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IS201 Agenda: 09/19
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Modify contents of the database.
Discuss queries: Turning data stored in a database into
information for decision making.
Create relationships through “Lookup tables”.
At the beginning of class on 9/21:
Login.
 Copy the Belmont database from:
Kdrive:\is201\is201-hilfer\AccessBookFiles\Access1\Tutorial
 Save, rename and open the Belmont database in your
preferred area to store files (flash drive or u:drive).
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Previously in IS201…
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Discussed information visualization and the importance of
presenting information in a way that is usable and
understandable.
Discussed how a computer stores data and what data are
stored.
Learned how to store data in a database, focusing on the
design of data.
Learned how to create tables, relate tables and populate tables
in MS Access.
Touched on accessing data from a database. Have not really
talked about presenting information from the data stored in a
database.
Belmont Landscapes Database Design
Difference between table and query
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Table contains structure of data, constraints and actual
data.
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Table is referred to as “underlying data”.
Query is a way to look at the data.
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Queries seldom look at the complete contents of a table
because tables are usually very big, with many columns and
many rows.
The goal of creating a query is to provide appropriate data for
decision making.
Queries “filter” the data; fewer columns, fewer rows, calculated
fields, summarized information.
General MS Access query vocabulary
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Design view: Used to structure a query. Referred to as
“query by example” or QBE.
Result table: The table produced by the query. Shown in
the datasheet view.
SELECT query window: The window displayed in design
view that is filled out to produce a result table. Also
called the query design grid.
Field row: The area in the SELECT query window used to
define what columns should appear in the result table.
Criteria row: The area in the SELECT query window
used to identify which rows should appear in the result
table.
Understanding data like a computer
understands data
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Each value in a field has very specific data coded for a
computer to read.
Humans can discern vague similarities and differences
among data fairly easily. Computers are more exacting.
Computers need you to tell them when data is a date, or
a character, or a number.
A zero is not the same as a blank which is not the same
as a null.
A null is a special character assigned to a field that
technically has “no value”. It is very useful because we
can search for a null value with special operators.
Queries with multiple tables
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Referred to as “joining” tables.
Can produce confusing results.
Very dependent on a well-designed database. The tables
must be related with appropriate foreign keys or the
tables cannot be joined correctly for queries.
Understanding relational operators
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Computers require very explicit instructions.
MS Access has default instructions, but that is because it is
considered a very friendly, user-oriented package.
Normally, must be very explicit about relational operators
on the conditions of queries.
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=, >, <, >=, <=
Like
Between
In
Is
Wildcard is an asterisk.
Making new columns based on calculations
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Can do calculations for a column based on the data in
other columns for that same row.
Can use mathematical operators.
Can use pre-written functions in MS Access. Many
different types of pre-written functions for date handling,
data type conversion, calculations, etc.
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See the pre-written functions in the expression builder.
Can be very simple to very complicated.
Grouped output
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Pre-written functions exist to do common summary
calculations:
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Sum, count
Max, min
Avg, stdev, var
First, last
Can do calculations for all data in a result table, or
grouped data in a result table