Midterm Exam: Tuesday, September 28
• Covers all course material through today’s lecture:
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Homeworks 1 - 5; Problem 1 of Homework #6
All lectures
All handouts
Readings from Stair and Reynolds and Rob and Coronel
• Will be pencil-and-paper
– No computers or calculators are necessary
• Will include:
– Relational database design (about 60%)
– Short answer/True-False (about 30%/10%)
• Review sessions will be held:
– Wednesday 9/29, 5:30 PM - 7 PM, Room 255 Baker Hall
– Saturday 10/2, 1 PM - 4 PM, Room 1003 HbH
• Homework #6 (Queries) due Tuesday, October 12
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
1
Query Logic and Design
Queries are sequences of commands used to extract and combine
data. Using the department store example, what are typical
questions that could be answered via queries?
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While tables store data, and relationships encode business rules
that link data in multiple tables, only queries assist in the
transformation of data into information
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
2
Design and Use of Queries
• In Access, queries are designed and executed using three
views:
– Design view
– Datasheet view
– SQL view
• Queries are used:
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to perform ad-hoc data analysis
to populate recordsets used in forms
to populate controls such as combo boxes and text boxes
to organize data for reports
as part of macros and code for custom processing tasks
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
3
Structured Query Language
Queries are executed using Structured Query Language (SQL).
SQL has a number of advantages compared to sequential programs
implemented in third-generation languages such as C or Pascal:
– SQL is simple: there are only thirty or so commands
– SQL is nonprocedural: data storage details are shielded from the user;
– SQL is platform-independent: queries can be represented identically on
different platforms;
– SQL is GUI-compatible: queries can be written in Access and other
languages with a GUI alone.
You may eventually find that some queries are more easily
expressed using SQL than via an interface
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
4
SQL SELECT
Many queries are based on the command which extracts a set
of records from a table for further analysis: SELECT
SQL View 
 Datasheet View
 Design View
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
5
SQL SELECT (cont’d)
The general SELECT command uses many clauses :
SELECT <set of columns, string or arithmetic combination of column(s) or
rows, joins on columns in different tables>
[INTO <new table>]
FROM <table name(s)>
[WHERE <logical conditions hold>]
[GROUP BY <column(s)>]
The SELECT command can extract a set of columns from one table, or a set of
columns from different tables for which pairs of tables have Foreign Key
relationships.
The INTO clause specifies a table which will store results of this query.
The FROM clause lists the table(s) used in the query
The WHERE clause lists logical conditions that must be satisfied.
The GROUP BY clause lists the attributes by which rows will be aggregated.
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
6
SQL SELECT- Using String Expressions
New columns in queries may be assigned values using a variety of
string expressions:
– [ColName1] & [ColName2] (concatenation): appends one string field to
another.
• Ex: [SName] & “ - “ & [Sex] applied to “Richards” & “ - “ “M” yields
“Richards - M”
– Left([ColName], N): extracts first N characters of column ColName.
Similarly: Right([ColName], N)
• Ex: Left([SName], 1) applied to “Richards” yields “R”
– Mid([ColName], N, M): extracts M characters of column ColName starting
at character #N
• Ex: Mid([CrsNbr],4,1) applied to “ACC610” yields “6”
– Len([ColName]): returns the length of column ColName
• Ex: Len([SID]) applied to “218” yields 3.
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
7
SQL SELECT- Using Arithmetic Expressions
New columns in queries may also be assigned values using a
variety of arithmetic expressions:
– [ColName1] + [ColName2] (addition): add the contents of two columns.
Similarly for “-” (subtraction)
– [ColName1] * [ColName2] (multiplication): subtracts the contents of one
column from another. Similarly for “/” (division)
– [ColName]^N (exponentiation): computes the value of a column to the
power N (N can be any real number)
– Abs([ColName]) (absolute value): computes the absolute value of a
column
• ex.: Abs([Temperature]) applied to “-32” gives “32”
– Int([ColName]): returns the integer portion of a real number
• ex.: Int([InterestRate]) applied to “8.325” gives “8”
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
8
SQL WHERE: Criteria for Selecting Rows
Logical expressions can determine rows to appear in query output:
– WHERE LogicalExpression([ColName])
• Ex: WHERE Left([Sname],1) < “S” chooses all rows where the first initial
of the last name is lower than “S”
• Ex: WHERE Major Is Null selects all rows where the value of the field
“Major” is Null (empty)
• Other operators: BETWEEN, LIKE, IN, EXISTS
– WHERE LogicalExpression1([ColName1]) OR
LogicalExpression2([ColName2])
(Logical OR)
• Ex: (Left([SName],1)<"P") OR ([GPA])>2.5) chooses all rows where the
first initial of the last name is lower than “P” OR the GPA exceeds 2.5
– WHERE LogicalExpression1([ColName1]) AND
LogicalExpression2([ColName2])
(Logical AND)
• Ex: (Left([SName],1)<"P") AND ([GPA])>2.5) chooses all rows where the
first initial of the last name is lower than “P” AND the GPA exceeds 2.5
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
9
SQL GROUP BY: Aggregate Records
The GROUP BY clause divides records into groups based on the
value of a criterion. New fields may be created using
summarized values of fields in each category. Example:
– SELECT Major, Avg(GPA) AS AvgOfGPA
FROM STUDENT
GROUP BY STUDENT.Major
Other summary calculations: Sum, Min, Max, Count, StDev, Var,
First, Last
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
10
Access Variations on SELECT Queries
• UPDATE: Calculates a new value for an existing
column using arithmetic/string expressions for rows
satisfying certain criteria. For example:
– UPDATE FACULTY
SET FACULTY.FName = "Kennedy-Jenkins"
WHERE (([FName]="Kennedy"))
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
11
Access Variations on SELECT Queries
(cont’d)
• APPEND: Adds records from the current query to another table
with identical format. For example:
– INSERT INTO FACULTY4
SELECT FACULTY3.*
FROM FACULTY3;
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
12
Access Variations on SELECT Queries
(cont’d)
• MAKE TABLE: Creates a new table based on results from the
current query. For example:
– SELECT FACULTY3.FID, FACULTY3.FName
INTO FACULTY_NEW
FROM FACULTY3
GROUP BY FACULTY3.FID, FACULTY3.FName
ORDER BY FACULTY3.FID;
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
13
Access Variations on SELECT Queries
(cont’d)
• DELETE: deletes all records satisfying certain criteria.
Example:
– DELETE STUDENT2.*, STUDENT2.GPA
FROM STUDENT2
WHERE (((STUDENT2.GPA)<=2.5));
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
14
Access Variations on SELECT Queries
(cont’d)
• CROSSTAB: creates a two-dimensional table in which a
value field is summarized according to row and column
field(s). Example:
– TRANSFORM Avg(STUDENT.GPA) AS AvgOfGPA
SELECT STUDENT.Major
FROM STUDENT
GROUP BY STUDENT.Major
PIVOT STUDENT.Sex;
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
15
Parameter Queries
• Parameter Queries: Select records that match a user-defined
criterion based on a particular field. Example:
– SELECT COURSE.*
FROM COURSE
WHERE (((COURSE.CrsNbr)=[Select a course number:]));
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
16
Other Query Applications
Views: Select a row driver, and add one or more tables, each pair of which is
linked by a Foreign key relationship. Select columns of interest for
output.
Find Duplicate Records: Find the records in a
table that have identical values for all
columns
Find Unmatched Records: Find the records in
one table without records in another table
according to a common field
Archive: Select records according to given criteria (SELECT query); create a
new table based on query results (MAKE TABLE query), delete selected
records from original table (DELETE query)
Select Top X Records: Select the top X (X%) records according to given criteria
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
17
Data Analysis Applications of Queries
• Suppose you have a number of fields that could serve as indexes or foreign
keys, but with inconsistent information:
– “Degree attained” = “Bachelor’s”, “B.A.”, “A.B”, “MPM”, “M.S.”
How could you derive a consistent set of values?
• Now suppose you have a dataset describing customers with a number of
candidate keys:
– Last name, Phone number, Street address
How could you determine a primary key (if one exists)?
• Finally, you want to determine the distribution of family income by marital
status and gender:
– “Marital Status” = “Married”, “Separated”, “Divorced”, …
How would you calculate this distribution?
Tuesday, September 28,
1999
90-728 MIS Lecture Notes
18