Metadata is effectively another database in which information related to the DWH data is stored; this information facilitates data transfer between the DWH itself and the Microstrategy application: essentially, the Microstrategy application uses the metadata database to convert user requests into SQL queries and reconvert the results of these queries into Microstrategy objects such as reports and documents. To download the full text and for more information, click HERE
As the amount of information stored in the Data Warehouse grows and the ways in which it is used increase, it becomes necessary to manage so-called metadata in a sort of repository, that is, the information related to the data itself. The definition of metadata varies depending on the context in which it is applied: • in Data Warehouse design, they represent the mapping of business information to the data contained in the Data Warehouse • in acquisition through ETL tools, they represent the transformation methods of data from operational systems to the Data Warehouse • in management via DBMS, they represent database objects (e.g. tables, views, users, …) • in access via OLAP products, they represent the mapping of the physical database schema to the view obtainable through queries Metadata are created and managed during the design and development phase of the Data Warehouse. They can be imported from external sources such as DBMS catalogs, program libraries, Case products. They are managed within tools that cover various architectural aspects. Often, the architecture of the tools is proprietary and results in a non-unified management of metadata. Normally, they are distinguished as technical metadata and business or functional metadata. Technical metadata contain detailed information about the design, development, creation, and management phases (authorizations, save frequency, update frequency, versioning) of the Data Warehouse data. Other examples of technical metadata are information related to data acquisition (cleaning and extraction rules), information on types of access to the Data Warehouse, and on how data usage by users is performed (statistics). Business metadata contain information that allows the end user to access the Data Warehouse in a manner understandable from a business perspective. This information particularly concerns the association between technical metadata and business concepts: from which source systems the data come, details relating to queries, predefined DSS reports and objects, subscriptions to reports and analyses whose results are then regularly provided. Among business metadata, information regarding data ownership and more generally authorization aspects is especially important. The fundamental requirement for products supporting metadata use is the integration of their management throughout the entire Data Warehouse creation process. However, there is still no global standard for managing types of metadata, which are created and managed in a proprietary manner within tools that cover the various architectural aspects. The real difficulty, therefore, is to integrate and synchronize these metadata islands to have a single interface and mode of handling both technical and business metadata. Below is presented in a three-dimensional form, to allow an immediate perception of “who does what,” the complete structure of the MicroStrategy decision support suite Integrated Business Data Analysis • The ROLAP approach provides data access at a transactional level of detail • The optimized multi-step SQL code allows fast and efficient access to databases, without size or vendor limits • An extensive multi-level security model protects business assets • The Metadata-centric architecture enables reuse of business rules and data definitions • Flexible support for heterogeneous schemas allows leveraging existing data architectures A Scalable, High-Performance Application Server • Clustering allows adding resources adapting to needs • Intelligent Cubes maximize performance for large user communities • Failover ensures high reliability for critical applications The Server-centric architecture optimizes performance for millions of users Easy and Powerful Query & Reporting over the Internet • The purely DHTML interface provides a robust security model • A “thin-client” architecture simplifies deployment and maintenance • An intuitive interface based on common web standards is as easy to use as a search engine • The interface and features are fully customizable Structured workflow paths guide the analysis Advanced Analysis for All Users • Predefined statistical and financial functions enable forecasting, trend analysis, data mining • Iterative analysis optimizes middle-tier and database features allowing rapid advanced analysis • Set analysis enables multi-level calculations not allowed by other tools Users can create Derived Metrics on each report Proactive Delivery of Critical Information • Subscriptions ensure personalization based on user-defined preferences • Exception reporting employs sophisticated metrics • Information is delivered via web, wireless, and voice • Scalability exceeds 200,000 messages per hour Content comes from multiple sources, such as databases, files, web, XML Rapid and Simple Integration with Existing Applications • Easy integration with web applications and portals thanks to Java, XML, and MDX standards • Supports Excel and other business intelligence clients • Closed-loop decision support provides write-back databases and integration with backend systems A rich set of open APIs allows integration of customized features, content, and interfaces Rapid Application Development • The Application Creation Wizard allows creating fully functional applications in minutes • An Abstraction layer provides the necessary flexibility for evolving your business model • Migration from development to production environment is immediate • System administration is possible both from command line and GUI Data replication is eliminated thanks to the adoption of a single data store ALL RIGHTS RESERVED
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