Symfoware Analytics Server

Symfoware Analytics Server is Fujitsu's high-performance database software that is designed for use with data warehouses. It can process and format large volumes of data from mission-critical systems before storing it.

Symfoware Analytics Server incorporates a high-speed query engine that is ideal for data analysis. You can extract and utilize the information you require from a large volume of stored data at high speed by using analysis tools or business applications. Therefore it supports faster job-related decision making.

Symfoware Analytics Server provides a solution for diminishing service levels due to increased data volumes, and to provide greater accuracy for point-of-sale data analysis. Therefore it reduces lost sales, and also offers more effective inventory management to reduce stock wastage and inventory storage issues.

Data analysis is processor-intensive, and can cause disruption by reducing mission-critical system performance. The Symfoware Analytics Server data warehousing solution circumvents this problem by providing an efficient analysis database that is independent of the backend system.

So that users are able to obtain data when they need it, Symfoware Analytics Server provides the following solutions:

High-speed query engine
Symfoware Analytics Server query engine handles columnar tables, this makes it possible to access specific columns within a large volume of data, reducing disk input/output during data retrieval. The query engine can aggregate, search, and analyze stored data at high speed to suit any purpose.

Simple Data Processing definition
Symfoware Analytics Server places the user in control of processing the required data.
Using the GUI, the user can easily define the processing procedure for converting stored data to the data format required. Even users without any specific data mining skills can define a procedure because a Data Processing definition is provided as a template.

Open interface
Symfoware Analytics Server uses an open standard interface. Users can employ a variety of tools, for increasing productivity and enhancing the portability of information-based analytics applications.

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