1.  Continue queries ◦ You completed two tutorials with step-by-step instructions for creating queries in MS Access. ◦ Now must apply knowledge and skills learned in the tutorials.  Class today:  Highlight key issues about queries.  Answer any questions about queries in preparation for completion of the next part of the project (due 10/03).  Learn conditional logic using IIF and ISNULL.  Do conditional logic exercise.

2. A query reduces the number of rows and columns in the underlying tables to provide information for decision making. This is done through relational criteria. A query enhances the data in the underlying tables by adding calculations and logical conditions. The goal of a query is to provide information from the data in a database.

3.  Individual rows vs. grouped output  Criteria. ◦ And vs. Or ◦ Relational operators., =, IN, LIKE, BETWEEN ◦ Wildcards  Multiple tables.  Parameters  Calculations.  Logical conditions. ◦ IIF ◦ ISNULL

4.  Individual row queries. ◦ Using one table. ◦ Using multiple tables. Tables must be related.  Aggregate queries. ◦ Can use one table or multiple tables. ◦ Creating one line in the result table as a summary of all data in the related tables. ◦ Creating multiple groups in the result table.

5.  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.

7.  Query to Find “unmatched” data.  Data that exists in one table (usually the parent), but does not exist in a related table (usually the child).  Examples: ◦ Which donors have not made any donations? ◦ Which categories have not been received on any donations? ◦ Which agencies have not received any donations?

8.  Pre-written functions exist to do common summary calculations: ◦ Sum, count ◦ Max, min ◦ Avg, stDev, var

9.  Enter data each time a query is run.  Can provide greater flexibility for queries that don’t have structured/standardized input.  Parameter is placed within standard criteria. Parameter is surrounded by square brackets, just like a data field.

10.  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.

11.  Frequently want to see if something is TRUE or FALSE, then do something based on that information.  Example: If a donation value is > $200, then we want to have a column in that output that says it is a “big” donation.  Logical condition for Access: ◦ IIF(donationvalue>200, ‘BIG’)

12.  The IIF function has three arguments: ◦ Relational condition ◦ What to do if the relational condition is True part ◦ What to do if the relational condition is False part  Examples: ◦ IIF(donationvalue > 200, ‘BIG’, ‘small’) ◦ IIF(donationvalue > 200 and donationvalue < 500, ‘medium’, ‘small’) ◦ IIF(donationdesc = ‘cash’, donationvalue, donationvalue *.75) ◦ IIF(datediff(“d”, now(), donationdate) > 0, ‘future donation’)

13.  Nothing is not nothing for computers.  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.  In MS Access: ◦ ISNULL(company) ◦ IIF(ISNULL(company), firstname + ‘ ‘ + lastname, company)