulations, as well as maintaining ethical standards, as covered in the [ethics lesson](1-Introduction\02-ethics).
Here’s some things that a team may do with security in mind: Here’s some things that a team may do with security in mind:

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