Temporary Switching & Simulations

One of the features that we enabled in our QuarkCube platform is the ability to dynamically change the state of metadata and also to track the state of the same. Our premise for enabling such a feature is to make some complex data intensive reporting easier for end users. In general there are 2 kinds of Temporal Switch we provide
1. Temporal Trees – With this, any metadata element within QuarkCube can be structured in a hierarchy form. Each hierarchy/tree is aligned to a specific time. For example, Employee Hierarchy in a specific year or Product Hierarchy in a Year are all Time enabled. So, it is possible to do Modeling Analytics by moving across time on metadata alone. This enables us to answer queries like below

a. What is the Sales done by all Employees reporting into me?
b. What is the Sales done by all Employees who reported into me 3 years back – here data remains the same, but we move across the hierarchies
c. What could be the Sales done by all Employees in the next year but removing a few (say a re-org is happening)?

2. Temporal Attributes – With this, any metadata element within QuarkCube can be aligned to an Attribute which can change over a period of time. This is a very interesting feature where every attribute is given a start date and end date – but then the window between start date & end date can be moved over the time axis to provide a temporal switch perspective. This is very helpful in complex data intensive analytic scenarios like Financial Restatements or M&A Merger/Divesture analysis.

And even more interesting is the fact that both the above can be used together to make it even more powerful. The above 2 gives us the ability to do As Is, As Was and As Could be reporting without writing any code. This enables business users to build complex scenario specific models which can significantly scale.

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