dwh_tutorial

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DWH Data Mart Data marts contain a subset of organization-wide data that is valuable to specific groups of people in an organization. In other words, a data mart contains only those data that is specific to a particular group. For example, the marketing data mart may contain only data related to items, customers, and sales. Data marts are confined to subjects. Points to Remember About Data Marts Windows-based or Unix/Linux-based servers are used to implement data marts. They are implemented on low-cost servers. The implementation cycle of a data mart is measured in short periods of time, i.e., in weeks rather than months or years. The life cycle of data marts may be complex in the long run, if their planning and design are not organization-wide. Data marts are small in size. Data marts are customized by department. The source of a data mart is departmentally structured data warehouse. Data marts are flexible. 11
DWH The following figure shows a graphical representation of data marts. Virtual Warehouse The view over an operational data warehouse is known as virtual warehouse. It is easy to build a virtual warehouse. Building a virtual warehouse requires excess capacity on operational database servers. 12
Page 2 and 3: About the Tutorial A data warehouse
Page 4 and 5: IT Strategy .......................
Page 6 and 7: Categories of Metadata ............
Page 8 and 9: 1. OVERVIEW DWH The term "Data Ware
Page 10 and 11: DWH Data Warehouse Applications As
Page 12 and 13: 2. CONCEPTS DWH What is Data Wareho
Page 14 and 15: DWH Data Transformation - Involv
Page 16 and 17: DWH Data Cube A data cube helps us
Page 20 and 21: 4. DELIVERY PROCESS DWH A data ware
Page 22 and 23: DWH and medium-term, then we can de
Page 24 and 25: DWH The architecture is designed to
Page 26 and 27: DWH Controlling the Process Control
Page 28 and 29: 6. ARCHITECTURE DWH In this chapter
Page 30 and 31: DWH Enterprise Warehouse Virtual W
Page 32 and 33: DWH The transformations affects
Page 34 and 35: DWH Detailed Information Detailed i
Page 36 and 37: 7. OLAP DWH Online Analytical Proce
Page 38 and 39: DWH Roll-up is performed by cl
Page 40 and 41: DWH Here Slice is performed for t
Page 42 and 43: DWH OLAP vs OLTP Data Warehouse (OL
Page 44 and 45: 8. RELATIONAL OLAP DWH Relational O
Page 46 and 47: 9. MULTIDIMENSIONAL OLAP DWH Multid
Page 48 and 49: 10. SCHEMAS DWH Schema is a logical
Page 50 and 51: DWH The sales fact table is sam
Page 52 and 53: DWH define dimension location as (l
Page 54 and 55: DWH Horizontal Partitioning There a
Page 56 and 57: DWH Round Robin Partitions In the r
Page 58 and 59: DWH Note: While using vertical part
Page 60 and 61: DWH Role of Metadata Metadata has a
Page 62 and 63: DWH Challenges for Metadata Managem
Page 64 and 65: DWH As the merchant is not interest
Page 66 and 67: DWH The summaries are data marted i
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14. SYSTEM MANAGERS DWH System mana
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DWH Events Events are the actions t
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15. PROCESS MANAGERS DWH Process ma
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DWH Functions of Warehouse Manager
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16. SECURITY DWH The objective of a
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DWH But if each department accesses
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DWH These restrictions need to be c
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17. BACKUP DWH A data warehouse is
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DWH Connecting the tape drive as
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DWH Will it work in cluster a
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DWH It is also essential that th
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DWH Points to Note It is important
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DWH Test Schedule First of all, the
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DWH Testing the Application All th
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21. INTERVIEW QUESTIONS DWH Dear re
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DWH Q: Define a warehouse manager.
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