 Agenda 2/20/13 o Review quiz, answer questions o Review database design exercises from 2/13 o Create relationships through “Lookup tables” o Discuss queries: Turning data stored in a database into information for decision making. Highlight key issues about queries Answer any questions about queries to prepare you to complete part 2 of the Access Project.

 A lookup field lets the user select a value from a list of possible values  You use a Lookup Wizard field in Access to create a lookup field in a table o Example: Contract – ContractType relationship 2

 Turning data stored in a database into information for decision making.  A query creates a “virtual table”.  Table vs query: o What is the difference between a query and a table? o What is the difference between a query datasheet and a table datasheet? o Why do we create queries when we already have the data in tables?

 Table contains structure of data, constraints and actual data. o Table is referred to as “underlying data”.  Query is a way to look at the data. o Queries seldom look at the complete contents of a table because tables are usually very big, with many columns and many rows. o A query reduces the number of rows and columns in the underlying data (tables) to provide information for decision making. o Queries “filter” the data; fewer columns, fewer rows, calculated fields, summarized information. o A query enhances the data in the underlying tables by added calculations and logical conditions.

 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.

 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.

 Generalized queries o Using one or multiple tables o Specify the fields and records you want to Select.  Aggregate queries o Create one line in the result table. OR o Create multiple groups in the result table.  Parameter queries o Type of query that prompts the user for input before it runs. The query then uses the input as criteria that control your results. Example: City Parameter query in Panorama database.

 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.

 Computers require very explicit instructions.  Used in criteria to specify what records to include in the query.  Normally, must be very explicit about relational operators on the conditions of queries. o =, >, =, <= o Like o Between o In – Define a condition with a list of two or more values for a field o Is  Wildcard is an asterisk.

 You use the logical operators to combine two Boolean values and return a true, false, or null result. Logical operators are also referred to as Boolean operators.  And: Returns True when Expr1 and Expr2 are true. o Example: InvoiceAmt >$500 And City = Lansing  Or: Returns True when either Expr1 or Expr2 are true. o Example: InvoiceAmt > $500 OR City = Lansing  Not: Returns True when Expr is not true. o Example: Not In ("holland","rockford","saugatuck")

 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. o See the pre-written functions in the expression builder.  Can be very simple to very complicated.

 To perform a calculation, you define an expression containing a combination of database fields, constants, and operators o Expression Builder is an Access tool that makes it easy for you to create an expression  In the Query Setup group on the Design tab, click the Builder button  Use the expression elements and common operators to build the expression, or type the expression directly in the expression box  Click the OK button 13

 You can specify a particular format for a calculated field, just as you can for any field, by modifying its properties 14

 The & (ampersand) operator is a concatenation operator that joins text expressions  The IsNull function tests a field value or an expression for a null value; if the field value or expression is null, the result is true; otherwise, the result is false 15

 Aggregate functions are used to create grouped output.  Common summary calculations have pre-written functions: o Sum, count o Max, min o Avg, stDev, var o First, last  Calculations can be done for all data in the result table or to create grouped output in the result table.  The Group By operator divides the selected records into groups based on the values in the specified field

 The IIf (Immediate If) function assigns one value to a calculated field or control if a condition is true, and a second value if the condition is false.

 Frequently want to see if something is TRUE or FALSE.  Example: If a training event has > $500 in expenses, then it is a high expense event.  Logical condition for Access: o IIF(ProductCost > ProductPrice, “Losing Money”) o IIF(ISNULL(trainingexpenses + travelexpenses), 0) o IIF(ISNULL(trainingexpenses + travelexpenses), 0, trainingexpenses + travelexpenses)

 5 minutes.  Turn to the person or people next to you.  Describe at least 3 queries that would be relevant to the order database we use for the Access project. o Make sure that one of the queries requires calculations.