1. IS201 Agenda: 09/19  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).

2. Previously in IS201…  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.

3. Belmont Landscapes Database Design

4. Difference between table and query  Table contains structure of data, constraints and actual data.  Table is referred to as “underlying data”.  Query is a way to look at the data.  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.

5. General MS Access query vocabulary  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.

6. Understanding data like a computer understands data  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.

7. Queries with multiple tables  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.

8. Understanding relational operators  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.  =, >, =, <=  Like  Between  In  Is  Wildcard is an asterisk.

9. Making new columns based on calculations  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.  See the pre-written functions in the expression builder.  Can be very simple to very complicated.

10. Grouped output  Pre-written functions exist to do common summary calculations:  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