Already in pilot with a major Investment Bank, PolarLake has been able to consolidate ten separate Trade, Position, Reference and Client Data repositories in 5 weeks, benchmarked to hundreds of millions of Trades. With this Solution PolarLake's Clients have a choice of maintaining the Data in the source repository, loading into the PolarLake Data Store for processing or a combination of the two, making the solution a "Virtualized" Data Warehouse solution.

The components of the PolarLake Virtualized Data Warehouse Solution are:
 PolarLake Data Search Application: An out of the box Search Application enabling clients to answer questions such as, "What are my unsettled Trades?" and "What are my total positions in securities A,B,C?". The Search Application can also be used to define data extracts in custom formats for reporting purposes.
 PolarLake Semantic Policy and Rules Engine: The Semantic Policy and Rules engine enables the creation and implementation of Business Rules for building consolidated records and the creation of Virtual Identifiers across all repositories. This delivers remote linking of entities with zero intervention on the source repositories themselves.
 PolarLake Data Store: The Data Store provides a store for Source Data as well as Index Data used in Virtualized queries. A post-relational Data Store, it is also fully change tolerant to changes in source repositories with zero downtime for format changes.
 PolarLake Connectivity Subsystem: The PolarLake Connectivity Subsystem enables communication across multiple protocols and formats in batch, real time, request reply, pub sub and ad hoc distributions. This PolarLake component allows for the assembly of Virtualized Queries, data import into the PolarLake Data Store, as well as a sophisticated export / API service to the Data Store.

The Business Challenges which are addressed by the PolarLake Virtualized Data Warehouse solution are:
 Compliance and Regulation: Ability to integrate Trade, Position, Reference & Client reporting across multiple repositories and asset classes over extended reporting periods, giving integrated access and transparency to regulators.
 Risk Management: Ability to track and consolidate unsettled Trades and Counterparties exposures across multiple Trade and Client repositories.
 Operational Efficiency Improvement: Ability to gain insight and control Trade flows across multiple applications from Front, Middle and Back Office.

Commenting on the release, PolarLake CEO John Randles said "At times of huge challenges, innovation always comes to the fore. We are at the point now where the old approaches of massive multi-year Data Warehousing projects are no longer tenable. The PolarLake approach of adopting a Search based view of Data with an Integrated Semantic Policy Engine proven to deliver business requirement in weeks rather than years. This will aid firms to address the tide of Regulation requirements coming down the track and the unending pressure to do more with less."