Finally, the only thing that is left is to access the views we created in the Denodo Platform from a client tool. In this specific example we will use Tableau but any standard tool will be able to access Denodo through either the JDBC, ODBC or Web Services interface.
The first thing we need for Tableau to access Denodo is to create a standard Windows ODBC DSN.
You will need to install first the PostgreSQL ODBC driver, if you don't have it yet. Please go to the official PostgreSQL site and download the latest ODBC driver for your operating system and CPU architecture.
Once that is installed, open the Windows ODBC Data Source Administrator and in the System DSN tab click on "Add ..." and select the postgresql unicode driver.
From Tableau it's easy to connect to Denodo - just follow these steps:
Create a new generic ODBC data source.
Select the DSN that you created in the last step.
Select the schema where you created the virtual views.
Select the view that you want to import. We have tow, monthly_sales_country and monthly_sales_area so follow this process twice.
Once the data connection is live, we can use the standard features from Tableau to create a dashboard that highlights the performance of the marketing promotions over time, split by country, split by area and total across all regions:
With this report at hand, that highlights the promotion-driven sales in orange versus the organic sales in blue, we can measure the performance of each marketing campaign per country and per month, so we can realize at a glance that the campaigns in Germany have low performance when compared to the rest of countries, or that the end of the year has been a great performer in Canada, like the outstanding performance of the first marketing promotion of the year in the UK. All of this thanks to the straightforward way of bringing data together that Denodo provides you.
In this tutorial we have seen how a business question that traditionally has been difficult to answer can be solved with Denodo in a fast and easy manner. Not only that, but implementing a solution using Data Virtualization allows us to have a live report - as we have not imported any data, but retrieved in real time, in the future when our sales database grows and new marketing data becomes available, the report will be always up to date at any point.
On top of that, as we have created semantically relevant business entities within our virtualization layer, we are in a position where deriving new reports or entities is trivial, so we can continue building views and adding value based on disparate data; the fact that the data sources are physically distributed and have a variety of formats does not impact the ease of building new analysis infrastructure on top of them, so we can have an intelligent framework that is centralized, so it prevents duplication of business logic and brings out the real value of the data within your organization.
This concludes the Agile BI tutorial - if you want to continue exploring what the Denodo Platform can do for you, take a look at the official documentation and play with your own use cases.