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Scenario:
As a Business analyst of the Pacifica Company, I want to analyze online sales data for Ohio, Pennsylvania, and New York State to understand:
- How the company is growing
- Discover similarities or differences between product families and regions
- Understand the reason for any discrepancies
In this demo session, you will perform the following exercises within SAP BusinessObjects Cloud
* Disclaimer:
- For the best experience, please use Google Chrome and refrain from using the "Upload File" functionality
- At this time, there is no geo enabled dimension in this demo. To experience the geospatial functionality please see this demo.
- When logging in for the first time and choosing a new password, the password must have at least eight characters and contain the following character types: at least one uppercase, at least one digit, and lowercase.
Let's get started!
Log on to SAP Business Objects Cloud with the log in information you were provided. If you don't have the log in information, you can request an invite here. |  |
| The application provides you with additional tool tips to get started easily. You can choose to keep this turned on or turn it off at any point of the demo. |  |
Get familiar with the home screen. It gives you an overview of the actions you can take Note : Based on the account permission setting only a limited set of actions might be available. |  |
| You like to continue the analysis you started last time. Navigate to the menu on the top left corner and select "Stories" |  |
| Open the "Pacifica Sales Demo" story under the "All" tab. |  |
The story will open. As you only have read rights, use the "Save As" option to create your own copy of the document. |  |
Please include your name in the new story title - Example: Pacifica Sales Demo - YourName. Click "OK" to save the story. |  |
| Adding a new chart. Let's add a few more visualizations that show the "Sales Revenue" and "Gross Margin %" per product. |  |
| Select the "Pacific_Sales" model for the chart |  |
A blank chart will be added to the story dashboard. Note: Depending on space, the blank chart will pop up anywhere on the dashboard. You can later position it as needed. The Builder menu should be visible on the right side. |  |
Under Axis 1, select "Sales Revenue as the measure. Under Categories, select "Product" as the dimension. |   |
In the "BUILDER" option, select color to add the desired palette. Note: for this demo, there is only one choice. |  |
| Currently the chart is hard to read. Resize it to make it fit about half of the bottom page. |  |
Now, let's filter the chart to only show the 2015 data. Go back to "BUILDER". Under Filters, add Time filter to filter the objects. Data can be filtered for a specific time range (Filter by Range) or for a specific Year (Filter by Member). As we want to see only the 2015 data let's filter by member. |  |
| Under "(all)" Select "2015" and click "Ok". |  |
You like to create another chart showing the Gross Margin % per product. As the chart is similar to the one just created, we can copy and paste to create the same chart and change the measure. Select the chart and use Ctrl+C to copy and then Ctrl+V to paste the chart. Resize as needed. |  |
Select the chart. Under Axis 1, remove "Sales Revenue" and then add "Gross Margin %". Note: The category still remains the same as we want to see Gross Margin % per product. |  |
You like to make sure that when the bottom two charts (which you just created) are filtered, that filter is also applied to the entire page, instead of just the selected chart. Go back to menu in the top right corner and in the drop down select "Linked Analysis. Then select "Entire story + This chart" under "Chart interactions apply to:" Note: Change the settings for "Sales Revenue per Product" chart, which is the one we will be working on |   |
Click on the "Sales Revenue per Product" chart. Single click on the "Accessories" bar will give you the filter options. Select "Drill Down" from the options. |  |
| See how a story filter token was applied and the bottom right chart was drilled down to just "Accessories" and all other charts are also filtered down. |  |
After viewing the data, remove the "Product" filter. Click on the "Filter" icon at the top and deselect the "Product" filter. |  |
Furthermore, you would like to add a visualization that shows you the "Sales Revenue" and Gross Margin % per Location. Add a new page and select "Canvas". Add a new chart. Select the "Pacifica_Sales" model for the chart and click "Ok". |    |
A blank chart is dropped. Select "Gross Margin %" and "Location" to create a default chart. |   |
You can also change the chart type. Under "BUILDER" panel, select "CHART TYPE" You would like to see the data in a tabular view. From the drop down select the chart type as table. |   |
| Re-size the chart to fit the table. |  |
Ohio is having the lowest Gross Margin %. You know that discounts have an effect on the Gross Margin %, hence you would like to add Discount % to the table. Use the side panel (click "Add Another Measure") to add Discount % to the chart. |   |
You can see that Ohio has the highest Discount %. You wonder how many coupons are being accepted at this location. Your data-set does not have this information. Hence you would like to blend the data from a different data-set into this one. Open the "Link Dimensions" in the top left corner. Add the "Coupon_Usage" model. Link "Location" under both models. Click "SET". |      |
Select the chart and add a new measure. Now in addition to the measures from the sales data-set, you also have the measures from the Coupon_Usage data-set available. Select Coupon_usage dataset under Data Source. Now you can see additional values from the Coupon_Usage dataset. Add "No of Used Coupon" to the chart. The chart now has the "No. of used Coupon" value from the three areas. From the table you can see that New York State has the highest usage of coupons but Ohio has the highest Discount % which effects the Gross Margin %. |    |
The same information regarding coupon usage can be seen in another way. Add a visualization from the Coupon_Usage data-set to find out how coupons have been used. Add a new chart. Select the "Coupon_Usage" model for the chart. |   |
A blank chart was created. Add No of Coupons and Coupon Type to the chart. Re size the chart to fit the canvas. |  |
So far, we can still view the table that we have created on this page. This time you want to focus on the chart that you just created. Select the "Zoom in" option to enlarge the chart. You want to focus in on 40%, 50%, and 60% coupons. Select these values by clicking on them. Then use the filter option to focus just on these discount values. |    |
Next, add location to the categories to see the distribution of the high discount coupons. This very basic analysis shows that most of the High Discount coupons are being used in the Ohio state |  |
Next you would also like to see who the top Sales Managers are in your region. As this task is not related to the one you were working on till now, you would like to see this on a new page. Create a new canvas page. Add a new chart. Select the "Pacifica_Sales" model for the chart. |    |
A new chart was placed. Add "Sales Revenue" under Axis 1 and "Sales Manager" under Categories. Expand the chart to fit the canvas. You like to sort the chart. Select the sorting icon on the right side of the chart and sort by "Highest to Lowest". |    |
| The Sales Manager performance chart is of interest to you, hence you would like to pin it onto your homepage. |  |
You like to rename the new pages. Go to "Settings" menu and open "Maintain Pages". Rename page 2 to "Location" and page 3 to "Sales Managers". Click "Ok". |    |
| Save the story. |  |
Plan Your Business - Grid Functionality In this section, you will find out another way to explore the dataset further. Add a new page and select Grid (beta). |  |
Add a Dynamic Table to the Grid. Select Pacifica_Sales as the data model. |   |
A table is added to the grid with Actual and Forecast categories. Under Accounts, you can see all the measures within the Pacifica_Sales dataset. |  |
You would like to know what the Sales Revenue per Location is. Click on Designer tab in the top right corner to bring up the Builder panel With the table selected, within the Builder panel, click on the icon to add a dimension. |   |
Drag the dimension Location from the Dimensions column to the Rows column Click OK. |   |
Depending on how you placed Location relative to Account, you can get two different Table views. For this walkthrough, we went with the second view where Location was placed under Account. This way you can see Sales Revenue for each region. |  |
Select the Actual Sales Revenue for each region and then click on Examine to create a chart. A default chart is show based on your data selection and data visualization best practices. |   |
You can change the default chart to other chart types. Click on Bar/Column in the top right corner within the chart to view a drop down of all available charts. |   |
| If you are happy with the chart you have created, you can copy it to the new page. |   |
Thank you!
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