the sales process • Data warehouses exist to support o OLAP • What does it mean for a data warehouse to be multidimensional. o The files stored in a warehouse contain several layers of columns and rows. • A bank in trying to decide the interest rate to offer on a CD, checks a Web source what rates other banks are offering. This information is considered as: o External • Information exhibits high quality only if: o It is pertinent, relevant, and useful to you. • Data refers to o Raw facts
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works * Packet-switching technology Actual data transmission takes place sporadically, rather than continuously. Data to be transmitted is divided into small packets of information and labeled to identify the sender and recipient. These are sent over a network and then reassembled at their destination. If any packet did not arrive or was not intact, original sender requested to resend the packet. -> This enables millions to transmit data at the same time. * Understand the importance
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Abstract | 3 | 2 | What is Data Warehouse? | 3 | 3 | Who uses Data Warehouse? | 4 | 4 | Characteristics of Data Warehouse | 4 | 5 | Basic Elements of Data Warehouse | 5 | 6 | Basic Processes of Data Warehouse | 7 | 7 | Basic Components of Data Warehouse | 8 | 8 | Data Warehouse Architecture | 9 | 9 | Steps to build successful Data Warehouse | 12 | 10 | Selection of Data Warehouse | 13 | 11 | Cost and Size of Data Warehouse | 15 |
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business intelligence * —Supported by data warehouses and data-mining tools RELATIONAL DATABASE MODEL: Database – collection of information that you organize and access according to the logical structure of the information Relational database – series of logically related two-dimensional tables or files for storing information * —Relation = table = file * —Most popular database model DATABASE- CREATED WITH LOGICAL STRUCTURES Data dictionary – contains the logical structure
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government regulations or informed customers or market conditions. This requires organizations to be agile and to make frequent and quick strategic, tactical, and operational decisions. Making such decisions may require considerable amounts of relevant data, information, and knowledge. Processing these, in the framework of the needed decisions, must be done quickly, frequently in real time, and usually requires some computerized support. This course is about using business intelligence as computerized
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business organization, data is the most important thing. Different types of information are produced from data. When the amount of data is large, it becomes more difficult to process this data manually. In order to get quick results and timely information, an information system is used in almost all organizations. As the business grows, the amount of data also increases. As a result, it becomes more difficult to process the data manually. With the use of information system, data can be processed with
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and Container terminals , also a warehouse system, Gate control system, and Billing Invoice System, all these steps are the very first steps toward Monitor and control Day to day operation Jobs and tasks in ports, but it doesn’t make a big significance in boosting port performance , in order to take full advantages of these IT systems port authorities should implement Business Intelligence System as BI or EIS “Executive Information System” Combine Operation Data from all different department systems
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answers the question. 1. A characteristic or quality describing an entity is called a(n): 1. _______ A) attribute. B) key field. C) tuple. D) field. Answer: A Diff: 1 Page Ref: 230 2. The data hierarchy goes from bits and bytes to: 2. _______ A) fields, records, files, and databases. B) entities, attributes, fields, and records. C) records, entities, fields, and databases. D) fields, attributes, entities,
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Open Object Business Intelligence Release 1.0 Tiny SPRL 2009-04-09 CONTENTS i ii Open Object Business Intelligence, Release 1.0 I 1 2 Part 1 : Introduction Goal of the project What is for User? 2.1 2.2 2.3 For the end-user: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . For the administrator user: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . For the developer: . . . . . . . . . . . . . . . . . . . . . . . .
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Data warehousing History: "Data Warehouse" (QW) as a term was first coined and used by Bill Inmon in 1990. He asserted that Data warehouse is subject Oriented, Integrated, Time-Variant and nonvolatile collection of facts that can be useful in supporting decision making if studied or critically analysed. Definition: A DW is a centralized repository that stores data and information from multiple sources and can be used to transforms this data into a common, multidimensional data model for efficient
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