Information Visualizations Are Just the Tip of the Iceberg
When we first talk to customers, we show them our data visualizations and how these can support visual analysis and monitoring based on their business requirements. This isn’t surprising, of course, since visualizations like our interactive, real-time Treemap are the most obvious part of our Visual Business Intelligence software. However, information visualizations actually account for a very small part of our technology – in fact they form less than a tenth of our total codebase in our platform.
Our unique StreamCube™data model provides rich OLAP functionality that supports fast analysis through the visualizations. The data model can handle traditional multidimensional analysis for static data (like those specified by the MDX language) and also for dynamic data streams. It can also be used for monitoring scenarios, triggering rich events when certain conditions are fulfilled.
 There are data models available from other companies that support multidimensional analytical OLAP functionality. However, most other data models are not optimized for real-time performance. The Panopticon StreamCube™ is specifically designed to make extremely fast calculations using continuously updated data. The StreamCube™ matches the requirements that live visual interactive displays poses to a data back-end. This involves being able to bind aspects of the data to visuals and other requirements. The performance of most other data models degrades significantly when presented with large streaming feeds of live data.
Panopticon's StreamCube™ data model conforms to the original rules defined by Dr Edgar “Ted” Codd for OLAP data models by offering support for multidimensional fast analysis. Specific features include:
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StreamCube™ Data Model
- In-Memory OLAP data model
- Supports multidimensional data and true real-time streaming data
- Handles aggregations & calculations
- Access ODBC, OLE DB and
JDBC-compliant repositories
- Connect to OLAP servers
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Multidimensional conceptual views capable of breaking down dimensions as required by interactive reports.
- Supports intuitive data manipulation, such as interactive direct manipulation (filtering, grouping, and so on.)
- Can be used as a standalone middleware if required, or can be deployed in a client/server architecture – either on the server, on the client or both.
- Can be used both for batch and interpretative use.
- Provides transparency against data sources – provides live access to heterogeneous data sources and can be used to unify structured and unstructured data sources.
- Supports storing aggregates (OLAP results) separately from the source data.
- Supports extraction and treatment of missing values.Provides uniform reporting performance and does not degrade significantly in performance when number of dimensions are increased.
 You can also use the StreamCube™ add OLAP analytical capabilities to virtually any data source. The StreamCube™ provides transparency against data sources and therefore you can also use other OLAP cubes as data sources.
The StreamCube™ data model is at the heart of all of our products, including the Developer SDK, our Enterprise web-deployed solution, and our Explorer Windows Desktop product.
The architecture of our SDK is based on a “pluggable” data model. This means that a programmer can even bypass the StreamCube™ data model entirely and tie our data visualizations directly to other data models.
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