Lab 4-2 Use PivotCharts to Visualize Declarative Data
Q1. Using UML diagram, identify which table(s) and attributes you will need to answer your initial question regarding the amount of products sold.
To answer the initial question of how many products were sold, we need the Sales Subset table with the Sales Order Quantity Sold and Product Code attributes. However, to determine areas that need improved pricing, marketing, and strategy, we need to bring in the FGI Product and Customer tables with the product description to identify target areas and specific product details. Q2. If the Sales Order Date datatype had imported as number, how might that cause a problem with our analysis if we wanted to dig into the data by month, for example?
If it had imported as a number, it would be a 5-digit number that we would not be able to recognize which month it was. The only way we can show the mm/dd/yyyy format is to import it
as text.
Q3. Why did your Sales Order ID attribute import as text when it looks like each field has numerical data in it? I used the Access Database file link given in the lab assignment and it did not import the data as text, but as a number instead. Would there be any benefit in Sales Order ID being stored as a number? There would be no benefit in having this stored as a number because the Sales Order ID field is simply a title or name given to each individual sales order to keep them separate but the numbers themselves have no value (they are not greater than or less than each other). Why will it not present a problem in our analysis to maintain these data as text?
Because the numbers in this field have no value, it doesn’t matter whether they are text or number as we are only looking to differentiate one sales order from another.
Q4. Identify two ways to improve this visual to make it more easily understandable?
Sorting the bars in descending (or ascending) order gives us a quick and easy view of the highest to lowest total sales of the product.
Adding labels (using show mark labels) to reflect the actual sales totals of each product on
the bars makes it easier to see the totals right away.
Q5. After creating these sheets and the dashboard, what additional data would you recommend that Slainte analyze? I would recommend that they analyze the total volume of products sold with the Product Sale Price to look at patterns of behavior or customer preferences in terms of the prices of the products. In other words, seeing if some prices are more popular than others in relation to the total products sold at those prices. What is another data visualization that would be helpful for Slainte’s decision making? I think a pie chart is a great visualization to help Slainte in their decision making. They could use it to compare the total products sold by either product description or by state to compare what percentage of the total sold was attached to each individual product (or state).
