標(biāo)題: Titlebook: Building a Data Warehouse; With Examples in SQL Vincent Rainardi Book 2008 Vincent Rainardi 2008 DBMS.Microsoft SQL Server.Reporting Servic [打印本頁] 作者: 抵押證書 時(shí)間: 2025-3-21 17:19
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作者: 一條卷發(fā) 時(shí)間: 2025-3-21 22:37 作者: recession 時(shí)間: 2025-3-22 03:15
Physical Database Design,ment those data stores physically as SQL Server databases. For an experienced DBA, this should not be a problem. In the previous chapter, we defined all the columns, all the data types, and the relationships between tables. It should be quite straightforward to now create those tables, right?作者: 有害 時(shí)間: 2025-3-22 05:47 作者: Stress 時(shí)間: 2025-3-22 12:48 作者: nautical 時(shí)間: 2025-3-22 16:10 作者: LUMEN 時(shí)間: 2025-3-22 18:40 作者: 落葉劑 時(shí)間: 2025-3-23 00:00 作者: choleretic 時(shí)間: 2025-3-23 04:21
Data Warehouse Administration,t, the BI manager creates the user guide, and the development team writes the system documentation and the support manual. Second, the business intelligence manager (BIM) trains the business users, and the development team trains the data warehouse administrator (DWA) and support desk personnel. Fin作者: Anthropoid 時(shí)間: 2025-3-23 08:56 作者: 庇護(hù) 時(shí)間: 2025-3-23 12:23 作者: STENT 時(shí)間: 2025-3-23 17:49
Mathematics and Statistics for Sciencesiness (for example, a school or university, government agency, nonprofit organization, social club, political party, and so on), you can replace the word . in the earlier definition with ., and so on, whichever is most appropriate.作者: Functional 時(shí)間: 2025-3-23 18:45
ood.The code in the book will save companies hundreds of hou.Building a Data Warehouse: With Examples in SQL Server. describes how to build a data warehouse completely from scratch and shows practical examples on how to do it. Author .Vincent Rainardi. also describes some practical issues he has exp作者: NEXUS 時(shí)間: 2025-3-24 01:16 作者: 議程 時(shí)間: 2025-3-24 06:23
Data Warehouse Administration,igence manager (BIM) trains the business users, and the development team trains the data warehouse administrator (DWA) and support desk personnel. Finally, the DWA sets up the users, and the data warehouse goes into operation.作者: 討好美人 時(shí)間: 2025-3-24 06:44
Multidimensional Database,ey are for, how to design them, how to populate them, and how to query them, you need to remember that the final purpose of data warehousing is to get the data to the users, not to get the data into the warehouse.作者: 小隔間 時(shí)間: 2025-3-24 13:30 作者: 實(shí)現(xiàn) 時(shí)間: 2025-3-24 16:53
Book 2008mple, extracting from source systems, loading the data stores, maintaining data quality, and utilizing the metadata. After you populate the data warehouse, in chapters 11 through 15, you explore how to present data to users using reports and multidimensional databases and how to use the data in the 作者: 陰謀 時(shí)間: 2025-3-24 19:10
nd utilizing the metadata. After you populate the data warehouse, in chapters 11 through 15, you explore how to present data to users using reports and multidimensional databases and how to use the data in the 978-1-4302-1196-9978-1-4302-0528-9作者: groggy 時(shí)間: 2025-3-24 23:57
Data Warehouse Architecture,nged within a data warehouse and how the data flows from the source systems to the users through these data stores. The . is about the physical configuration of the servers, network, software, storage, and clients. In this chapter, I will discuss the data flow architecture first and then the system architecture.作者: 使堅(jiān)硬 時(shí)間: 2025-3-25 05:34 作者: dyspareunia 時(shí)間: 2025-3-25 10:01
Physical Database Design,ment those data stores physically as SQL Server databases. For an experienced DBA, this should not be a problem. In the previous chapter, we defined all the columns, all the data types, and the relationships between tables. It should be quite straightforward to now create those tables, right?作者: INERT 時(shí)間: 2025-3-25 13:17 作者: 夸張 時(shí)間: 2025-3-25 17:33 作者: 解凍 時(shí)間: 2025-3-25 21:27 作者: innovation 時(shí)間: 2025-3-26 02:58 作者: 易怒 時(shí)間: 2025-3-26 05:56
Alan D. Taylor,Allison M. Pacellit is important to define functional and nonfunctional requirements when building a data warehouse system to make sure that the system we build will help users achieve the business objectives. . define what the system does. They contain the features that the data warehouse system should have. . guide and constrain the architecture.作者: 協(xié)奏曲 時(shí)間: 2025-3-26 10:29
https://doi.org/10.1007/978-0-387-77645-3n this chapter, we will design the data stores for the Amadeus Entertainment case study. We will use the NDS + DDS architecture. Apart from the benefits outlined in Chapter 2, the purpose of choosing this architecture for this case study is so that you can have the experience of designing a normalized store and a dimensional store.作者: 比目魚 時(shí)間: 2025-3-26 15:36 作者: 殺人 時(shí)間: 2025-3-26 17:47
https://doi.org/10.1007/978-0-387-77645-3Now that we have extracted the data from the source system, we’ll populate the normalized data store and dimensional data store with the data we have extracted. In this chapter, I will discuss five main subjects regarding data warehouse population in the sequence they occur in a data warehouse system:作者: 使更活躍 時(shí)間: 2025-3-26 23:21 作者: 施舍 時(shí)間: 2025-3-27 01:18 作者: Indelible 時(shí)間: 2025-3-27 07:13 作者: 遭遇 時(shí)間: 2025-3-27 10:14 作者: NAG 時(shí)間: 2025-3-27 16:52
Functional and Nonfunctional Requirements,t is important to define functional and nonfunctional requirements when building a data warehouse system to make sure that the system we build will help users achieve the business objectives. . define what the system does. They contain the features that the data warehouse system should have. . guide and constrain the architecture.作者: 宿醉 時(shí)間: 2025-3-27 19:53
Data Modeling,n this chapter, we will design the data stores for the Amadeus Entertainment case study. We will use the NDS + DDS architecture. Apart from the benefits outlined in Chapter 2, the purpose of choosing this architecture for this case study is so that you can have the experience of designing a normalized store and a dimensional store.作者: 放肆的我 時(shí)間: 2025-3-27 23:41
Data Extraction,ow that we have created the tables in the NDS and the DDS, it is time to populate them. Before we can populate them, though, we need to retrieve the data from the source system. This is what data extraction is all about.作者: Excise 時(shí)間: 2025-3-28 05:29 作者: 沒花的是打擾 時(shí)間: 2025-3-28 08:20 作者: 安定 時(shí)間: 2025-3-28 14:04 作者: DOSE 時(shí)間: 2025-3-28 17:18
Testing Your Data Warehouse,s with any other IT system, after you build the data warehouse with its ETL and applications, you need to test it thoroughly. You need to go through six types of testing. I’ll introduce them here with a brief description, and in the rest of the chapter I will discuss them one by one:作者: 發(fā)誓放棄 時(shí)間: 2025-3-28 21:56
https://doi.org/10.1007/978-0-387-77645-3nged within a data warehouse and how the data flows from the source systems to the users through these data stores. The . is about the physical configuration of the servers, network, software, storage, and clients. In this chapter, I will discuss the data flow architecture first and then the system 作者: deciduous 時(shí)間: 2025-3-29 02:54
https://doi.org/10.1007/978-0-387-77645-3ature of the data in the organization, not to suit the people. I believe that all IT systems of any kind need to be built to suit the users. A system must be usable. If the system is not used, there is no point in building it. This usability concept is fundamental to this chapter, so keep that in mi作者: 投票 時(shí)間: 2025-3-29 04:37
https://doi.org/10.1007/978-0-387-77645-3ment those data stores physically as SQL Server databases. For an experienced DBA, this should not be a problem. In the previous chapter, we defined all the columns, all the data types, and the relationships between tables. It should be quite straightforward to now create those tables, right?作者: considerable 時(shí)間: 2025-3-29 10:50 作者: 媽媽不開心 時(shí)間: 2025-3-29 14:33
Measurement, rounding and uncertaintyents, designing the data models, and creating the databases. In the past few chapters, I discussed how to populate the data warehouse, including extracting from the source system, loading the data stores, maintaining the data quality, and utilizing the metadata.作者: badinage 時(shí)間: 2025-3-29 15:44
https://doi.org/10.1007/978-3-031-05318-4o the users. In this chapter, I will discuss another popular way of getting the data out—using multidimensional databases (MDBs). Multidimensional databases are mainly used for analytics and data mining applications. While you are learning in this chapter what multidimensional databases are, what th作者: Facet-Joints 時(shí)間: 2025-3-29 20:53 作者: PANT 時(shí)間: 2025-3-30 00:16
Mathematics and Statistics for Sciencect new customers, performing business transactions with customers, servicing customers, and providing support to customers. Customers are the people (or parties) who a company or an organization serves; they’re the ones who consume its products or services. If the organization is not a company or bu作者: 侵略者 時(shí)間: 2025-3-30 07:55
Madona Chartouny,Iman Osta,Nawal Abou Raadt, the BI manager creates the user guide, and the development team writes the system documentation and the support manual. Second, the business intelligence manager (BIM) trains the business users, and the development team trains the data warehouse administrator (DWA) and support desk personnel. Fin作者: Mets552 時(shí)間: 2025-3-30 10:53 作者: Fissure 時(shí)間: 2025-3-30 14:25
978-1-4302-1196-9Vincent Rainardi 2008作者: AVANT 時(shí)間: 2025-3-30 20:06
Vincent RainardiThe only book that shows how to implement a data warehouse using SQL Server.Interest in this topic for SQL Server is high and poorly understood.The code in the book will save companies hundreds of hou作者: 擴(kuò)音器 時(shí)間: 2025-3-30 21:06 作者: 刪除 時(shí)間: 2025-3-31 04:04
https://doi.org/10.1007/978-0-387-77645-3nged within a data warehouse and how the data flows from the source systems to the users through these data stores. The . is about the physical configuration of the servers, network, software, storage, and clients. In this chapter, I will discuss the data flow architecture first and then the system architecture.
