Data Modeling Essentials 2005 phần 7 potx
Data Modeling Essentials 2005 phần 7 potx
... combina-
tion of < ;Data Item 1 Name>, < ;Data Item 2 Name>, . . . and < ;Data
Item n Name>.”
10.18 The Assertions Approach
■
3 17
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10.18.2.3. Attribute ... accepting a data model.
10.16 Testing the Model with Sample Data
If sample data is available, there are few better ways of communicating and
verifying a data model than...
Data Modeling Essentials 2005 phần 2 potx
... HO
Employee
Number
Qualification
Description
Qualification
Year
012 67 Bachelor of Arts 1 970
012 67 Master of Arts 1 973
012 67 Doctor of Philosophy 1 976
70 964 Bachelor of Arts 1969
226 17 Bachelor of Arts 1 972
226 17 Master of Arts 1 977
Employee Table ... Philosophy 1 976
70 964 Bachelor of Arts 1969
226 17 Bachelor of Arts 1 972
226 17 Master of Arts 1 977
Employee
Numbe...
Data Modeling Essentials 2005 phần 1 ppsx
... format.
4
■
Chapter 1 What Is Data Modeling?
Figure 1.1 An information system.
Report
Program
DATABASE Program
data
Report
Program
data
data
ProgramProgram
data
data
1
Data models can be presented ... Concept 219
7. 3.6 Chen Conventions in Practice 220
7. 4 Using UML Object Class Diagrams 220
7. 4.1 A Conceptual Data Model in UML 221
7. 4.2 Advantages of UML 222
7. 5 Object...
Data Modeling Essentials 2005 phần 3 ppsx
... data.
You obviously need to be careful in choosing not to reflect real-world
overlap in the data model. Failure to recognize overlaps among parties is
one of the most common faults in older database ... but whether the database structure, as
specified by the data model, is the best place for them.
Recall that one of the reasons we give so much attention to designing a
sound data model...
Data Modeling Essentials 2005 phần 4 ppsx
... 10/8/04 7: 56 PM Page 152
5.4.4 Column Datatype and Length Requirements
We now look at the translation of attribute types into column datatypes.
If your DBMS does not support UDTs (user-defined datatypes), ... varchar datatype
7
(depending on the
particular properties of these datatypes in the DBMS being used), unless it
is known that nonnumeric values will never be required, in which case...
Data Modeling Essentials 2005 phần 5 pot
... Bulwer-Lytton
8.1 Data Modeling in the Real World
In the preceding chapters, we have focused largely on learning the lan-
guage of data modeling without giving much attention to the practicalities
of modeling ... minimum list.
8.2.1 Recognition of Data Modeling
Let us repeat what we said in Chapter 1: No database was ever built with-
out a data model. Unfortunately, many datab...
Data Modeling Essentials 2005 phần 6 pdf
... same as those we use for selecting good
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Chapter 10 Conceptual Data Modeling
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Chapter 10
Conceptual Data Modeling
“Our job is to give the client not ... needs, as well as
detailed data requirements. Sources of requirements and ideas include
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■
Chapter 9 The Business Requirements
Simsion-Witt_09 10/8/04 7: 47 PM Page 270
sugges...
Data Modeling Essentials 2005 phần 8 pps
... include historical data in the same table as the corresponding current
data, it is likely that different queries access current and historical data.
Placing current and historical data in different ... improve the performance of queries on current data. You may
prefer to include a copy of the current data in the historical data table to
enable queries on all data to be written w...
Data Modeling Essentials 2005 phần 9 ppsx
... 1968
15.1 The Problem
Few areas of data modeling are the subject of as much confusion as the
handling of time-related and time-dependent data.
Perhaps we are modeling data for an insurance company. ... attribute is optional (nullable) (a data validation rule)
7. The DBMS datatype of each attribute (e.g., if the attribute is given a
numeric datatype, this specifies a data valida...
Data Modeling Essentials 2005 phần 10 ppt
... some impact on data modeling.
16.2.1 Data Integration: Working with Existing
Databases
A data warehouse is not simply a collection of copies of records from
source systems. It is a database that ... consistent results.
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Chapter 16 Modeling for Data Warehouses and Data Marts
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Chapter 17
Enterprise Data Models and
Data Manageme...
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