Discover data

Outdoor Sports is a worldwide company that distributes outdoor materials for people who love to practice sports in nature. Although it was a small company created in the United States, the quality of their products established a strong position in the market.

As a result of this strong growth, Outdoor Sports is currently stocked in several countries in North America and Europe. The Sales department has a sales representative for each country and a Chief Sales Officer.

This is the staff:

  • Peter Bradley (pbradley): Chief Sales Officer.
  • Michael Sanders (msanders): sales representative for USA.
  • Steven Dupont (sdupont): sales representative for Canada.
  • William Aldridge (waldridge): sales representative for UK.
  • Fabian Lombard (flombard): sales representative for France.
  • Rudolf Kauffman (rkauffman): sales representative for Germany.
  • Jorge Perez (jperez): sales representative for Spain.
  • Giovanni Mazzoni (gmazzoni): sales representative for Italy.

Due to the configuration of roles and permissions, each sales rep can only access the data related to their area (North America or Europe) but Peter Bradley can access to the worldwide data. Besides, he has permissions to access to some views representing global reports.

The IT department of Outdoor Sports has two different types of data sources to model the structure of the Sales department, and uses Virtual DataPort to implement the use cases required by the final users. The data related to sales is stored in a MySQL server, whereas the data about marketing promotions is stored in a MS Excel file.

Thankfully, the Information Self Service tool hides these details from the final users so they will not to be aware of how the data is organized or implemented. Nevertheless, they do have a certain level of access to the metadata to be able to configure their own reports according to their personal needs or preferences. They can hide fields, create their own queries to obtain only the data that they want, apply their own filters and save them to avoid repeating the same workflow every time they need the data.

Discover data

Let's say, Peter Bradley wants to know the sales data information in Germany, but he doesn't know how the data is organized internally (He doesn't care about the views/tables.). For this task, he only wants to use a search field like the one he uses when searching with his browser in Internet.

The Denodo Information Self-Service allows that!

Peter Bradley now can log in into the ISS web application, using the same login he uses in the Windows laptop (as you already know Denodo Platform allows Kerberos authentication), click on Databases > OUTDOORSPORTS, click on the Search tab and, finally, type "Germany" in the search field.

Let's see the results:

As you can see, the Information Self-Service Tool shows all the rows in the index that contains the word “Germany” in any field, and clicking on the icon of the view, the matching rows will be displayed.

The number of fields and the number of rows shown by default in this results table can be configured by a Denodo Administrator in the Configuration > Search Configuration section.


Another example, Peter Bradley now wants to know the information related to snowboard products. This is as simple as typing snowboard in the search field.

Let's see the new results:

Combining searches

How can searches combining terms be performed? Simply type germany snowboard to get the sales data in Germany for snowboard products:


To summarize, this means that you, as a high-level user, will be able to:

  • Perform Keyword-based searches from your favourite browser for intuitive discovery process.
  • Do Cross-silo exploration without worrying about where the data is stored or how it’s accessed.
  • Search both metadata and data to find what you want.
  • Have a full view of your data virtualization project

Ok, now you know that there are interesting data in several Denodo views (sales_marketing, salesdata, sales_marketing_summary, ...) but what's next? What about if you need to create more advanced filters (for example, filtering by dates)? or what happen if you need to execute searches for LIVE data?

The next section of the tutorial will answer these questions!