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One of the most overlooked components of the Oracle Analytics platform has undoubtedly been the Administration Tool. This tool is used to manage the repository otherwise known as the semantic model. 

In this blog, we’ll take a look back at the Administration Tool and also look at the structure of the repository/semantic model.

History

This modelling tool has been around since the nQuire/Siebel Analytics days which makes the Administration Tool well over 20 years old and in need of a fresh lick of paint. If you look closely enough, you’ll still spot references to nQuire!

The Administration Tool (affectionately known as the Admin Tool)  provides the interface to what was Oracle’s unique selling point back in the day - the Semantic Model. This model is a metadata representation of complex data structures mapped to business terms that end users are more accustomed to.  Its main benefit was that it provides a layer of abstraction between end-users and the complex data structures of the applications that users are looking to pull out insights from.

The Semantic Model also defines data security that can be used to manage user data access. There are other levels of security that can be defined in the model to control access to certain parts of the model. Calculations can be defined centrally in the model ensuring that all end users have access to the centrally defined calculations.

Model Structure

The Admin Tool consists of three main areas:

  1. Physical Layer
  2. Business Model & Mapping Layer
  3. Presentation Layer

One of the main benefits of the 3-layered model is that you have the ability to abstract the physical data sources from the logical part of the model. This means that you can define data sources from multiple vendors as well as easily isolate physical data source changes.

Definitions of physical data sources are set up within the Physical Layer where you also define the relationship between these physical tables. It is also within the Physical Layer that data source connections are defined.

The Business Model & Mapping layer also called the logical layer is the section of the Semantic Model where physical models defined in the Physical Layer are translated logically into business terms. An example is that you may store Customer and Countries as 2 physical tables but from a business perspective, these 2 sets of data can be logically grouped together into a single logical table. Facts (their measures), dimensions (their attributes), and hierarchical structures of dimensions are also set up in this layer.

The third layer in the Semantic Model is known as the Presentation Layer. It is within this layer that the structure of the model that is accessible by end-users is configured.

Initial Setup

To activate the Semantic Modeller, you’ll need to enable it by navigating to the Oracle Analytics console in Data Visualisation to access the System Settings. Within the Preview section of the System Settings, enable the toggle of the “Preview Semantic Modeller” setting.

 

Finally, you’ll need to log out and log back in again for the changes to be activated. You should now be able to access the Semantic Model option from the hamburger icon on the home screen.

Clicking on the Semantic Models menu item in the dropdown from the hamburger menu on the home screen will open up the Semantic Models screen which lists all models that have been worked on previously.

Disclaimer

Oracle has clearly stated that the Semantic Modeller has been released in the May 2022 Oracle Analytics Cloud release as a preview feature. The modeller should not be used in Production environments.

Coming Soon

In the next part of this series, we’ll take a look at the user interface of the new web-based semantic modeller.

In future blogs within this series covering the Semantic Modeller, we will be looking at specific areas of the new tool in detail to describe how it all works. We’ll also be highlighting the feature parity between the current Admin Tool client and the new web-based Semantic Modeller. We will also be looking at the new features of the Semantic Modeller that bring repository development into the 21st century.

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Topics

Analytics

Joel Acha

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Joel Acha