Cognos Analytics

Coffee shop sample data (11.1.3+)

By Business Solutions posted Fri July 12, 2019 08:52 AM

  

In IBM Cognos Analytics 11.1.3, a new set of dashboards were added to the Base Samples to illustrate a retail coffee chain.

We have created sample data for a fictional coffee shop chain with three locations in New York city. The chain has purchased IBM Cognos Analytics to identify factors that contribute to their success, and ultimately to make data-informed decisions.

Amber and Sandeep are the co-founders of the coffee chain. They uploaded their data in a series of spreadsheets and created a data module. From that data, they designed an operations dashboard and a marketing dashboard.

Inventory

Amber and Sandeep have created two dashboards and one data module that is based on nine spreadsheets:

  • Coffee operations: This sample dashboard demonstrates operational data from a fictional coffee chain. Location: Team content > Samples > Dashboards.
  • Coffee marketing: This sample dashboard demonstrates marketing data from a fictional coffee chain. Location: Team content > Samples > Dashboards.
  • Coffee sales and marketing: This sample data module contains representative retail data from a fictional coffee chain. Location: Team content > Samples > Data.
  • April Sales.zip: This sample data contains representative retail data from a fictional coffee chain. This ZIP file contains nine related CSV files. Location: Team content > Samples > Data > Source files > Retail.

Data

The sample data module named Coffee sales and marketing can be found in Team content > Samples > Data. There are nine tables:

  • Sales Receipts
  • Pastry Inventory
  • Sales Targets
  • Customer
  • Dates
  • Product
  • Sales Outlet
  • Staff
  • Generation

Use Cases

Amber uses the Coffee operations dashboard to view high-level metrics for her three stores:


To determine which beverages are not selling as well as others, in the Sales by Category visualization, Amber drills down on Beverages (right-clicks the Beverages|Coffee square and Drill down in the context toolbar. She drills down again on Coffee | Barista Espresso to see that Ouro Brasileiro Shot is selling poorly (it is the smallest box):


When Amber interacts with this visualization, all the other visualizations (except Spoilage By Type) are filtered by her actions.

 

Switching gears, Amber decides to study spoilage. In the Spoilage By Type visualization, Amber sees that Scones have the highest spoilage. She right-clicks Scone in the legend, clicks Navigate in the context toolbar, and selects Product. She can clearly see that Ginger Scones have the highest spoilage:

Amber shares her findings with Sandeep, and they decide to test a new promotion at one of their locations where they pair up an Ouro Brasileiro shot and a ginger scone for a special price. They create a new dashboard named Coffee marketing to track the promotion’s progress:

After a week, Amber and Sandeep see that the sales for both products have increased:

They can also see that spoilage for ginger scones has decreased:

So as you can see, Amber and Sandeep now have excellent visibility into how their business is performing, and are able to easily create new assets for themselves.




Related posts:


Other samples:
Base Samples | Extended Samples | JavaScript | Themes and Extensions | Audit Reporting | OLAP | Package Based Drill-Through | Legacy | 10.2.2 Cognos Mashup Services (CMS) | Notebooks



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