Abstract: A report generator of a storage area network management application includes a data validation mechanism that validates data related to managed resources operating in a storage area network. The data validation mechanism obtains first and second data sets concerning first and second characteristics of a resource operating in the storage area network and applies at least one data validation test using data sets to detect inconsistencies in data in the first and second data sets associated with the resource operating in the storage area network. Values can be compared in different columns of the same or different reports to detect report integrity errors or data mining errors. The report generator provides a storage area network management report based on data of the first data set and the second data set that accounts for inconsistencies in data associated with the resource as detected by the at least one data validation test.

Abstract: A decision support system including a query generation tool provides a Graphical User Interface (GUI) for generating a query of a Storage Area Network (SAN) database using interactive screen displays identifying manageable entities in the SAN and queryable statistics thereof. Configurations herein provide a query mechanism, or interface, that generates an executable query via a GUI having intuitive mnemonic labels corresponding to the real-world (i.e. SAN manageable entities) represented in the query database, rather than the technical database table and attribute names which tend to be more cryptic, particularly to an uninitiated query operator. The GUI presents a sequence of screens for selecting SAN manageable entities, report fields, selection criteria, and output format. The query logic computes SQL syntax for identifying corresponding database tables and attributes, performing the required joins between the tables, and selecting the report set of records for output in the resulting SQL query.

Abstract: Described are techniques used in connection with management and processing of configuration data and performance data about a data storage system. The data is collected by one or more agents and forwarded to store components. The store components are responsible for maintaining persistent data objects in a repository. A server may process user requests issued from one or more consoles by retrieving data from the repository and displaying information based thereon on the consoles. The data collected by the agents may be in accordance with a first object model or data representation different from another object model or data representation of the repository. The store components update the repository using data collected by the agents.

Abstract: A Decision Support System (DSS) coalescer offloads and transforms data from an online statistical gathering database to a report query database adapted for report generation. The coalescer generates and populates a query database structured for query data retrieval, in contrast to realtime access transaction storage as in the online database. Configurations transform the online database into a star join schema (table structure) that centralizes database “facts” in a central table and forms associations to database “dimensions” upon which a query is likely to be based. The facts refer to items which tend to change regularly over time, such as sales volumes and unit shipped. Conversely, the dimensions include more static values such as time (e.g. days, weeks, and quarters) and geographic regions, such as states and countries. The resulting query model (schema) includes relatively small dimensions tables associated with (i.e. having a schema association to) a relatively larger fact table.

Abstract: A storage area network (SAN) management application generates device allocation reports displaying foundation variables, device specific parameters, and computed, derived fields for different types of storage arrays, without burdening the allocation report with extraneous parameters through the use of a layout indicative of the information included on the report, providing a streamlined and seamless allocation report. The SAN management application defines a layout indicative of the foundation variables, device attributes, and derived fields requested in an allocation report. The user selected layout indicates the requested allocation parameters for a report, indicative of the foundation variable, device attributes, and derived fields, and also indicates the device usage metrics for computing the derived fields from the foundation variables and device attributes.

Abstract: Collecting data for a storage area network includes providing a plurality of agents that collect data from objects of the storage area network, providing a plurality of data collection policies, where each of the policies indicates a type of data to be collected and a frequency of collection, and applying the policies to the agents, where the agents collect data according to the type of data and the frequencies indicated by the data collection policies. At least one of the agents may have a plurality of data collection policies applied thereto to cause the at least one agent to collect the types of data at the frequencies indicated by the merge of all of the data collection policies applied to the at least one agent. Merging the data collection policies may be performed by the at least one of the agents that receives the data collection policies or may be performed by an entity other than the at least one of the agents.

Abstract: Storage arrays are subdivided into a plurality of physical and logical entities to provide a framework of the available storage. In a large SAN, the network of storage arrays may define a complex arrangement of such physical and logical entities to partition the total storage volume. Therefore, the storage area network classifies a series of storage categories corresponding to different levels of the physical and logical entities representing subdivisions of the storage. In the storage array, designated storage is often not immediately employed for storing active data. In the enumerated storage categories, storage is apportioned from the previous category level in a progressive manner. Storage utilization reports which simultaneously display a plurality of storage category levels, and compute designated and free storage capacity at each level, indicate underutilized or potential available storage which may be obscured by imprecise or overly generous storage allotment estimates.

Abstract: Historical access information identifies which resources in a storage area network access portions of shared storage in the storage area network. Based on an analysis of the historical access information, a management report generator application analyzing such information can infer the existence of a cluster of resources that access a common portion of shared storage. When the management report generator identifies that two or more resources access the same storage resources during approximately the same timeframe, the management report generator knows that there is a high likelihood that the two or more resources are part of a cluster sharing access to common storage resources. Thus, when reporting a tally of storage resources used in the storage area network, it is possible for the management report generator to take into account the cluster and indicate that two resources share access to a common portion of storage.

Abstract: Described are techniques used in connection with management and processing of configuration data and performance data about a data storage system. The data is collected by one or more agents and forwarded to store components. The store components are responsible for maintaining persistent data objects in a repository. A server may process user requests issued from one or more consoles by retrieving data from the repository and displaying information based thereon on the consoles. The data collected by the agents may be in accordance with a first object model or data representation different from another object model or data representation of the repository. The store components update the repository using data collected by the agents.