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OLAP Data Mining Interface
A presentation front end that facilitates interaction with complex, multi-dimensional data to produce tabular and graphical reports tailored to performance analysis. Most IT organizations are drowning in huge amounts of raw data produced by a growing number of valuable data sources but lack the ability to organize and correlate that data into unified, meaningful, and actionable information. While each product captures and analyzes raw data, there is no way to combine that data with data from other sources and effectively and meaningfully analyze metrics from multiple appliances.
SeaView/PDB™ is a data management, analysis and reporting tool that enables IT to both correlate the highly granular metrics from multiple SeaView/RTM™ appliances and to integrate those metrics with any other performance measurement tool and with corporate meta-data. PDB's ability to combine RTM's end-user experience metrics, application topology, and external resource utilization feeds, enables IT for the first time to discern cause and effect between their network events. It generates actionable information describing the Quality of Service (QoS) experienced by end users.
Unlike competitive solutions, SeaView/PDB™ comes with a published data dictionary, describing every field, including how it is derived, what it means, and its intended uses.
- the Data Collection component extracts, collects and consolidates data from a multitude of distributed multi-vendor data sources. The SeaView/PDB™ framework is based on flexible and scalable architecture capable of easily adding new data sources.
- the Data Management component, often overlooked by other tools, organizes and manages huge volumes of data collected over long periods of time. Data are managed at various levels: detail, days, weeks, months, and years. This structure maintains needed granularity while at the same time enabling rapid analysis and reporting.
- SeaView/PDB™ provides the key function of identifying, mapping, and categorizing data and correlating it with metadata; for example, matching a dynamically assigned IP address to the real address and user ID by correlating the data to the NAT (Network Address Translation)/authentication server data.
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