MISM 621_Microsoft Data Warehouse Tool_Group 8

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

[email protected]

Shrestha Rath

[email protected]

Sowmya S.

[email protected]

Sukritha S.

[email protected]
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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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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Documents

MISM 621_Microsoft Data Warehouse Tool_Group 8