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Data Warehousing

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Module 1: Introduction to Data Warehousing and OLAP

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The staging area, or data preparation area, is a collection of processes that cleans, transforms, combines, and prepares source data for use in the data warehouse or data mart. Can be included (one or many subject-specific data marts) in a data warehouse.. In the previous section, you learned about data warehousing and the flow of data from source systems to users. This section focuses on one area of the data warehouse—the OLAP database. Fact Table Components. Fact table components.

Oracle - Building A Banking Customer Relationship Data Warehouse - A Case Study - White Paper (pdf)

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The Data Warehouse framework will enable both Business Development and Direct Marketing officials to enhance their understanding of data warehousing concepts, and set in motion a tactical plan to support the Bank’s efforts in merging its marketing and IT capabilities.. One of the fundamental milestones of any Data Warehousing engagement is the collection of business requirements and Organization’s commitment to the project with appointment of a project sponsor.

Microsoft SQL Server 2000 Data Transformation Services- P1

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Tim Peterson is one of the owners of SDG Computing, Inc., a company specializing in Microsoft SQL Server data warehousing consulting and development. He worked on his first data warehousing project in 1995, using SQL Server 6.0.. Tim is a Microsoft Certified Trainer who teaches courses in the field of SQL Server data ware- housing (DTS, Analysis Services, OLAP, Data Mining, and MDX). Data Transformation Services in Microsoft SQL Server 2000 is a powerful tool for moving data.

Module 9: Data Storage Considerations

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SQL Server supports data queries, importing and extraction from a wide variety of clients and third-party data stores, and data warehousing.. In addition to its high-capacity database engine, SQL Server 7.0 offers a wide variety of features, including the following:. An OLAP tool accompanying SQL Server aids in studying data trends and. SQL Server supports a large number of concurrent users, primarily limited. by the size of the servers and network bandwidth.

Oracle Database Data Warehousing Guide

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8-7 Materialized View Schema Design. 8-8 Materialized View Schema Design Guidelines. 8-10 Overview of Materialized View Management Tasks. 8-19 Nested Materialized View Usage Guidelines. Materialized View Restrictions. 8-31 Materialized View Logs. 8-37 Analyzing Materialized View Capabilities. 9-6 Partitioning a Materialized View. 9-7 Benefits of Partitioning a Materialized View. 15-21 Checking the Status of a Materialized View. Materialized View Refresh Enhancements....

Module 3: Understanding Analysis Services Architecture

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Analysis Services is just one component of the Microsoft data warehousing and business intelligence strategy.. Analysis Services Clients. Analysis Services Clients DTS. Analysis Services is bundled with SQL Server 2000. Analysis Services does not require that the data warehouse be stored in SQL Server 2000.. Topic Objective To describe the role of Analysis Services in the Microsoft data warehousing framework..

Data Mining P1

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Preface xv 1 Introduction to Data Mining 1. 1.1 Introduction 1 1.2 Knowledge Discovery and Data Mining 5 1.3 Data Compression 10 1.4 Information Retrieval 12 1.5 Text Mining 14 1.6 Web Mining 15 1.7 Image Mining 16 1.8 Classification 18 1.9 Clustering 19 1.10 Rule Mining 20 1.11 String Matching 21 1.12 Bioinformatics 23 1.13 Data Warehousing 24 1.14 Applications and Challenges 25 1.15 Conclusions and Discussion 28 References 30. Soft Computing 35 2.1 Introduction 35 2.2 What is Soft Computing?

Managing time in relational databases- P21

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(iv) Asserted Versioning and Real-Time Data Warehousing.. Asserted Versioning supports bi- temporal tables in OLTP source system databases and/or Operational Data Stores. Asserted Versioning makes real-time data warehousing neither necessary nor desirable.. These updatable views make Asserted Versioning’s temporal transactions look like conventional SQL.

Tìm hiểu về đối sánh lược đồ và xây dựng ứng dụng VNMatch

000000208321-TT.pdf

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Bài toán đối sánh lược đồ được áp dụng trong các ứng dụng tích hợp dữ liệu (data integration), chuyển đổi dữ liệu (data translation), nhà kho dữ liệu (data warehousing), các ứng dụng web ngữ nghĩa (Web Semantic). Bài toán đối sánh lược đồ có thể được định nghĩa như sau: “Cho hai lược đồ S1 và S2 hãy tìm sự tương đồng giữa các phần tử của S1và S2 bằng cách khai thác tất cả các thông tin tồn tại trong hai lược đồ đó, trong dữ liệu và các nguồn thông tin hỗ trợ khác”.

Data Mining Multimedia Soft Computin And Bioinformatics P1

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Preface xv 1 Introduction to Data Mining 1. 1.1 Introduction 1 1.2 Knowledge Discovery and Data Mining 5 1.3 Data Compression 10 1.4 Information Retrieval 12 1.5 Text Mining 14 1.6 Web Mining 15 1.7 Image Mining 16 1.8 Classification 18 1.9 Clustering 19 1.10 Rule Mining 20 1.11 String Matching 21 1.12 Bioinformatics 23 1.13 Data Warehousing 24 1.14 Applications and Challenges 25 1.15 Conclusions and Discussion 28 References 30. Soft Computing 35 2.1 Introduction 35 2.2 What is Soft Computing?

SQL Server MVP Deep Dives- P19

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In data warehousing, it is com- mon to profile the data in advance to identify patterns in the data and determine if there are quality problems. 710 C HAPTER 56 Incorporating data profiling in the ETL process. When it is used this way, it can help identify problematic data in the sources.

High-Performance Parallel Database Processing and Grid Databases- P13

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Dehne, F., Eavis, T., and Rau-Chaplin, A., “Computing Partial Data Cubes for Parallel Data Warehousing Applications”, Proceedings of the 8th European PVM/MPI Users’ Group. Dehne, F., Eavis, T., and Rau-Chaplin, A., “Parallel querying of ROLAP cubes in the pres- ence of hierarchies”, Proceedings of International Workshop on Data Warehousing and OLAP (DOLAP), pp.

High-Performance Parallel Database Processing and Grid Databases- P12

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Dehne, F., Eavis, T., and Rau-Chaplin, A., “Computing Partial Data Cubes for Parallel Data Warehousing Applications”, Proceedings of the 8th European PVM/MPI Users’ Group. Dehne, F., Eavis, T., and Rau-Chaplin, A., “Parallel querying of ROLAP cubes in the pres- ence of hierarchies”, Proceedings of International Workshop on Data Warehousing and OLAP (DOLAP), pp.

NỔI CÁC VẤN ĐỀ AN NINH TRÊN HỆ THỐNG HIỆN ĐẠI VÀ ỨNG DỤNG QUẢN LÝ DỮ LIỆU

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Biometrics Application Technologies Visualization, Collaborative Computing, Mobile Relational DB Security, Distributed/Federated DB Layer Computing, Knowledge-based Systems Security, Web DB Security, Object/Multimedia DB Security, Data Warehouse Security, Inference Problem, Sensor DB and Stream Data Processing Security Layer 3: information extraction & sharing Data Management Layer Data Warehousing, Data Mining, Internet DBs, Collaborative, P2P & Grid Data Management Figure 2: Database and applications

E-Human Resource Management 33

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Journal of Data Warehousing &. Journal of Enterprise Information Systems Int. Journal of Business Data Comm. Journal of Intelligent Information Technologies International Journal of Cases on E-Commerce Int. Journal of Knowledge Management. International Journal of E-Business Research Int. Journal of Info. Technology Education International Journal of E-Collaboration Int. Journal of Technology &. Journal of Electronic Government Research Int .

Nghiên cứu ảnh hưởng của storage engine đến hiệu năng các ứng dụng kho dữ liệu

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Roland Bouman and Jos van Dongen Pentaho Solutions Business Intelligence and Data Warehousing with Pentaho and MySQL”, tr.1-90. María Carina Roldán Pentaho 3.2 Data Integration”, tr.7-60. “Pentaho Solutions: Business Intelligence and Data Warehousing with Pentaho and MySQL”, tr1-55 9. http://www.pentaho.com 11. http://www.mysql.com 12

ORACLE8i- P22

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Following that we will look at some of the other Oracle8i features and SQL tools for application in data warehousing environments. The average size of the Oracle database has grown rapidly over the years. That is one of the primary purposes of a data warehouse: analysis of historical data (as opposed to OLTP, which works with current data). It is about helping you understand some basic tenets of the data ware- housing approach to databases..

HANDBOOK OF CRM: Achieving Excellence in Customer Management Part 5

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Organizations should, however, also be aware of the potential drawbacks of data warehousing. Data warehouse functionality is limited by the quality and comprehensiveness of the data it contains.. This analysis provides the basis for the performance assessment process, the subject of the next chapter.. We have created a central data warehouse and have a single view of the customer.

Luận văn Thạc sĩ Khoa học máy tính: Nghiên cứu luật kết hợp và ứng dụng trong bài toán xây dựng hệ hỗ trợ học sinh trung học phổ thông

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Các kỹ thuật đó gọi chung là kỹ thuật tạo kho dữ liệu (data warehousing) và môi trƣờng các dữ liệu có đƣợc gọi là các kho dữ liệu (data warehouse).. Đồng thời, Công nghệ khai phá dữ liệu (data mining) ra đời đáp ứng những đòi hỏi trong khoa học cũng nhƣ trong hoạt động thực tiễn. Đây chính là một ứng dụng chính để khai phá kho dữ liệu nhằm phát hiện tri thức (Knowledge Discovery) phục vụ công tác quản lý, kinh doanh,…..

Pro SQL Server 2008 Analysis Services- P10

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Data-Mining Resources. Data Mining with SQL Server 2005, by ZhaoHui Tang and Jamie MacLennan (Wiley, 2005) Data Warehousing, Data Mining, &.