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📄 Contents

  1. SQL Server Reference Guide
  2. Introduction
  3. SQL Server Reference Guide Overview
  4. Table of Contents
  5. Microsoft SQL Server Defined
  6. SQL Server Editions
  7. SQL Server Access
  8. Informit Articles and Sample Chapters
  9. Online Resources
  10. Microsoft SQL Server Features
  11. SQL Server Books Online
  12. Clustering Services
  13. Data Transformation Services (DTS) Overview
  14. Replication Services
  15. Database Mirroring
  16. Natural Language Processing (NLP)
  17. Analysis Services
  18. Microsot SQL Server Reporting Services
  19. XML Overview
  20. Notification Services for the DBA
  21. Full-Text Search
  22. SQL Server 2005 - Service Broker
  23. Using SQL Server as a Web Service
  24. SQL Server Encryption Options Overview
  25. SQL Server 2008 Overview
  26. SQL Server 2008 R2 Overview
  27. SQL Azure
  28. The Utility Control Point and Data Application Component, Part 1
  29. The Utility Control Point and Data Application Component, Part 2
  30. Microsoft SQL Server Administration
  31. The DBA Survival Guide: The 10 Minute SQL Server Overview
  32. Preparing (or Tuning) a Windows System for SQL Server, Part 1
  33. Preparing (or Tuning) a Windows System for SQL Server, Part 2
  34. Installing SQL Server
  35. Upgrading SQL Server
  36. SQL Server 2000 Management Tools
  37. SQL Server 2005 Management Tools
  38. SQL Server 2008 Management Tools
  39. SQL Azure Tools
  40. Automating Tasks with SQL Server Agent
  41. Run Operating System Commands in SQL Agent using PowerShell
  42. Automating Tasks Without SQL Server Agent
  43. Storage – SQL Server I/O
  44. Service Packs, Hotfixes and Cumulative Upgrades
  45. Tracking SQL Server Information with Error and Event Logs
  46. Change Management
  47. SQL Server Metadata, Part One
  48. SQL Server Meta-Data, Part Two
  49. Monitoring - SQL Server 2005 Dynamic Views and Functions
  50. Monitoring - Performance Monitor
  51. Unattended Performance Monitoring for SQL Server
  52. Monitoring - User-Defined Performance Counters
  53. Monitoring: SQL Server Activity Monitor
  54. SQL Server Instances
  55. DBCC Commands
  56. SQL Server and Mail
  57. Database Maintenance Checklist
  58. The Maintenance Wizard: SQL Server 2000 and Earlier
  59. The Maintenance Wizard: SQL Server 2005 (SP2) and Later
  60. The Web Assistant Wizard
  61. Creating Web Pages from SQL Server
  62. SQL Server Security
  63. Securing the SQL Server Platform, Part 1
  64. Securing the SQL Server Platform, Part 2
  65. SQL Server Security: Users and other Principals
  66. SQL Server Security – Roles
  67. SQL Server Security: Objects (Securables)
  68. Security: Using the Command Line
  69. SQL Server Security - Encrypting Connections
  70. SQL Server Security: Encrypting Data
  71. SQL Server Security Audit
  72. High Availability - SQL Server Clustering
  73. SQL Server Configuration, Part 1
  74. SQL Server Configuration, Part 2
  75. Database Configuration Options
  76. 32- vs 64-bit Computing for SQL Server
  77. SQL Server and Memory
  78. Performance Tuning: Introduction to Indexes
  79. Statistical Indexes
  80. Backup and Recovery
  81. Backup and Recovery Examples, Part One
  82. Backup and Recovery Examples, Part Two: Transferring Databases to Another System (Even Without Backups)
  83. SQL Profiler - Reverse Engineering An Application
  84. SQL Trace
  85. SQL Server Alerts
  86. Files and Filegroups
  87. Partitioning
  88. Full-Text Indexes
  89. Read-Only Data
  90. SQL Server Locks
  91. Monitoring Locking and Deadlocking
  92. Controlling Locks in SQL Server
  93. SQL Server Policy-Based Management, Part One
  94. SQL Server Policy-Based Management, Part Two
  95. SQL Server Policy-Based Management, Part Three
  96. Microsoft SQL Server Programming
  97. An Outline for Development
  98. Database
  99. Database Services
  100. Database Objects: Databases
  101. Database Objects: Tables
  102. Database Objects: Table Relationships
  103. Database Objects: Keys
  104. Database Objects: Constraints
  105. Database Objects: Data Types
  106. Database Objects: Views
  107. Database Objects: Stored Procedures
  108. Database Objects: Indexes
  109. Database Objects: User Defined Functions
  110. Database Objects: Triggers
  111. Database Design: Requirements, Entities, and Attributes
  112. Business Process Model Notation (BPMN) and the Data Professional
  113. Business Questions for Database Design, Part One
  114. Business Questions for Database Design, Part Two
  115. Database Design: Finalizing Requirements and Defining Relationships
  116. Database Design: Creating an Entity Relationship Diagram
  117. Database Design: The Logical ERD
  118. Database Design: Adjusting The Model
  119. Database Design: Normalizing the Model
  120. Creating The Physical Model
  121. Database Design: Changing Attributes to Columns
  122. Database Design: Creating The Physical Database
  123. Database Design Example: Curriculum Vitae
  124. NULLs
  125. The SQL Server Sample Databases
  126. The SQL Server Sample Databases: pubs
  127. The SQL Server Sample Databases: NorthWind
  128. The SQL Server Sample Databases: AdventureWorks
  129. The SQL Server Sample Databases: Adventureworks Derivatives
  130. UniversalDB: The Demo and Testing Database, Part 1
  131. UniversalDB: The Demo and Testing Database, Part 2
  132. UniversalDB: The Demo and Testing Database, Part 3
  133. UniversalDB: The Demo and Testing Database, Part 4
  134. Getting Started with Transact-SQL
  135. Transact-SQL: Data Definition Language (DDL) Basics
  136. Transact-SQL: Limiting Results
  137. Transact-SQL: More Operators
  138. Transact-SQL: Ordering and Aggregating Data
  139. Transact-SQL: Subqueries
  140. Transact-SQL: Joins
  141. Transact-SQL: Complex Joins - Building a View with Multiple JOINs
  142. Transact-SQL: Inserts, Updates, and Deletes
  143. An Introduction to the CLR in SQL Server 2005
  144. Design Elements Part 1: Programming Flow Overview, Code Format and Commenting your Code
  145. Design Elements Part 2: Controlling SQL's Scope
  146. Design Elements Part 3: Error Handling
  147. Design Elements Part 4: Variables
  148. Design Elements Part 5: Where Does The Code Live?
  149. Design Elements Part 6: Math Operators and Functions
  150. Design Elements Part 7: Statistical Functions
  151. Design Elements Part 8: Summarization Statistical Algorithms
  152. Design Elements Part 9:Representing Data with Statistical Algorithms
  153. Design Elements Part 10: Interpreting the Data—Regression
  154. Design Elements Part 11: String Manipulation
  155. Design Elements Part 12: Loops
  156. Design Elements Part 13: Recursion
  157. Design Elements Part 14: Arrays
  158. Design Elements Part 15: Event-Driven Programming Vs. Scheduled Processes
  159. Design Elements Part 16: Event-Driven Programming
  160. Design Elements Part 17: Program Flow
  161. Forming Queries Part 1: Design
  162. Forming Queries Part 2: Query Basics
  163. Forming Queries Part 3: Query Optimization
  164. Forming Queries Part 4: SET Options
  165. Forming Queries Part 5: Table Optimization Hints
  166. Using SQL Server Templates
  167. Transact-SQL Unit Testing
  168. Index Tuning Wizard
  169. Unicode and SQL Server
  170. SQL Server Development Tools
  171. The SQL Server Transact-SQL Debugger
  172. The Transact-SQL Debugger, Part 2
  173. Basic Troubleshooting for Transact-SQL Code
  174. An Introduction to Spatial Data in SQL Server 2008
  175. Performance Tuning
  176. Performance Tuning SQL Server: Tools and Processes
  177. Performance Tuning SQL Server: Tools Overview
  178. Creating a Performance Tuning Audit - Defining Components
  179. Creating a Performance Tuning Audit - Evaluation Part One
  180. Creating a Performance Tuning Audit - Evaluation Part Two
  181. Creating a Performance Tuning Audit - Interpretation
  182. Creating a Performance Tuning Audit - Developing an Action Plan
  183. Understanding SQL Server Query Plans
  184. Performance Tuning: Implementing Indexes
  185. Performance Monitoring Tools: Windows 2008 (and Higher) Server Utilities, Part 1
  186. Performance Monitoring Tools: Windows 2008 (and Higher) Server Utilities, Part 2
  187. Performance Monitoring Tools: Windows System Monitor
  188. Performance Monitoring Tools: Logging with System Monitor
  189. Performance Monitoring Tools: User Defined Counters
  190. General Transact-SQL (T-SQL) Performance Tuning, Part 1
  191. General Transact-SQL (T-SQL) Performance Tuning, Part 2
  192. General Transact-SQL (T-SQL) Performance Tuning, Part 3
  193. Performance Monitoring Tools: An Introduction to SQL Profiler
  194. Performance Tuning: Introduction to Indexes
  195. Performance Monitoring Tools: SQL Server 2000 Index Tuning Wizard
  196. Performance Monitoring Tools: SQL Server 2005 Database Tuning Advisor
  197. Performance Monitoring Tools: SQL Server Management Studio Reports
  198. Performance Monitoring Tools: SQL Server 2008 Activity Monitor
  199. The SQL Server 2008 Management Data Warehouse and Data Collector
  200. Performance Monitoring Tools: Evaluating Wait States with PowerShell and Excel
  201. Practical Applications
  202. Choosing the Back End
  203. The DBA's Toolbox, Part 1
  204. The DBA's Toolbox, Part 2
  205. Scripting Solutions for SQL Server
  206. Building a SQL Server Lab
  207. Using Graphics Files with SQL Server
  208. Enterprise Resource Planning
  209. Customer Relationship Management (CRM)
  210. Building a Reporting Data Server
  211. Building a Database Documenter, Part 1
  212. Building a Database Documenter, Part 2
  213. Data Management Objects
  214. Data Management Objects: The Server Object
  215. Data Management Objects: Server Object Methods
  216. Data Management Objects: Collections and the Database Object
  217. Data Management Objects: Database Information
  218. Data Management Objects: Database Control
  219. Data Management Objects: Database Maintenance
  220. Data Management Objects: Logging the Process
  221. Data Management Objects: Running SQL Statements
  222. Data Management Objects: Multiple Row Returns
  223. Data Management Objects: Other Database Objects
  224. Data Management Objects: Security
  225. Data Management Objects: Scripting
  226. Powershell and SQL Server - Overview
  227. PowerShell and SQL Server - Objects and Providers
  228. Powershell and SQL Server - A Script Framework
  229. Powershell and SQL Server - Logging the Process
  230. Powershell and SQL Server - Reading a Control File
  231. Powershell and SQL Server - SQL Server Access
  232. Powershell and SQL Server - Web Pages from a SQL Query
  233. Powershell and SQL Server - Scrubbing the Event Logs
  234. SQL Server 2008 PowerShell Provider
  235. SQL Server I/O: Importing and Exporting Data
  236. SQL Server I/O: XML in Database Terms
  237. SQL Server I/O: Creating XML Output
  238. SQL Server I/O: Reading XML Documents
  239. SQL Server I/O: Using XML Control Mechanisms
  240. SQL Server I/O: Creating Hierarchies
  241. SQL Server I/O: Using HTTP with SQL Server XML
  242. SQL Server I/O: Using HTTP with SQL Server XML Templates
  243. SQL Server I/O: Remote Queries
  244. SQL Server I/O: Working with Text Files
  245. Using Microsoft SQL Server on Handheld Devices
  246. Front-Ends 101: Microsoft Access
  247. Comparing Two SQL Server Databases
  248. English Query - Part 1
  249. English Query - Part 2
  250. English Query - Part 3
  251. English Query - Part 4
  252. English Query - Part 5
  253. RSS Feeds from SQL Server
  254. Using SQL Server Agent to Monitor Backups
  255. Reporting Services - Creating a Maintenance Report
  256. SQL Server Chargeback Strategies, Part 1
  257. SQL Server Chargeback Strategies, Part 2
  258. SQL Server Replication Example
  259. Creating a Master Agent and Alert Server
  260. The SQL Server Central Management System: Definition
  261. The SQL Server Central Management System: Base Tables
  262. The SQL Server Central Management System: Execution of Server Information (Part 1)
  263. The SQL Server Central Management System: Execution of Server Information (Part 2)
  264. The SQL Server Central Management System: Collecting Performance Metrics
  265. The SQL Server Central Management System: Centralizing Agent Jobs, Events and Scripts
  266. The SQL Server Central Management System: Reporting the Data and Project Summary
  267. Time Tracking for SQL Server Operations
  268. Migrating Departmental Data Stores to SQL Server
  269. Migrating Departmental Data Stores to SQL Server: Model the System
  270. Migrating Departmental Data Stores to SQL Server: Model the System, Continued
  271. Migrating Departmental Data Stores to SQL Server: Decide on the Destination
  272. Migrating Departmental Data Stores to SQL Server: Design the ETL
  273. Migrating Departmental Data Stores to SQL Server: Design the ETL, Continued
  274. Migrating Departmental Data Stores to SQL Server: Attach the Front End, Test, and Monitor
  275. Tracking SQL Server Timed Events, Part 1
  276. Tracking SQL Server Timed Events, Part 2
  277. Patterns and Practices for the Data Professional
  278. Managing Vendor Databases
  279. Consolidation Options
  280. Connecting to a SQL Azure Database from Microsoft Access
  281. SharePoint 2007 and SQL Server, Part One
  282. SharePoint 2007 and SQL Server, Part Two
  283. SharePoint 2007 and SQL Server, Part Three
  284. Querying Multiple Data Sources from a Single Location (Distributed Queries)
  285. Importing and Exporting Data for SQL Azure
  286. Working on Distributed Teams
  287. Professional Development
  288. Becoming a DBA
  289. Certification
  290. DBA Levels
  291. Becoming a Data Professional
  292. SQL Server Professional Development Plan, Part 1
  293. SQL Server Professional Development Plan, Part 2
  294. SQL Server Professional Development Plan, Part 3
  295. Evaluating Technical Options
  296. System Sizing
  297. Creating a Disaster Recovery Plan
  298. Anatomy of a Disaster (Response Plan)
  299. Database Troubleshooting
  300. Conducting an Effective Code Review
  301. Developing an Exit Strategy
  302. Data Retention Strategy
  303. Keeping Your DBA/Developer Job in Troubled Times
  304. The SQL Server Runbook
  305. Creating and Maintaining a SQL Server Configuration History, Part 1
  306. Creating and Maintaining a SQL Server Configuration History, Part 2
  307. Creating an Application Profile, Part 1
  308. Creating an Application Profile, Part 2
  309. How to Attend a Technical Conference
  310. Tips for Maximizing Your IT Budget This Year
  311. The Importance of Blue-Sky Planning
  312. Application Architecture Assessments
  313. Transact-SQL Code Reviews, Part One
  314. Transact-SQL Code Reviews, Part Two
  315. Cloud Computing (Distributed Computing) Paradigms
  316. NoSQL for the SQL Server Professional, Part One
  317. NoSQL for the SQL Server Professional, Part Two
  318. Object-Role Modeling (ORM) for the Database Professional
  319. Business Intelligence
  320. BI Explained
  321. Developing a Data Dictionary
  322. BI Security
  323. Gathering BI Requirements
  324. Source System Extracts and Transforms
  325. ETL Mechanisms
  326. Business Intelligence Landscapes
  327. Business Intelligence Layouts and the Build or Buy Decision
  328. A Single Version of the Truth
  329. The Operational Data Store (ODS)
  330. Data Marts – Combining and Transforming Data
  331. Designing Data Elements
  332. The Enterprise Data Warehouse — Aggregations and the Star Schema
  333. On-Line Analytical Processing (OLAP)
  334. Data Mining
  335. Key Performance Indicators
  336. BI Presentation - Client Tools
  337. BI Presentation - Portals
  338. Implementing ETL - Introduction to SQL Server 2005 Integration Services
  339. Building a Business Intelligence Solution, Part 1
  340. Building a Business Intelligence Solution, Part 2
  341. Building a Business Intelligence Solution, Part 3
  342. Tips and Troubleshooting
  343. SQL Server and Microsoft Excel Integration
  344. Tips for the SQL Server Tools: SQL Server 2000
  345. Tips for the SQL Server Tools – SQL Server 2005
  346. Transaction Log Troubles
  347. SQL Server Connection Problems
  348. Orphaned Database Users
  349. Additional Resources
  350. Tools and Downloads
  351. Utilities (Free)
  352. Tool Review (Free): DBDesignerFork
  353. Aqua Data Studio
  354. Microsoft SQL Server Best Practices Analyzer
  355. Utilities (Cost)
  356. Quest Software's TOAD for SQL Server
  357. Quest Software's Spotlight on SQL Server
  358. SQL Server on Microsoft's Virtual PC
  359. Red Gate SQL Bundle
  360. Microsoft's Visio for Database Folks
  361. Quest Capacity Manager
  362. SQL Server Help
  363. Visual Studio Team Edition for Database Professionals
  364. Microsoft Assessment and Planning Solution Accelerator
  365. Aggregating Server Data from the MAPS Tool

In previous entries in this series I've explained how important it is to involve the business in developing your Business Intelligence (BI) landscape. In the next few tutorials I'll cover more of the technical and physical aspects of the process, but we need to talk about a concept you will run into when you in your design process: "A single version of the truth". This phrased is most often used by either the business side of your organization in meetings or by a vendor of a BI system.

Let's first examine the intent of this statement and then dig a little further into the reality you'll face when you try to implement it.

Many businesses decide they need an analytical system (BI) when they realize how much data they are storing, and begin to understand that they may not be getting the most information out of it that they can. As I've mentioned, as a technical professional it's important that you steer this conversation towards these general stages:

  • Solid data strategy
  • Solid reporting strategy
  • Solid analytical strategy

I was a consultant for a few years, and in almost every case a business that wanted (or thought they wanted) an analytical system did not have the first two strategies mapped out or implemented properly. In the data strategy, you're thinking about what you store, where you store it, how it is accessed, and how it is protected. You must start here because if the base data are incorrect, any numeric calculations made on them will be even more incorrect. This is often called a "drift error", and you'll see it quite often in statistics. Taking the average of two incorrect numbers is even further from the truth than the incorrect numbers themselves, and this error is made even worse if the consumer does not know that the original numbers are wrong.

The data strategy includes archiving, access and protection – all of these play into the analytical system, since the BI landscape derives its information from the base data. If the data isn't there, or can be tampered with, once again the subsequent decisions will be incomplete or incorrect.

The second strategy of reporting is equally important. About 40-50% of the engagements I've been on could be solved with solid reporting, rather than implementing a BI solution. In most cases management (and even the whole organization) wasn't even aware of what reports were available, who was using them, or how. A good reporting strategy, in fact, can form the basis of your BI system. Knowing which questions can be answered by a simple report and which need an analytical approach is one of the first steps in your design.

This brings us to the analytical system and the desire on the part of management for that single version of the truth. By that they normally mean a system of record – one that shows the exact amounts of something or at what time of the month things happen and so on. They mean that when we say we have 300 widgets in stock we really have 300 physical widgets on a shelf somewhere.

This kind of information is highly desirable. You and I do this all the time when we make our grocery lists: we see if we have any pasta on the shelf, and if we don't, we buy more. That knowledge makes our decision for us. You can imagine that in a complex organization of thousands of people spread around the world, with regulations, laws, accounting standards and so on that you would really want to be able to know absolute information about inventory, headcount, income and expenses and so on.

But as desirable as this information might be, it isn't always possible. While you and I can look in our cabinet to see if we have any pasta, imagine trying to count the boxes of pasta in all of the cabinets in your entire city, or even just in your neighborhood. What if the boxes are already opened? Do you count those? What if they only have a very small amount? Do you combine all of the mostly-empty boxes in all the cabinets to make a new one? And what is pasta, anyway? Do the cans of pre-prepared dishes with pasta in them count?

You can see even in this simple sample that it is less intuitive than you might think to count up a single item of inventory. Now what if you are a manufacturing plant, and you count the parts you build things with. What do you count? The completed units, the individual parts, or both? How do you account for which stage of the manufacturing process they are in when they are neither a single part nor a completed unit?

And this doesn't even deal with things like accounting, where you have currency differences among countries and so on. Do you take the spot price, the daily average, an agreed-on "leveling" currency or some other method?

And even if you answered these questions definitively, you should resist the urge to do so. The time will come when that definition won't work anymore. You'll absorb another company, the laws or even the governments will change.

This is difficult to explain to a management team, but it can be done, especially if you use examples. Since the "pasta" example might be deemed too silly for a high-level meeting (or perhaps not), you can lead them through an exercise of discovering this for themselves. It all depends, of course, on the type of organization you're in, but once you've convinced them to consider the other two strategies (data and reporting) you can ask them to begin to define terms like "currency", "inventory" and "headcount" very specifically. Take notes, and then read that back to them, prodding them with questions like: "so headcount is the number of people employed by the firm on a given date. Does that include contractors and part-time employees? In all situations?" You'll normally get a slight pause while they think that through, and then come to the understanding that "perhaps not" is the right response.

You can't just leave them there, however. Once they understand what the issue is, you can make two broad suggestions for dealing with the issue.

The first method you can use is to break apart the single concepts into multiple views, reports, or slices of data. You can say: We have a single version of the truth, but we have a lot of qualifications of that truth. for instance, you might have a view that shows the number of full-time employees, another that shows the number of contractors, and so on. You might even want to put those as "levels" (which we'll study later) and then roll them up to a single report of "headcount". The analyst can then drill down into those levels to see the qualifications of that "truth".

This becomes a bit ridiculous after a while, however. Suppose you're asked to attend a dinner at a friend's house. You reply: "Yes, but only if it doesn't rain, the dinner is after 6:00, my daughter doesn't have any homework, I feel like it and my wife will go. Then I'll come." Your friend would have no idea if you're coming or not!

Normally the better solution is to accept that there may be multiple versions of the truth. You'll design your information so that it fits the best definition of the common understanding that the organization has of the concept, and then create more views as warranted. You're not looking to eliminate ambiguity; you're trying to minimize it.

So what does this mean? Let's take the example of current cash-on-hand. The major problem with this number in a global organization is multiple currencies. Depending on how you convert those currencies (since they fluctuate against each other all the time) you can end up with different numbers. So what you do is pick the conversion rate (average, spot, moving average, etc.) that the users of the particular view or report care about the most. You may have one view for accounting, another for management, another for budgeting and so on. Each of these might report a slightly different number, which suits the question at hand.

Which brings us all the way around to the start again – you have to do two things before you embark on any kind of analytic system: get those requirements nailed down carefully and force the business to define their terms. There is simply no way you can do this for them. If they will do this, you can deliver a great system that they can trust – with or without a "single version of the truth."

InformIT Tutorials and Sample Chapters – A Single Version of the Truth

This book seems to be an interesting take on BI: Internet-Enabled Business Intelligence, by William A. Giovinazzo.

Online Resources – A Single Version of the Truth

There's a great reference for all things BI here.

InformIT Promotional Mailings & Special Offers

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  • To exercise its legal rights, including enforcement of the Terms of Use for this site or another contract
  • To affiliated Pearson companies and other companies and organizations who perform work for Pearson and are obligated to protect the privacy of personal information consistent with this Privacy Notice
  • To a school, organization, company or government agency, where Pearson collects or processes the personal information in a school setting or on behalf of such organization, company or government agency.

Links


This web site contains links to other sites. Please be aware that we are not responsible for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every web site that collects Personal Information. This privacy statement applies solely to information collected by this web site.

Requests and Contact


Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice


We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020