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8/7/2019 MISM 621_Microsoft Data Warehouse Tool_Group 8
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Microsoft Data Warehouse Tool
International School of Information Management,
University of Mysore, Mysore
Submitted to,
Prof. Chandrashekar
Submitted By,
Saurabh Dey
saurabh@isim.net.in
Shrestha Rath
shrestha_rath@isim.net.in
Sowmya S.
sowmya@isim.net.in
Sukritha S.
sukritha@isim.net.in
mailto:saurabh@isim.net.inmailto:shrestha_rath@isim.net.inmailto:sowmya@isim.net.inmailto:sukritha@isim.net.inmailto:saurabh@isim.net.inmailto:shrestha_rath@isim.net.inmailto:sowmya@isim.net.inmailto:sukritha@isim.net.in8/7/2019 MISM 621_Microsoft Data Warehouse Tool_Group 8
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~ Content ~
Summary 2
1. Introduction 3
2. Microsoft Data Warehouse Framework
4
2.1. Building Data Warehouse 4
2.2. Managing Data Warehouse 5
2.3. Using Data Warehouse 5
3. Features of SQL Server 2008
5
4. Functions of SQL Server 2008
10
4.1. Aggregate Functions in SQL Server 2008 10
4.2. Default Databases in SQL server 2008 11
4.3. Types of Joins in SQL Server 11
4.4. Indexes in Microsoft SQL Server 12
5. BI Overview and ETL
13
6. Comparison of Microsoft Data Warehouse with IBM DB215
7. A Case Study of Carl Zeiss Vision, North America
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8. Conclusion 20
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References 20
Summary
This report highlights the basic concept of Data Warehouse and the main focus is given on
Microsoft Data Warehouse Tool. Microsoft Data Warehouse tool is actually a combination of
various components such as SQL Server Database, SQL Server Integration Services (SSIS), SQL
Server Analysis Services (SSAS), and SQL Server Reporting Services (SSRS). The SQL Server
is designed by Microsoft and the current released version is Microsoft SQL Server 2008 R2.
In this report the Microsoft Data Warehouse Framework is described which has building section,
managing section and utilizing section. The building section captures data from various data
sources such as legacy systems; flat files etc., and then perform basic transformation to make the
data suitable for loading into the data warehouse. The managing section performs the
management of metadata repository which allows the smooth operation of multiple vendor tools
without creating any problem in the data warehouse operation. The utilization section provides
the user access to the stored data for analysis and decision making, through different application
programs and directory access, which helps in searching and security of the stored data.
SQL server has various features like, automatic recovery of data pages which enables the
principal and mirror machines to transparently recover from 823/824 types of data page errors,
then predictable query performance which enables greater query performance stability and
predictability etc. It has many other features also which are discussed in the content. In the
functions of SQL Server 2008 focus is given on aggregate functions, default databases, types of
joins supported and index.
In the overview of Business Intelligence (BI) the basic structure of the BI is given in graphic
format and the extraction, transformation and loading of data is defined in brief using four
themes. Finally a comparison is made between Microsoft SQL Server and IBM DB2.
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2. Microsoft Data Warehouse Framework
The Microsoft Data Warehouse Framework has been designed to provide an open architecture
which can be extended easily by Microsoft customers and business partners using industry
standard technology.
The Microsoft Data Warehouse Framework describes the relationship between the various
components used in the process of building, using and managing a data warehouse. The core of
the framework is the set of enabling technologies data transport layer and integrated metadata
repository. The framework has three sections that are given below -
Figure 1: Microsoft Data Warehouse Framework
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2.1. Building Data Warehouse
This section requires a set of tools for describing logical and physical design of the data sources
and their destinations in the data warehouse or data marts. Data which is operational must go
through cleansing and transformation stage before being fetched into the data warehouse or data
marts in order to meet the definition set up during design stage. The depth of data staging process
varies based on the enterprise data warehouse architecture.
2.2. Managing Data Warehouse
The managing section of Microsoft Data Warehouse framework manages multi server network
and also schedules recurring task. There is a repository in this managing section which provides
integration point for metadata that is shared by the various tools used in the data warehousing
process. Shared metadata helps in integrating multiple tools that are available from different
vendors, so due to that no specialized interface is needed between each of the tools.
2.3. Using Data Warehouse
In the using section of Microsoft Data Warehouse framework, desktop productivity products,
specialized analysis products and custom programs are used to gain access to information in the
data warehouse. The user access to the data warehouse is done by information directory which
provides optimized search option to the end user and also provides secured access to the data
warehouse.
3. Features of SQL Server 2008
Transparent Data Encryption - Enable encryption of an entire database, data files, or
log files, without the need for application changes. Benefits of this include: Search
encrypted data using range and fuzzy searches, search secure data from unauthorized
users, and data encryption without any required changes in existing applications.
Extensible Key Management - SQL Server 2005 provides a comprehensive solution for
encryption and key management. SQL Server 2008 delivers an excellent solution to this
growing need by supporting third-party key management and HSM products.
Auditing - Create and manage auditing via DDL, while simplifying compliance by
providing more comprehensive data auditing. This enables organizations to answer
common questions, such as, What data was retrieved?
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Enhanced Database Monitoring - SQL Server 2008 builds on SQL Server 2005 by
providing a more reliable platform that has enhanced database mirroring, including
automatic page repair, improved performance, and enhanced supportability.
Automatic Recovery of Data Pages - SQL Server 2008 enables the principal and mirror
machines to transparently recover from 823/824 types of data page errors by requesting a
fresh copy of the suspect page from the mirroring partner transparently to end users and
applications.
Log Stream Compression - Database mirroring requires data transmissions between the
participants of the mirroring implementations. With SQL Server 2008, compression of
the outgoing log stream between the participants delivers optimal performance and
minimizes the network bandwidth used by database mirroring.
Resource Governor - Provide a consistent and predictable response to end users with the
introduction of Resource Governor, allowing organizations to define resource limits andpriorities for different workloads, which enable concurrent workloads to provide
consistent performance to their end users.
Predictable Query Performance - Enable greater query performance stability and
predictability by providing functionality to lock down query plans, enabling
organizations to promote stable query plans across hardware server replacements, server
upgrades, and production deployments.
Data Compression - Enable data to be stored more effectively, and reduce the storage
requirements for our data. Data compression also provides significant performance
improvements for large I/O bound workloads, like data warehousing.
Hot Add CPU - Dynamically scale a database on demand by allowing CPU resources to
be added to SQL Server 2008 on supported hardware platforms without forcing any
downtime on applications. Note that SQL Server already supports the ability to add
memory resources online.
Policy-based Management - Police-based Management is a policy-based system for
managing one or more instances of SQL Server 2008. Use this with SQL ServerManagement Studio to create policies that manage entities on the server, such as the
instance of SQL Server, databases, and other SQL Server objects.
Streamlined Installation - SQL Server 2008 introduces significant improvements to the
service life cycle for SQL Server through the re-engineering of the installation, setup, and
configuration architecture. These improvements separate the installation of the physical
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bits on the hardware from the configuration of the SQL Server software, enabling
organizations and software partners to provide recommended installation configurations.
Performance Data Collection - Performance tuning and troubleshooting are time-
consuming tasks for the administrator. To provide actionable performance insights to
administrators, SQL Server 2008 includes more extensive performance data collection, a
new centralized data repository for storing performance data, and new tools for reporting
and monitoring.
Language Integrated Query (LINQ) - Enable developers to issue queries against data,
using a managed programming language, such as C# or VB.NET, instead of SQL
statements.
ADO.NET Data Services - Developers using the ADO.NET framework can program
against a database, using CLR objects that are managed by ADO.NET. SQL SERVER
2008 introduces more efficient, optimized support that improves performance andsimplifies development.
DATE/TIME - SQL Server 2008 introduces new date and time data types:
DATE A date-only type
TIME At time-only type
DATETIMEOFFSET A time-zone-aware datetime type
DATETIME2 A datetime type with larger fractional seconds and year range
than existing DATETIME type
The new data types enable applications to have separate data and time types while
providing large data ranges of user defined precision for time values.
HIERARCHY ID - Enable database applications to model tree structures in a more
efficient way than currently possible. New system type HIERARCHYID can store values
that can represent nodes in a hierarchy tree. This new type will be implemented as a CLR
UDT, and will expose several efficient and useful built-in methods for creating and
operating on hierarchy nodes with a flexible programming model.
FILESTREAM Data - Allow large binary data to be stored directly in an NTFS file
system, while preserving an integral part of the database and maintaining transactionalconsistency. Enable the scaleout of large binary data traditionally managed by the
database to be stored outside the database on more cost-effective storage without
compromise.
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Integrated Full Text Search - Integrated Full Text Search makes the transition between
Text Search and relational data seamless, while enabling users to use the Text Indexes to
perform high-speed text searches on large text columns.
Sparse Columns- NULL data consumes no physical space, providing a highly efficient
way of managing empty data in a database. For example, Sparse Columns allows object
models that typically have numerous null values to be stored in a SQL Server 2005
database without experiencing large space costs.
Large User-Defined Types - SQL Server 2008 eliminates the 8-KB limit for User-
Defined Types (UDTs), allowing users to dramatically expand the size of their UDTs.
Spatial Data Types It has support for spatial data. It implements Round Earth solutions
with geography data type. Uses latitude and Longitude coordinates to define areas on the
Earths surface. It implements Flat Earth solutions with the geometry data type. Storepolygons, points, and lines that are associated with projected planar surfaces and
naturally planar data, such as interior spaces.
Backup Compression - Keeping disk-based backups online is expensive and time-
consuming. With SQL Server 2008 backup compression, less storage is required to keep
backups online, and backups run significantly faster since less disk I/O is required.
Partitioned Table Parallelism - Partitions enable organizations to manage large growing
tables more effectively by transparently breaking them into manageable blocks of data.
Star Join Query Optimizations - SQL Server 2008 provides improves query
performance for common data warehouse scenarios. Star Join Query optimizations
reduce query response time by recognizing data warehouse join patterns.
Grouping Sets - Grouping sets is an extension to the GROUP BY clause that lets users
defines multiple grouping in the same query. Grouping Sets produces a single result set
that is equivalent to a UNION ALL of differently grouped rows, making aggregation
querying and reporting easier and faster.
Change DataCapture - With Change Data Structure, changes are captured and placed
in change tables. It captures complete content of changes, maintains cross-table
consistency, and even works across schema changes. It enables organizations to integrate
the latest information into the data warehouse.
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MERGE SQL Statement With the inclusion of this statement developers can more
effectively handle common data warehousing scenarios, like checking whether a row
exists, and then existing an insert or update.
SQL Server Integration Services (SSIS) Pipeline Data Integration packages can scale
more effectively, making use of available resources and managing the largest enterprise-
scale workloads.
SQL Server Integration Services (SSIS) Persistent Lookups - The need to perform
lookups is one of the most common ETL operations. This is especially prevalent in data
warehousing, where fact records need to use lookups to transform business keys to their
corresponding surrogates, SSIS increases the performance of lookups to support the
largest tables.
Analysis Scale and Performance SQL Server 2008 drives broader analysis withenhanced analytical capabilities and with more complex computations and aggregations.
Cube design tools help users streamline the development of the analysis infrastructure
enabling them to build solutions for optimized performance.
Block Computations Block computations provide a significant improvement in
processing performance enabling user to increase the depth of their hierarchies and
complexity of the computations.
Writeback - MOLAP enabled writeback capabilities in SQL Server 2008 Analysis
Services removes the need to query ROLAP partitions. This provides users with
enhanced writeback scenarios from within analytical applications without sacrificing the
traditional OLAP performance.
Enterprise Reporting Engine - Reports can easily be delivered throughout the
organization, both internally and externally, with simplified deployment and
configuration. This enables users to easily create and share reports of any size and
complexity.
Internet Report Development - Customers and suppliers can effortlessly be reached bydeploying reports over the Internet.
Manage Reporting Infrastructure - Increase supportability and the ability to control
server behavior with memory management, infrastructure consolidation, and easier
configuration through a centralized store and API for all configuration settings.
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Report Builder Enhancements - Easily build ad-hoc and author reports with any
structure through Report Designer.
Forms Authentication Support - Support for Forms authentication enable users to
choose between Windows and Forms authentication.
Report Server Application Embedding - Report Server application embedding the
URLs in reports and subscriptions to point back to front-end applications.
Microsoft Office Integration - SQL Server 2008 provides Word rendering that enables
users to consume reports directly from within Microsoft Office Word. In addition, the
existing Excel renderer has been greatly enhanced to accommodate the support features,
like nested data regions, sub-reports, as well as merged cell improvements. This let users
maintain layout fidelity and improves the overall consumption of reports from Microsoft
Office applications.
Predictive Analysis - SQL Server Analysis Services continues to deliver advanced data
mining technologies. Better Time Series support extends forecasting capabilities.
Enhanced Mining Structures deliver more flexibility to perform focused analysis through
filtering as well as to deliver complete information in reports beyond the scope of the
mining model. Cross-validation enables confirmation of both accuracy and stability for
results that you can trust. Furthermore, the new features delivered with SQL Server 2008
Data Mining Add-ins for Office 2007 empower every user in the organization with even
more actionable insight at the desktop.
4. Function of SQL Server 2008
Following are the different functions performed by Microsoft SQL Server 2008
4.1. Aggregate Functions in SQL Server 2008
Aggregate functions are applied to a group of data values from a column. Aggregate functions
always return a single value. SQL Server 2008/Transact-SQL supports following aggregatefunctions:
AVG - Calculates the arithmetic mean (average) of the data values contained within a
column. The column must contain numeric values.
MAX and MIN - Calculate the maximum and minimum data value of the column,
respectively. The column can contain numeric, string, and date/time values.
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SUM - Calculates the total of all data values in a column. The column must contain
numeric values.
COUNT - Calculates the number of (non-null) data values in a column. The only
aggregate function not being applied to columns is COUNT (*). This function returns the
number of rows (whether or not particular columns have NULL values).
COUNT_BIG - New and Analogous to COUNT, the only difference being that
COUNT_BIG returns a value of the BIGINT data type.
Aggregate function Example
SELECT ProjectName, SUM (budget) TotalBudget FROM Project_Tbl GROUP BY
ProjectName;
4.2. Default Databases in SQL server 2008
Microsoft SQL SERVER provides 3 default databases.
The Master database holds information for all the databases located on the SQL Server
instance and is the glue that holds the engine together. Because SQL Server cannot start
without a functioning master database, we must administer this database with care.
The tempdb holds temporary objects such as global and local temporary tables and stored
procedures. The model is essentially a template database used in the creation of any new
user database created in the instance.
The msdb database stores information regarding database backups, SQL Agent
information, DTS packages, SQL Server jobs, and some replication information such as
for log shipping.
4.3. Types of Joins in SQL Server
Joins are used in SQL queries to explain how different tables are related. Joins helps in selecting
data from a table depending upon data from another table.
Joins are used to retrieve data from more than one table based a common field. Based on the
query, the output is taken from two or more tables.
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Types of Joins: INNER JOIN, OUTER JOIN, CROSS JOIN, OUTER JOIN is further classified
as LEFT OUTER JOINS, RIGHT OUTER JOINS and FULL OUTER JOINS.
4.4. Indexes in Microsoft SQL Server
An index is a physical structure containing pointers to the data. Indexes are created in an either
existing table to locate rows more quickly and efficiently or it is possible to create an index on
one or more columns of a table, and each index is given a name. The users cannot see the
indexes; they are just used to speed up queries. Effective indexes are one of the best ways to
improve performance in a database application.
A table scan happens when there is no index available to help a query. In a table scan SQL
Server examines every row in the table to satisfy the query results. Table scans are sometimes
unavoidable, but on large tables, scans have a terrific impact on performance. There are twotypes of indexes are available in SQL SERVER.
Clustered indexes define the physical sorting of a database tables rows in the storage
media. For this reason, each database table may have only one clustered index. A
clustered index is a special type of index that reorders the way records in the table are
physically stored. Therefore, table can have only one clustered index. The leaf nodes of a
clustered index contain the data pages.
Non-clustered indexes are created outside of the database table and contain a sorted list of
references to the table itself. Non-clustered indexes can be multiple. A non-clustered
index is a special type of index in which the logical order of the index does not match the
physical stored order of the rows on disk. The leaf node of a non-clustered index does not
consist of the data pages. Instead, the leaf nodes contain index rows of references to the
table.
5. BI Overview and ETL
Microsoft has built an end-to-end BI platform and is in the form of Data Transformation Service
(DTS), Analysis Services and Reporting Services. DTS was rewritten as SQL Server Integration
Services (SSIS), which is an enterprise class Extract Transform Load (ETL) tool. SQL server
has Analysis Services which has Universal Dimensional Model (UDM), cube partitioning, data
mining and predictive analysis, what if modeling, key performance indicators, etc. Business
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intelligence development Studio (BIDS) was introduced with SQL Server 2005 to give a single
and integrated tool for development of SSIS, SQL Server Analysis Services (SSAS) and SQL
Server Reporting Services (SSRS) objects.
Figure 2: Microsoft BI End-to-End Offerings
SQL Server 2008 makes data available at any place, any time, and to any device to its customers.
It provides for a more trusted, scalable and available platform. With significant advancements in
key areas, SQL Server 2008 becomes a more productive, intelligent and enterprise data platform.The new features in SQL Server 2008 are added around the following four major themes.
Enterprise Data Platform - SQL Server 2008 provides a more reliable, secure, trusted
and scalable platform. It improves availability, using enhanced data mirroring,
predictable query performance, data and backup compression, and many development
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SQL Server Integration Services (SSIS) - ETL
SQL 2008 Database
SQL Server Reporting Services
(SSRS)
SQL Server Analysis Services
(SSAS)
SQL BI Platform
Scoreboards Dashboards ReportsExcel, pdf,
MS Word
Charts,
graphs
Excel Calculation Analytics Performance point server
Business Performance monitoring using performance application
Heterogeneous Data Sources (Oracle, DB2, CRM, File Sources etc.)
Share
Point
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features. Another innovative feature is Policy-based management, which enables an
easier SQL Server administration.
Beyond Relational - The features in this category cab handle any type of data, even
those that are unstructured and non relational. New data types are introduced to handle
geo spatial data, documents and image files ad well. It enables the developers to design
location intelligent applications and enhances the ability to handle the document
management.
Dynamic Development - Using the new .NET Framework 3.5 reduces the complexity of
the development with ADO.NET Entity Framework and Language Integrated Query
(LINQ) to SQL. ADO.NET Entity Framework enables the developers to become more
productive by directly interacting with the business entities. Developers can write
synchronizing applications by using features like change tracking.
Pervasive Insight - These features further enhance the SSIS (SQL Server Integration
Services), SSAS (SQL Server Analysis Services) and SSRS (SQL Server Reporting
Services), making them more scalable. They enable the enterprises to integrate all the
data into data warehouse more efficiently and enables real-time data analysis. It also
empowers every user with actionable insights.
6. Comparison of Microsoft Data Warehouse with IBM DB2
The comparison of Microsoft Data Warehouse Tool and IBM DB2 is made, based on various
aspects.
Total Cost of Ownership
SQL Server 2008 offers lower cost than IBM DB2 in each of the major areas that
contribute to total cost of ownership.
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SQL Server has a better total cost of ownership than IBM DB2 because of its lower
costs of administration and services.
SQL Server 2008 provides features that customers of IBM DB2 must buy as add-ins.
Flexible Licensing Model
In Microsoft licensing requirements are determined by the number of processors, and
not the number of cores. IBM has more complex licensing policies such as licensing
per core or by processor value unit, and customers can end up paying substantially
more for multi-core systems.
Simplified Product Line
SQL Server has a single well defined and easily understood database product line. Ithas SQL Server and integrated BI, but IBM lacks a tightly integrated/packaged BI
tools suite for DB2.
Price-Performance and Scalability
SQL Server 2008 is designed to scale reliably to meet the needs of the largest
organizations in the most demanding database environments.
SQL Server has a lead over IBM DB2 in price/performance
SQL Server 2008 enables enhanced analytical capabilities and supports more
complex computations and aggregations
High Availability
SQL Server 2008 offers high-availability features that are not offered by IBM DB2
Enhanced Manageability
Easier to manage and more productive than IBM DB2. For SMEs it is feasible to
deploy and manage many database applications without requiring external specialist
resources.
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7. A Case Study of Carl Zeiss Vision, North America
The Journey
Determined Need for Enterprise Data Warehouse Worked with Business Users to Understand Business Requirements
Determined Software Requirements
MS SQL Server 2005 & 2008
MS SSIS (ETL Tool)
MS SSAS (Analytic Cube Tool)MS SSRS & Excel (Reporting Tools)
SharePoint for Deploying Reports over Company Intranet
Designed and Developed zBis Data Warehouse
4 + 1 Steps Dimensional Design Process
Ralph Kimballs Process for Developing Star Schemas
Determine Business Process
Model business Processes
Each Process will determine 1 or more FactsDesign Data Warehouse by Business Process _ Not Business Unit
Identify the Grain of the Fact
What does 1 row in Fact table representTransactional or Summary
Design the Data Warehouse Dimensions
Design the Data Warehouse Facts
Determine Hierarchies
Customer Hierarchies Sales Channels
Distribution Channels
Business ChannelsCustomer Channels
Product DivisionsSales Organizations
Sales OfficeBuy Groups/Directly Purchase
Product Hierarchy
Manufacturer
Brand
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Product Type Each product type had own Hierarchy
Design
Make/Model
Geo Hierarchy
Sales DivisionSales Region
Sales Territory
Conformed Dimensions
Standardized dimensions across data warehouse
Dimensions are associated with multiple business processes
Determine by using Bus Matrix & enforced in ETL
Conformed Dimensions are shared and consistent across fact tables
Use Data Warehouse BUS Matrix
Use Data Warehouse BUS Matrix for
Understanding & mapping of Business Processes and Dimensions
Ongoing DW/BI planning effortsTeam & Management Communications
Understand Business Process unions across the enterprise
Date Company Customer Product Geo Dist Ctr Promo
Company
Sales
X X X X X X
Customer
Discounts
X X X X X X
Product
Cost
X X X X X X X
Company
Inventory
X X X
Dist Ctr
Inventory
X X X
Table 1: BUS Matrix
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Figure 3: Dimensional Schema
Slow Changing Dimensions
Type 1 Overwrite existing Dimension RowUse when dont need to keep history data row
Can be used to correct bad data
Type 2 Create a new Dimension Row
Use date and/or active non-active fields to identify current and inactive data rows
Type 3 Keep old and add new attributes in Dimension Row
Allow Alternate realities to exist simultaneously in one Dimension Row
Slow Changing Dimensions are handled in the ETL
Type of Dimensions
Mini-Dimension
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Junk Dimensions
Outrigger Dimensions
Small Static Dimensions
Lookup tables
Type of Facts
Transaction Fact Tables
Snapshot Fact Tables
Accumulating Snapshot Fact Tables
Consolidated or Aggregated Fact Tables
Figure 4: Bridge Tables
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Figure 5: Bridge Tables
8. Conclusion
Microsoft data warehouse is the most demanding data warehouse and business intelligence
applications in terms of performance, scalability, and security. Microsofts SQL Server product
has consistently maintained a leadership position in terms of growth in the database segment.
Tight integration with the Microsoft Visual Studio development environment improves
developer productivity and reduces database application development cycles. It provides rich
security architecture to help protect data and network resources.
References
A CIOview White Paper on CIOview: Should You Migrate from Sybase to SQL Server?
Alex Payne, Microsoft "Business Intelligence and Data Warehousing in SQL Server 2005"
published on 15 July, 2005 available at http://technet.microsoft.com/hi-in/library/bb545450
Bryan Thomas Solutions for Highly Scalable Database Applications An analysis ofarchitectures and technologies, Performance Tuning Corporation
Dr. Abhijit Chattaraj, Mr. Philip Cookson Comparing SQL Server 2008 to IBM DB2 9.5
SQL Server Technical Article published in May 2008
Elizabeth Diamond Architecting A Data Warehouse, A case study, September 9, 2009
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Paulraj Ponniah Data Warehousing Fundamentals A Comprehensive Guide for IT
Professionals
Microsoft SQL Server, available at http://en.wikipedia.org/wiki/Microsoft_SQL_Server
Mitch Kramer, Green Hill Analysis "A Comparison of Business Intelligence Strategies andPlatforms Comparing Microsoft, Oracle, IBM, and Hyperion",
Mitch Ruebush Comparing SQL Server 2005 and Oracle 10g as a Database Platform for
Microsoft .NET Developers - A Comparison of Developer Productivity published in April 2005
Sam Anahory, Dennis Murray Data Warehousing In The Real World A practical Guide for
Building Decision Support Systems, Pearson Education
SQL Server Fast Track Data Warehouse at http://www.microsoft.com/sqlserver/2008/en/
Virendra Wadkar, Phaneendra babu Sunivis, Nitesh Rai - "SQL Server 2008 BI Features"
Whitepaper on Microsofts SQL Server product has consistently maintained a leadership
position in terms of growth in the database segment, Revision 10, October 2004
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