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Sterna Business Positioning System™ (BPS) is a groundbreaking in-memory Business Intelligence (BI) platform that takes performance management to the next level. Converging strategic, operational, and predictive analytics, it empowers managers to continuously optimize operational and financial performance, enterprise-wide. Implemented in weeks if not days, Sterna BPS in-memory BI platform also drives managers to capitalize on financial opportunities and mitigate risks as they occur.
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To understand the business values derived from the in-memory BI provided by Sterna BPS, a comparison between traditional disk-based BI solutions and in-memory BI solutions is in order. |
Disk-based solutions are either relational (RDBMS) or OLAP based. OLAP engines were introduced to relieve some of the performance issues imposed by RDBMS systems. In essence, OLAP cubes pre-aggregate and pre-calculate the anticipated display options.
The drawbacks of such data storage techniques are:
 | Performance Limitations – since RDBMS systems run on hard-drives, their speed is limited, requiring the creation and maintenance of many intermediate aggregation tables.
| | Low Flexibility – once the OLAP cube structure is built and populated with data, it is highly cumbersome and time consuming to adapt the structure to dynamically changing business needs.
| | Limited scope of analysis – only small set of predefined dimensions.
| | Long implementation cycles – the inability to easily define and plug in and out system architecture components, results in the demand for very detailed requirements analysis and architecture design.
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As business analytics and BI solutions evolve alongside technology, in-memory data storage and manipulation techniques are emerging as a pervasive technology.
Leveraging the availability of low-cost, high-performance memory space and inexpensive 64-bit computing platforms, detailed data can today be loaded in memory where millions of calculations are performed "on the fly" at query time, thus improving performance and shortening implementation cycles.
The Sterna BPS in-memory BI server is unique in that it does not perform any data compression (thus reaching superior performance), and in its in-memory predictive analytics capabilities.
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By 2012, 70% of Global 1000 organizations will load detailed data into memory as the primary method to optimize BI application performance (0.7 probability).
Gartner, October 2006 |
At the core of the Sterna BPS in-memory BI platform is the Sterna BPS Server.
Using patented technology, the highly scalable Sterna BPS Server performs complex time-series based mathematical calculations on very large data sets, on demand, in memory, and in real time.
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Sterna BPS Server bypasses the need to build time-consuming, costly and inherently inflexible OLAP cubes, by storing the organization’s data into an in-memory data-store. Data is read from the organization’s data stores via Data Collectors and transformed into Sterna in-memory virtual data stores called “Business Matrices”.
Using mathematical constraints, Sterna BPS defines and manages in memory a Business Dependency Network that reflects the business interdependencies within the organization.
Business Matrices are maintained completely separately from the mathematical computations, providing an unprecedented level of flexibility. The computations are defined using an intuitive Business Mathematics syntax, expressing the dependencies between the Business Matrices. The set of dependencies among the Business Matrices and formulae results in an in-memory Business Dependency Network; any change to a value of one of the Business Matrices is immediately propagated throughout the network, providing the basis for real-time in-memory BI and advanced analytics such as predictive analytics and simulation capabilities. |
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