Design of a Data Warehouse: A BusinessAnalysis Framework Four views regarding the design of a data warehouse Top-down view allows selection of the relevant information necessary for thedata warehouse Data source view exposes the information being captured, stored, andmanaged by operational systems Data warehouse view consists of fact tables and dimension tables Business query view sees the perspectives of data in the warehouse from the viewof end-user33Data Warehouse Design Process Top-down, bottom-up approaches or a combination of both Top-down: Starts with overall design and planning (mature) Bottom-up: Starts with experiments and prototypes (rapid) From software engineering point of view Waterfall: structured and systematic analysis at each step beforeproceeding to the next Spiral: rapid generation of increasingly functional systems, shortturn around time, quick turn around Typical data warehouse design process Choose a business process to model, e.g., orders, invoices, etc. Choose the grain (atomic level of data) of the business process Choose the dimensions that will apply to each fact table record Choose the measure that will populate each fact table record
Three Data Warehouse Models Enterprise warehouse collects all of the information about subjects spanning theentire organization Data Mart a subset of corporate-wide data that is of value to a specificgroups of users. Its scope is confined to specific, selectedgroups, such as marketing data mart Independent vs. dependent (directly from warehouse) data mart Virtual warehouse A set of views over operational databases Only some of the possible summary views may bematerialized
OLAP Server Architectures Relational OLAP (ROLAP) Use relational or extended-relational DBMS to store and managewarehouse data and OLAP middle ware to support missing pieces Include optimization of DBMS backend, implementation ofaggregation navigation logic, and additional tools and services greater scalability Multidimensional OLAP (MOLAP) Array-based multidimensional storage engine (sparse matrixtechniques) fast indexing to pre-computed summarized data Hybrid OLAP (HOLAP) User flexibility, e.g., low level: relational, high-level: array Specialized SQL servers specialized support for SQL queries over star/snowflake schemas38
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