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	Star schema - Wikipedia, the free encyclopedia
		The star schema (sometimes referenced as star join schema) is the simplest data warehouse schema, consisting of a single "fact table" with a compound primary key, with one segment for each "dimension" and with additional columns of additive, numeric facts.
		Another reason for using star schema is its ease of understanding.
		Fact tables in star schema are mostly in third normal form (3NF), but dimensional tables are in de-normalized second normal form (2NF).
	en.wikipedia.org /wiki/Star_schema (332 words)

	Star Queries in Oracle8
		This star schema is an intuitive representation of multidimensional ‘datacube’ in a relational environment.
		When presented with a star query, the cost-based optimizer recognizes that the fact table is very large and expensive to access relative to the cost of accessing the much smaller dimension tables, and it considers this cost when choosing the best execution strategy for the star query.
		Many star queries are "outside-in," that is, the end user places constraints on the dimension tables (the outside of the star schema) and retrieves data from the fact table.
	www.fortunecity.com /skyscraper/oracle/699/orahtml/oracle/o8star.html (4951 words)

	Schema Modeling Techniques
		It is called a star schema because the entity-relationship diagram of this schema resembles a star, with points radiating from a central table.
		The snowflake schema is a more complex data warehouse model than a star schema, and is a type of star schema.
		The star transformation is a powerful optimization technique that relies upon implicitly rewriting (or transforming) the SQL of the original star query.
	www.cs.uvm.edu /oracle9doc/server.901/a90237/schemas.htm (2147 words)

	Teradata Magazine \| Applied Solutions: It's In the Stars
		The goal of the star schema is to provide a model that allows the business user to browse just a single table or, at most, a few tables in the query.
		Star schemas aim to minimize joins, to make the most of single table browse or lookups, and to keep the model simple for business user navigation, typically for report generation or “canned ad hoc” queries.
		The new star’s dimension tables might be copies of the existing dimension tables surrounding other fact tables, or they might consist of segments of existing dimension tables or even tables that represent the same dimension but consist of different entities (Figure 3).
	www.teradata.com /t/go.aspx?id=114820 (1357 words)

	Hidden Complexities in a Simple Star Schema (Site not responding. Last check: 2007-11-04)
		When designing a star schema, all data items are divided into one of two groups - numeric items used in calculations and non-numeric items used for filtering and sorting query results.
		The star schema intentionally creates a simplified data arrangement that aids users in understanding the design, while at the same time providing the structural setup for a relational version of a regression equation.
		Star schemas are simple for users to relate to and understand; but much of that simplicity is the result of proper recognition and resolution of the complexities of the source data before it gets to those users.
	www.dmreview.com /editorial/newsletter_article.cfm?nl=dmdirect&articleId=4858 (1747 words)

	Designing Star Schema
		Star Schema is a relational database schema for representing multimensional data.
		It is called a star schema because the entity-relationship diagram between dimensions and fact tables resembles a star where one fact table is connected to multiple dimensions.
		The center of the star schema consists of a large fact table and it points towards the dimension tables.
	www.learndatamodeling.com /star.htm (587 words)

	Teradata Magazine \| Insider's Warehouse: The case for normalization...
		The star schema demands a fixed number of levels because each level is set up by a series of fixed columns in a dimension table.
		Star schemas, snowflakes, summary tables, derived data, etc. could be built as virtual clusters of tables that look exactly like their physical counterparts.
		If the star schemas are physicalized, two very large schemas need to be maintained and coordinated, whereas with virtual star schemas, the data is maintained only in the base tables.
	www.teradata.com /t/page/115866 (2878 words)

	Schema Modeling Techniques (Site not responding. Last check: 2007-11-04)
		star schema is perhaps the simplest data warehouse schema.
		The center of the star consists of a large fact table and the points of the star are the dimension tables.
		Star schemas are used for both simple data marts and very large data warehouses.
	www.lc.leidenuniv.nl /awcourse/oracle/server.920/a96520/schemas.htm (2553 words)

	Schemas (Site not responding. Last check: 2007-11-04)
		The star schema is the simplest data warehouse schema.
		It is called a star schema because the diagram of a star schema resembles a star, with points radiating from a center.
		The star transformation does not rely on computing a Cartesian product of the dimension tables, which makes it better suited for cases where fact table sparsity and/or a large number of dimensions would lead to a large Cartesian product with few rows having actual matches in the fact table.
	www.usd.edu /oracle/doc/server.817/a76994/schemas.htm (2310 words)

	DATA MANAGEMENT STRATEGIES - Pros and cons of the star schema
		Star schemas are said to be the flat representation of a multi-dimensional cube.
		The pro side for star schemas is that they are intuitive to the user community.
		The star schema is one of the outputs of dimensional modeling.
	www.itworld.com /nl/db_mgr/09032003/pf_index.html (826 words)

	SQL Server Professional: October 2000 - The Star Schema: Your Data Warehouse's Foundation
		Therefore, in designing a star schema, your first order of business is usually to determine what you want to see (your measures) and how you want to see it (your dimensions).
		One of the major benefits of the star schema is that the low-level transactions are summarized to the fact table grain.
		Snowflake schemas that allow you to denormalize the dimension tables and represent hierarchical structures using the traditional relational database method aren't generally recommended.
	www.ciobriefings.com /WhitePapers/SQLPro/StarSchema.htm (2393 words)

	Dimensionless Star Schema (Bitmap Star) (Site not responding. Last check: 2007-11-04)
		So when a star is searched the outer dimension tables are first scanned then the bitmaps are merged based on the results from the scan of the dimension tables and the fact table is then sliced and diced based on the bitmap merges.
		However, this structure is not suitable for all star schemas but can be applied in a limited fashion to many where the duplicitous storage of values in both the fact and dimension tables occurs.
		The applicability of this structure has to be determined on a case by case basis and is not a suggested one-size-fits-all solution for all data warehouses.
	www.dba-oracle.com /T-dimensionless_star_bitmap_schema.htm (629 words)

	Star Schema Data Modeling for Data Mining
		Star schema is a standard technique for designing and building multi-dimensional databases in data warehousing.
		Star schema typically consists of a single main table and zero or more dimensional table.
		A flat file schema is a special case of star schema where there are no domain tables.
	www.roselladb.com /star-schema.htm (720 words)

	[Dev] star schemas (Re: RDF triples and Chandler data)
		The star schema seems named for the way tables revolve around the heart of the star, occupied by a central fact table which contains the bulk of content describing events of some kind -- an email fits the bill for "event" in this context.
		The star schema modeling approach seems characterized by an attempt to resist the fetishistic pursuit of database normalization by ER modeling practioners, which causes so much data factoring (to reduce reduncancy) that performance is killed by bad locality of reference when simply duplicating the data wouldn't have much space cost.
		In other words, a star schema favors flat tables which duplicate data, so joins (which are just inferences about related info) happen faster without having to jump through a long graph of data.
	lists.osafoundation.org /pipermail/dev/2002-November/000314.html (977 words)

	I am in the process of designing the data model for the data warehouse. Is star schema or snowflake better?
		Les Barbusinski's Answer: The choice of whether to use star schemas, snowflake schemas or a hybrid of the two in a data mart is largely dictated by the business intelligence tool you choose to use.
		Star schemas and snowflake schemas are part of dimensional modeling.
		That is that the star simply consists of the fact surrounded by a single level of collapsed or consolidated dimension entities.
	www.dmreview.com /article_sub.cfm?articleId=5465 (1122 words)

	A Star Schema Model for Narrative Data
		The representation of narrative facts in a star schema configuration has the potential to allow its users to “read less and learn more,” by supporting very targeted search capabilities on data that, in its native form, might need to be processed sequentially (i.e., read), a very time-consuming access method.
		Also, in the Narrative Star schema, any fact can occur at any level of detail for any taxonomy/dimension, in contrast to the more familiar iterative-data star schema where all facts are typically stored at the same level of detail for each dimension.
		In a narrative-data star schema, each fact is attributed to a narrative artifact (e.g., document); each narrative is a reference attesting to one or more facts.
	www.b-eye-network.com /view/1196 (1319 words)

	Clear View Training - What is STAR? (Site not responding. Last check: 2007-11-04)
		STAR is based on structured text and restructured text.
		STAR is very flexible and comes with a set of tools for transforming STAR documents into XML, XHTML and PDF.
		STAR use case editor - this is an example (but perfectly usable) STAR application that is a browser and editor for use cases
	www.umlandtheunifiedprocess.com /CVTPlone/STAR (451 words)

	19 Schema Modeling Techniques
		Although this guide primarily uses star schemas in its examples, you can also use the third normal form for your data warehouse implementation.
		A star join is a primary key to foreign key join of the dimension tables to a fact table.
		The star transformation is a query transformation aimed at executing star queries efficiently.
	stanford.edu /dept/itss/docs/oracle/10g/server.101/b10736/schemas.htm (2478 words)

	Data Warehouse Center Administration Guide (Site not responding. Last check: 2007-11-04)
		You would populate a star schema within the Data Warehouse Center with cleansed data before you use the data to build a multidimensional cube.
		A star schema is a specialized design that consists of multiple dimension tables, which describe aspects of a business, and one fact table, which contains the facts about the business.
		To view the warehouse schema that you exported, open the OLAP model (warehouse schema) using the warehouse schema name that you used in the Data Warehouse Center.
	www.pdc.kth.se /doc/SP/manuals/db2-7.1/html/db2dd/db2dbstr.htm (3813 words)

	Star Schema - FoxPro Wiki (Site not responding. Last check: 2007-11-04)
		The star schema has a single object (table) in the middle radially connected to other surrounding objects (tables) like a star.
		The star schema mirrors the end user's view of a business query such as a sales fact that is qualified by one or more dimensions (e.g., product, store, time, region, etc.).
		Moreover queries based on such schemas are quick (since the data in the DimensionTables is highly denormalized).
	fox.wikis.com /__snapshot/StarSchema.htm (629 words)

	[No title]
		Snowflake Schema The snowflake schema is a variant of the star.
		Another technique to help you avoid a snowflake schema (and consequently, bad performance) is to take the table that is a candidate snowflake dimension and hook it directly to the fact table; essentially, you are promoting the table to true dimension status.
		Some constellation schemas may consist of detail and aggregate fact tables; they may also consist of the detail rows arranged by month and by year (with the year table simply being a view).
	cis.bentley.edu /mrobbert/CS753/stars.doc (3125 words)

	Business Intelligence Tutorial (Site not responding. Last check: 2007-11-04)
		You also must have defined the dimension tables and fact table in Defining the rest of the tables for the star schema (optional).
		In this exercise, you will define the star schema that is to contain the dimension and fact tables that you have defined in this tutorial.
		In this exercise, you will open the star schema so that you can add the dimension tables and fact table to the schema in the next exercise.
	www.seas.ucla.edu /db2/db2tu/db2tussw.htm (819 words)

	Designing the Star Schema Database
		Creating a Star Schema Database is one of the most important, and sometimes the final, step in creating a data warehouse.
		In this section, on the star schema, we will just assume the “base” level of aggregation: all the data in our data warehouse is aggregated to a certain point in time.
		Therefore, in designing a star schema, our first order of business is usually to determine what we want to see (our measures) and how we want to see it (our dimensions).
	www.ciobriefings.com /whitepapers/StarSchema.asp (5086 words)

	AskTom "Star Schema" (Site not responding. Last check: 2007-11-04)
		Third is star transformation and the fourth is the introducion of bitmap join indexes.
		star schema is a data warehouse construct, as far from oltp (transaction processing) as you get.
		Snowflake schema is yet another relational model with fact tables and dimension tables.
	asktom.oracle.com /pls/ask/f?p=4950:8:::::F4950_P8_DISPLAYID:4632159445946 (9143 words)

	Why is the Star Schema a Good Data Warehouse Design? (ResearchIndex)
		Abstract: Database design for data warehouses is based on the notion of the snowflake schema and its important special case, the star schema.
		The snowflake schema represents a dimensional model which is composed of a central fact table and a set of constituent dimension tables which can be further broken up into subdimension tables.
		We formalise the concept of a snowflake schema in terms of an acyclic database schema whose join tree satisfies certain structural properties.
	citeseer.ist.psu.edu /220339.html (546 words)

	Star Schema
		The data schema (depicted in Figure 12) used in this experiment was composed of four tables:
		Figure 14: Time performance for Star schema for support level 20%.
		However, even for complex, expensive joins, we expect the relative performance of the I/O saving and Memory saving joined to be similar to the one exhibited for this data set.
	www.eecs.umich.edu /~viviane/Ddmprog/node46.html (607 words)

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