Microsoft SQL Server 2014 BI入门指南：数据仓库与商业智能实践

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《Microsoft SQL Server 2014 商业智能开发入门指南》是一本针对初学者编写的实用手册，由Reza Rad撰写，由BIRMINGHAM-MUMBAI出版。该书旨在帮助读者深入了解Microsoft的商业智能（BI）技术和数据仓库技术，提供了一个打开数据仓库和商业智能世界大门的清晰路径。通过这本书，读者可以学习如何有效地开发和利用Microsoft SQL Server 2014进行数据分析、报告生成和决策支持。本书的核心内容涵盖了以下几个方面： 1. **Microsoft SQL Server 2014简介**：书中首先介绍了SQL Server 2014的基本架构和功能，包括关系型数据库管理系统（RDBMS），数据集成、处理和存储能力，以及与BI工具的集成。 2. **数据仓库基础**：章节中详细解释了数据仓库的概念，包括其在组织中的角色、ETL（提取、转换、加载）过程，以及如何构建数据仓库架构以支持BI分析。 3. **商业智能工具**：作者会指导读者如何使用SQL Server的内置BI工具，如SQL Server Reporting Services (SSRS)、Power BI Desktop和Data Analysis Expressions (DAX)，进行数据可视化和报告创建。 4. **查询和分析**：通过实例演示，读者将学会编写复杂的T-SQL查询，以及如何运用SQL Server的分析服务（如SSAS）进行多维建模和OLAP（在线分析处理）。 5. **数据挖掘和预测分析**：书中还涉及了使用SQL Server的数据挖掘和机器学习功能，帮助用户发掘隐藏在大量数据中的模式和趋势。 6. **安全性和管理**：为了确保数据的安全和有效管理，本书也会介绍SQL Server 2014的权限设置、备份恢复策略以及性能优化技巧。 7. **案例研究和实战项目**：通过一系列实际操作案例，读者可以将所学知识应用到真实场景中，提升实践能力。版权信息部分强调，未经出版商Packt Publishing事先书面许可，书中的任何部分不得以任何形式复制、存储或传输，除非用于批评性引用。同时，尽管作者和出版社已尽最大努力保证信息的准确性，但不承担因使用本书内容导致的直接或间接损失的责任。《Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide》是一本全面且实用的教程，适合想要入门商业智能领域并掌握SQL Server 2014技术的开发者和分析师使用。随着商业智能在企业决策过程中的日益重要，掌握这些技能对于职业发展具有重要意义。

Preface

Business Intelligence (BI) is one of the hoest topics nowadays in the Informaon Technology

eld. Many companies and organizaons intend to ulize a BI system to solve problems and

help decision makers make decisions. This high demand for BI systems has raised the number

of job openings in this eld.

The following is Gartner's denion of Business Intelligence

(http://www.gartner.com/it-glossary/business-intelligence-bi/):

Business Intelligence (BI) is an umbrella term that includes the applicaons,

infrastructure and tools, and best pracces that enable access and analysis of

informaon to improve and opmize decisions and performance.

There are various reasons to have a BI system in place, but helping decision makers to

make beer decisions is one of the main purposes of BI. As an example, a director of a

manufacturing company would like to understand the trend of sales in past months (or

years) on specic products. This trend would be helpful for him to decide any changes

in that product or to create some other edions of that product. A bank directory might like

to use data mining soluons to disnguish suspicious or fraudulent transacons. A board of

directors would be interested to see Key Performance Indicators (KPIs) of their business.

BI could help in all the scenarios menoned here and many more. A BI system usually

uses a data warehouse as a core tool. The data warehouse is an integrated dimensional

data structure. Data from a variety of sources will be fed into the data warehouse and some

data quality and governance would be applied on the data. The dimensional model of data

warehousing is opmized for reporng and analysis, so data visualizaon tools can directly

query against the data warehouse. Another layer of modeling might be added to the BI

architecture, OnLine Analycal Processing (OLAP), or the tabular model. These models

will improve data access in terms of speed and performance of queries. BI systems have

one or more data visualizaon frontends that will be the GUI for the end user.

In this book, we will go through the BI architecture and explore the Microso technologies

that can implement and deliver BI soluons.

www.it-ebooks.info

Preface

[ 2 ]

What this book covers

Chapter 1, Data Warehouse Design, explains the rst steps in thinking and designing a

BI system. As the rst steps, a developer needs to design the data warehouse (DW) and

needs an understanding of the key concepts of the design and methodologies to create

the data warehouse.

Chapter 2, SQL Server Analysis Services Muldimensional Cube Development, explains

how an OLAP muldimensional structure is required to provide fast query response and

aggregated data from a data warehouse. In this chapter, readers will learn what OLAP

provides and how to design OLAP with Microso SSAS Muldimensional.

Chapter 3, Tabular Model Development of SQL Server Analysis Services, explains that SSAS

Tabular is a new method of presenng data in Microso BI 2012 and is very useful in small

BI systems and when a developer wants to create POC. In this chapter, the reader will learn

about SSAS Tabular and how to use it in BI projects.

Chapter 4, ETL with Integraon Services, describes how ETL is an operaon of transferring

and integrang data from source systems into the data warehouse. ETL needs to be done

on a scheduled basis. In this chapter, readers learn how to think about ETL processes and

use SSIS to perform data transfers.

Chapter 5, Master Data Management, guides readers on how to manage reference data.

Master Data Management (MDM) is very crical in all integrated systems, especially in BI and

data warehouse. In this chapter, the reader will learn how to use Master Data Services (MDS)

to implement an MDM soluon.

Chapter 6, Data Quality and Data Cleansing, explains that data quality is one of the biggest

concerns of database systems. The data should be cleansed to be reliable through the data

warehouse. In this chapter, readers will learn about data cleansing and how to use Data

Quality Services (DQS), which is one of the new services of SQL Server 2012, to apply data

cleansing on data warehouse.

Chapter 7, Data Mining – Descripve Models in SSAS, provides a descripve model on

historical events. In this chapter, readers will understand data mining concepts and how to

use data mining algorithms to understand the relaonship between historical data, and how

to analyze it using Microso technologies.

Chapter 8, Idenfying Data Paerns – Predicve Models in SSAS, focuses on predicng future

outcomes based on a paern recognized in the exisng data. In this chapter, readers will

become familiar with algorithms that help in predicon, and how to use them and customize

them with parameters. Users will also understand how to compare models together to nd

the best algorithm for the case.

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Preface

[ 3 ]

Chapter 9, Reporng Services, explores Reporng Services, one of the key tools of the

Microso BI toolset, which provides dierent types of reports with charts and grouping

opons. In this chapter, readers will learn when and how to use SSRS to create and

design reports from data warehouses, SSAS Muldimensional, or SSAS Tabular.

Chapter 10, Dashboard Design, describes how dashboards are one of the most popular

and useful methods of visualizing data. In this chapter, readers will learn when to use

dashboards, how to visualize data with dashboards, and how to use PerformancePoint

and Power View to create dashboards.

Chapter 11, Power BI, explains how predesigned reports and dashboards are good for

business users, but power users require more exibility. Power BI is a new self-service BI

tool. In this chapter, you will learn about Power Query as a self-service ETL tool and Power

Map as a 3D geospaal data visualizaon tool.

Chapter 12, Integrang Reports in Applicaons, begins with the premise that reports and

dashboards are always required in custom applicaons. This chapter explains dierent ways

to integrate SSRS reports and other dashboards into C# or VB.NET applicaons in web or

Metro applicaons to provide reports on the applicaon side for the users.

What you need for this book

This book will explain the features of Microso SQL Server 2014 Enterprise Edion. However,

you can also download and install MS SQL Server 2014 Evaluaon Edion, which has the

same funconalies but is free for the rst 180 days, from the following link:

http://technet.microsoft.com/en-US/evalcenter/dn205290.aspx

There are many examples in this book and all of the examples use the following databases as

a source:

 AdventureWorks2012

 AdventureWorksDW2012

 AdventureWorksLT2012

You can download the database les from the following link:

http://msftdbprodsamples.codeplex.com/releases/view/55330

Aer downloading the database les, open SQL Server Management Studio and enter the

following scripts to create databases from their data les:

CREATE DATABASE AdventureWorks2012 ON (FILENAME = '{drive}:\

{file path}\AdventureWorks2012_Data.mdf')

FOR ATTACH_REBUILD_LOG;

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