3 - EC1MakeupSolutions& Partitioning EC1MakeupDiscussion...

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EC1 Make-up Solutions &  Partitioning
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EC1 Make-up Discussion Q1. Dimension tables are said to be the entry points of a data warehouse. Comment. Ans. Most of the queries in Data Warehouse environment are outside-in queries, in such queries constraints come from the one or more of the dimension tables in the where clause. Also robust dimension attributes deliver robust analytical capabilities and moreover the interface to the data warehouse also depends on dimension implementation. Constraints come from DTs.
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Make up sols… Q.2 What is coverage fact table? What purpose it serves in a grocery store sales data mart? Give its schema. Also write an SQL to find out products that were on promotion but did not sell during a given time interval. Ans. Although you have provided various sales promotions, the actual sales may not happen for all promotions on each day. What products were on promotion but did not sell? The sales fact table only records the actually sold products. There are no records for no sale in the fact table doing so will enlarge the size enormously. So we will make promotion coverage fact table.
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Make up sols… A coverage fact less table, is a type of a fact less fact table when the primary fact table is spare and you need to generate the negative report. For example, you can create a sales promotion fact less table to store all the sales promotion for every week.
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Make up sols… Promotion Coverage fact table keys : Date Product Store Promotion
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Make up sols… Q3. List all the architectural components of a data warehouse and give a suitable architecture involving the components you list. Ans. Architectural components are : Source Systems Data Staging Meta Data Data Marts OLAP Data Mining Report Query Information Delivery
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Architecture Monitoring & Administration Metadata Repository Data Marts Serv Serv e OLAP servers
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Make up sols… Q4. Which data modeling technique, dimensional modeling or ER modeling is considered more restrictive and why ? Ans. Dimensional modeling is more restrictive . Reasons: Data must be classified as either fact or dimension.
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This note was uploaded on 03/14/2010 for the course CSE SS ZG515 taught by Professor Naveneetgoyal during the Summer '10 term at Birla Institute of Technology & Science.

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3 - EC1MakeupSolutions& Partitioning EC1MakeupDiscussion...

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