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COMP810 Data Warehousing and Big Data
创建日期：2024-07-01 16:55:57
标签： COMP810
Data Warehousing and Big Data

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 Assessment task
To design, implement and analyse a Data Warehouse (DW) for MarketExpress, one of the biggest


online sales websites.

 Project overview
MarketExpress is one of the biggest online websites, selling products from various suppliers. Suppliers’ products are kept in MarketExpress warehouses and orders (customer transactions) are fulfilled from warehouses located all over New Zealand. MarketExpress has thousands of customers and therefore it is important for the organisation to analyse the shopping behaviour of their customers. Based on such analysis the organisation can optimise their selling techniques e.g. by having relevant promotions on different products.

There is a need to 1. Build a DW so that shopping behaviour can be analysed. 2. Customer transactions from Data Sources (DSs) are required to be reflected in the DW on a daily basis. This process of reflecting the customer data into DW is called Data Integration (DI) as shown in Figure 1. To implement DI we usually need to perform ETL (Extraction, Transformation, and Loading). Since the data generated by customers is not in the format required by DW, it needs to be processed in the transformation layer of ETL. This processing will involve the enriching of transactions data with information from Master Data (MD) as shown in Figure 2. The ‘enriched data is then stored in the DW. Once the data is stored in the DW, you will be able to 3. perform analysis using multidimensional data analysis.

Assessment Part 1. Build a DW

You will build a DW using the star schema which is a data modelling technique that is used to map multidimensional decision support data into a relational DW. Star schema is an easily implemented model for multidimensional data analysis while still preserving the relational structures on which the operational database is built.

The star schema represents aggregated data for specific business activities. Using this schema, one can store aggregated data from multiple sources that will represent different aspects of business operations. For example, the aggregation may involve total sales by selected time periods, by products, by warehouses, and so on. Aggregated totals can be the total number of product sold, total sales values by products, and so on. The basic star schema has three main components: facts, dimensions, attributes. Usually in case of star-schema for sales the dimension tables are: product, date, warehouse, and supplier while the fact table is sales. However, to determine the right tables and attributes you will need to consider Figure 2, and build a DW with the appropriate fact table and dimension tables, each with appropriate attributes.


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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 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