What is a data warehouse?
A data warehouse is a collection of data marts representing historical data from different operations in the company. This data is stored in a structure optimized for querying and data analysis as a data warehouse. Table design, dimensions and organization should be consistent throughout a data warehouse so that reports or queries across the data warehouse are consistent. A data warehouse can also be viewed as a database for historical data from different functions within a company.
What is a data mart?
A data mart is a segment of a data warehouse that can provide data for reporting and analysis on a section, unit, department or operation in the company, e.g. sales, payroll, production. Data marts are sometimes complete individual data warehouses which are usually smaller than the corporate data warehouse.
What are the benefits of data warehousing?
Data warehouses are designed to perform well with aggregate queries running on large amounts of data.The structure of data warehouses is easier for end users to navigate, understand and query against unlike the relational databases primarily designed to handle lots of transactions.Data warehouses enable queries that cut across different segments of a company's operation. E.g. production data could be compared against inventory data even if they were originally stored in different databases with different structures.
Queries that would be complex in very normalized databases could be easier to build and maintain in data warehouses, decreasing the workload on transaction systems. Data warehousing is an efficient way to manage and report on data that is from a variety of sources, non uniform and scattered throughout a company. Data warehousing is an efficient way to manage demand for lots of information from lots of users. Data warehousing provides the capability to analyze large amounts of historical data for nuggets of wisdom that can provide an organization with competitive advantage.
OLAP - Online Analytics Processing
OLAP tools typically provide multi-dimensional functionalities, such as slicing and dicing, and pivoting query results, which require the underlying database to be designed in a multi-dimensional schema. Furthermore, some OLAP tools have specific preference for either star schemas or snowflake schemas (ROLAP), and some tools(MOLAP) even provide their own proprietary DBMS engine (e.g Hyperion System 9) Using the wrong database design could prevent the OLAP tool from functioning properly – or at all.
Hyperion System 9 is a comprehensive Business Performance Management system that
integrates modular suites of financial management applications with the most comprehensive
business intelligence (BI) capabilities for reporting and analysis.
Hyperion System 9 Foundation Services
Hyperion System 9 BI+ Analytics
Hyperion System 9 Applications+
Hyperion System 9 Data Management Services
Hyperion License Server
Hyperion System 9 Shared Services
Hyperion System 9 Smart View for Office
Hyperion System 9 BI+ Analytic Services
Hyperion System 9 BI+ Analytic Administration Services
Hyperion System 9 BI+ Analytic Integration Services
Hyperion System 9 BI+ Analytic Provider Services
Hyperion System 9 BI+ Interactive Reporting - OBIEE Plus
Hyperion System 9 BI+ Financial Reporting - OBIEE Plus
Hyperion System 9 BI+ Production Reporting - OBIEE Plus
Hyperion System 9 BI+ Web Analysis - OBIEE Plus
Hyperion System 9 BI+ Enterprise Metrics
Hyperion System 9 Planning
Hyperion System 9 Financial Management
Hyperion System 9 Performance Scorecard
Hyperion System 9 Strategic Finance
Hyperion System 9 Translation Manager
Hyperion System 9 Master Data Management
Hyperion System 9 Data Integration Management
Hyperion System 9 Financial Data Quality Management
Hyperion System 9 Workspace is the Web client for BI+, Planning, and Financial
Management and is part of the BI+ installation. Hyperion System 9 BPM Architect is part
of the Financial Management and Planning installations.
System 9 Relational Data Repositories:
Some relational databases are supported as both data repositories and data sources.
Products that require a dedicated data repository:
- Analytic Administration Services—A dedicated database repository is required for Analytic Administration Services only if Log Analyzer is used.
- Analytic Integration Services
- BPM Architect—Oracle client must be installed on the Dimension server.
- Data Integration Management
- Financial Management
- Hyperion MDM
- Performance Scorecard
- Shared Services
- Translation Manager
Products on which Oracle 10g-10.2.0.2 is supported:
Siebel Analytics Platform ~ OBIEE
Certified Multidimensional Data Source:
The Essbase cubes will be a data source for the Siebel Analytics/Oracle BI Server. Oracle has the connectivity built but has to get it in a release, most likely the end of the year.
Support for ODBC Data Sources
Oracle Business Intelligence support for ODBC allows Oracle Business Intelligence Server, when operating on Windows, to query any relational database management system—either as a data warehouse, an operational data store or as a transactional system—that supports the ODBC 2.0, 2.1 or 3.5 standards.