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Access 2007 for Starters: The Missing Manual by Matthew MacDonald

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Chapter 4. Blocking Bad Data

  • Data Integrity Basics

  • Input Masks

  • Validation Rules

  • Lookups

Even the best database designer has spent a sleepless night worrying about the errors that could be lurking in a database. Bad data’s a notorious problem—it enters the database, lies dormant for months, and appears only when you discover you’ve mailed an invoice to customer “Blank Blank” or sold a bag of peanuts for –$4.99.

The best way to prevent these types of problems is to stop bad data from making it into your database in the first place. In other words, you need to set up validation rules that reject suspicious values as soon as someone types them in. Once bad data’s entered your database, it’s harder to spot than a blueberry in a swimming pool.

This chapter covers the essential set of Access data validation tools:

  • The basicsinclude duplicates, required fields, and default values.

  • Input masksformat ordinary text into patterns, like postal codes and phone numbers.

  • Validation ruleslay down strict laws for unruly fields.

  • Lookupslimit values to a list of preset choices.

Data Integrity Basics

All of Access’s data validation features work via the Design view you learned about in Chapter 2. To put them in place, you choose a field and then tweak its properties. The only trick’s knowing what properties are most useful. You’ve already seen some in Chapter 2, but the following sections fill in a few more details.

Tip

Remember, Access gives you three ways to switch to Design view. You can right-click the table tab title and then choose Design View from the menu, use the Home → View button on the ribbon, or use the tiny view buttons at the Access window’s bottom-right corner. And if you’re really impatient, then you don’t even need to open your table first—just find it in the navigation pane, right-click it there, and then choose Design View.

Preventing Blank Fields

Every record needs a bare minimum of information to make sense. However, without your help, Access can’t distinguish between critical information and optional details. For that reason, every field in a new table is optional, except for the primary-key field (which is usually the ID value). Try this out with the Dolls table from Chapter 1; you’ll quickly discover that you can add records that have virtually no information in them.

You can easily remedy this problem. Just select the field that you want to make mandatory in Design view, and then set the Required field property to Yes (Figure 4-1).

The Required field property tells Access not to allow empty values (called nulls in tech-speak).
Figure 4-1. The Required field property tells Access not to allow empty values (called nulls in tech-speak).

Access checks the Required field property whenever you add a new record or modify a field in an existing record. However, if your table already contains data, there’s no guarantee that it follows the rules.

Imagine you fill the Dolls table with a few bobbleheads before you decide that every record requires a value for the Character field. You switch to Design view, choose the Character field, and then flip the Required field property to Yes. When you save the table (by switching back to Datasheet view or closing the table), Access gives you the option of verifying the bobblehead records that are already in the table (Figure 4-2). If you choose to perform the test and Access finds the problem, it gives you the option of reversing your changes (Figure 4-3).

It’s a good idea to test the data in your table to make sure it meets the new requirements you put into place. Otherwise, invalid data could still remain. Don’t let the message scare you—unless you have tens of thousands of records, this check doesn’t take long.
Figure 4-2. It’s a good idea to test the data in your table to make sure it meets the new requirements you put into place. Otherwise, invalid data could still remain. Don’t let the message scare you—unless you have tens of thousands of records, this check doesn’t take long.
If Access finds an empty value, then it stops the search and asks you what to do about it. You can keep your changes (even though they conflict with at least one record)—after all, at least new records won’t suffer from the same problem. Your other option is to reset your field to its more lenient previous self. Either way, you can track down the missing data by performing a sort on the field in question (Section 3.2.1), which brings empty values to the top.
Figure 4-3. If Access finds an empty value, then it stops the search and asks you what to do about it. You can keep your changes (even though they conflict with at least one record)—after all, at least new records won’t suffer from the same problem. Your other option is to reset your field to its more lenient previous self. Either way, you can track down the missing data by performing a sort on the field in question (Section 3.2.1), which brings empty values to the top.

Blank values and empty text

Access supports this Required property for every data type. However, with some data types you might want to add extra checks. That’s because the Required property prevents only blank fields—fields that don’t have any information in them at all. However, Access makes a slightly bizarre distinction between blank values and something called empty text.

A blank (null) value indicates that no information was supplied. Empty text indicates that a field value was supplied, but it just happens to be empty. Confused yet? The distinction exists because databases like Access need to recognize when information’s missing. A blank value could indicate an oversight—someone might just have forgotten to enter the value. On the other hand, empty text indicates a conscious decision to leave that information out.

Note

To try this out in your datasheet, create a text field that has Required set to Yes. Try inserting a new record, and leaving the record blank. (Access stops you cold.) Now, try adding a new record, but place a single space in the field. Here’s the strange part: Access automatically trims out the spaces, and by doing so, it converts your single space to empty text. However, you don’t receive an error message because empty text isn’t the same as a blank value.

The good news is that if you find this whole distinction confusing, then you can prevent both blank values and empty text. Just set Required to Yes to stop the blank values, and set Allow Zero Length to No to prevent empty text.

Note

A similar distinction exists for numeric data types. Even if you set Required to Yes, you can still supply a number of 0. If you want to prevent that action, then you’ll need to use the validation rules described later in this chapter (Section 4.3).

Setting Default Values

So far, the fields in your tables are either filled in explicitly by the person who adds the record or left blank. But there’s another option—you can supply a default value. Now, if someone inserts a record and leaves the field blank, Access applies the default value instead.

You set a default value using the Default Value field property. For a numeric Added-Cost field, you could set this to be the number 0. For a text Country field, you may use the text “U.S.A.” as a default value. (All text values must be wrapped in quotations marks when you use them for a default value.)

Access shows all your default values in the new-row slot at the bottom of the datasheet (Figure 4-4). It also automatically inserts default values into any hidden columns (Section 3.1.4).

Access inserts the default value when you create a new record. (You’re then free to change that value.) You can also switch a field back to its default value using the Ctrl+Alt+Space shortcut while you’re editing it.

Tip

One nice feature is that you can use the default value as a starting point for a new record. For example, when you create a new record in the datasheet, you can edit the default value, rather than replacing it with a completely new value.

You can also create more intelligent dynamic default values. Access evaluates dynamic default values whenever you insert a new record, which means that the default value can vary based on other information. Dynamic default values use expressions (specialized database formulas) that can perform calculations or retrieve other details. One useful expression, Date( ), grabs the current date that’s set on your computer. If you use Date( ) as the default value for a date field (as shown in Figure 4-5), then Access automatically inserts the current date whenever you add a new record.

This dating service uses four default values: a default height (5.9), a default city (New York), a default state (also New York), and a default country (U.S.A.). This system makes sense, because most of their new entries have this information. On the other hand, there’s no point in supplying a default value for the name fields.
Figure 4-4. This dating service uses four default values: a default height (5.9), a default city (New York), a default state (also New York), and a default country (U.S.A.). This system makes sense, because most of their new entries have this information. On the other hand, there’s no point in supplying a default value for the name fields.

Preventing Duplicate Values with Indexes

Any table’s first rule is that each record it contains must be unique. To enforce this restriction, you need to choose a primary key (Section 2.4), which is one or more fields that won’t ever be duplicated in different records.

Here’s the catch. As you learned in Chapter 2, the safest option’s to create an ID field for the primary key. So far, all the tables you’ve seen have included this detail. But what if you need to make sure other fields are unique? Imagine you create an Employees table. You follow good database design principles and identify every record with an automatically generated ID number. However, you also want to make sure that no two employees have the same Social Security number (SSN) to prevent possible errors—like accidentally entering the same employee twice.

If you use the Date( ) function as the default value for the DateAcquired field in the bobblehead table, then every time you add a new bobblehead record, Access fills in the current date. You decide whether you want to keep that date or replace it with a different value.
Figure 4-5. If you use the Date( ) function as the default value for the DateAcquired field in the bobblehead table, then every time you add a new bobblehead record, Access fills in the current date. You decide whether you want to keep that date or replace it with a different value.

Note

For a quick refresher about why ID fields are such a good idea, refer to Section 2.4. In the Employees table, you certainly could choose to make the SSN the primary key, but it’s not the ideal situation when you start linking tables together (Chapter 5), and it causes problems if you need to change the SSN later on (in the case of an error), or if you enter employee information before you’ve received the SSN.

You can force a field to require unique values with an index. A database index is analogous to the index in a book—it’s a list of values (from a field) with a cross-reference that points to the corresponding section (the full record). If you index the SocialSecurityNumber field, Access creates a list like this and stores it behind the scenes in your database file:

Table 4-1. 

SocialSecurityNumber

Location Of Full Record

 

001-01-3455

 

001-02-0434

 

001-02-9558

 

002-40-3200

 

Using this list, Access can quickly determine whether a new record duplicates an existing SSN. If it does, then Access doesn’t let you insert it.

So how do you apply an index to a field? The trick’s the Indexed field property, which is available for every data type except Attachment and OLE Object. When you add a field, the Indexed property’s set to No, which means Access doesn’t create a field. To add an index and prevent duplicates, you can change the Indexed property in Design view to Yes [No Duplicates]. The third option, Yes [Duplicates OK], creates an index but lets more than one record have the same value. This option doesn’t help you catch repeated records, but you can use it to speed up searches.

Note

As you know from Chapter 2 (Section 2.4.1), primary keys also disallow duplicates, using the same technique. When you define a primary key, Access automatically creates an index on that field.

When you close Design view after changing the Indexed field property, Access prompts you to save your changes. At this point, it creates any new indexes it needs. You can’t create a no-duplicates index if you already have duplicate information in your table. In this situation, Access gives you an error message when you close the Design window and it attempts to add the index.

Multifield indexes

You can also use indexes to prevent a combination of values from being repeated. Imagine you create a People table to track your friends and their contact information. You’re likely to have entries with the same first or last name. However, you may want to prevent two records from having the same first and last name. This limitation prevents you from inadvertently adding the same person twice.

Note

This example could cause endless headaches if you honestly do have two friends who share the same first and last names. In that case, you’ll need to remove the index before you’re allowed to add the name. You should think carefully about legitimate reasons for duplication before you create any indexes.

To ensure that a combination of fields is unique, you need to create a compound index, which combines the information from more than one field. Here’s how to do it:

  1. In Design view, choose Table Tools | Design → Show/Hide → Indexes.

    The Indexes window appears (Figure 4-6). Using the Indexes window, you can see your current indexes and add new ones.

    The Indexes window shows all the indexes that are defined for a table. Here, there’s a single index for the ID field (which Access created automatically) and a compound index that’s in the process of being created.
    Figure 4-6. The Indexes window shows all the indexes that are defined for a table. Here, there’s a single index for the ID field (which Access created automatically) and a compound index that’s in the process of being created.
  2. Choose a name for your index. Type this name into the first blank row in the Index Name column.

    The index name has no real importance—Access uses it to store the index in the database, but you don’t see the index name when you work with the table. Usually, you’ll use the name of one or both of the fields you’re indexing (like Last-Name+FirstName).

  3. Choose the first field in the Field Name column in the same row (like LastName).

    It doesn’t matter which field name you use first. Either way, the index can prevent duplicate values. However, the order does affect how searches use the index to boost performance.

  4. In the area at the bottom of the window, set the Unique box to Yes.

    This creates an index that prevents duplicates (as opposed to one that’s used only for boosting search speeds).

    You can also set the Ignore Nulls box to Yes, if you want Access to allow duplicate blank values. Imagine you want to make the SSN field optional. However, if an SSN number is entered, then you want to make sure it doesn’t duplicate any other value. In this case, you should Ignore Nulls to Yes. If you set Ignore Nulls to No, then Access lets only one record have a blank SSN field, which probably isn’t the behavior you want.

    Note

    You can also disallow blank values altogether using the Required property, as described in Section 4.1.

    Ignore the Primary box (which identifies the index used for the primary key).

  5. Move down one row. Leave the Index Name column blank (which tells Access it’s still part of the previous index), but choose another field in the Field Name column (like FirstName).

    If you want to create a compound index with more than two fields, then just repeat this step until you’ve added all the fields you need. Figure 4-7 shows what a finished index looks like.

    You can now close the Indexes window.

    Here’s a compound index that prevents two people from sharing the same first and last names.
    Figure 4-7. Here’s a compound index that prevents two people from sharing the same first and last names.

Input Masks

As you’ve already learned, databases prize consistency. If you have a field named Height, you better be sure every value in that field uses the same type of measurements; otherwise, your data’s not worth its weight in sock lint. Similarly, if you have a PhoneNumber field, you better make sure every phone number has the same format. If some phone numbers are written with dashes, spaces, and parentheses (like (844) 547-1123), while others are a bit different (say 847-547-1123), and a few leave out the area code information altogether (547-1123), then you’ve got a small problem on your hands. Because of the lack of consistency, you’ll have a hard time working with this information (say, searching for a specific phone number or sorting the phone numbers into different categories based on area code).

To help you manage values that have a fixed pattern—like phone numbers—you can use an input mask. Essentially, an input mask (or just mask for short) gives you a way to tell Access what pattern your data should use. Based on this pattern, Access changes the way values are entered and edited to make them easier to understand and less error-prone. Figure 4-8 shows how a mask lets Access format a series of characters as they’re being typed into a field.

You can add a mask to any field that uses the Text data type. Masks give you several advantages over ordinary text:

  • Masks guide data entry. When empty, a masked edit control shows the place-holders where values need to go. A phone number mask shows the text (_ _ _) _ _ _-_ _ _ _ when it’s empty, clearly indicating what type of information it needs.

  • Masks make data easier to understand. You can read many values more easily when they’re presented a certain way. Most people can pick out the numbers in this formatted Social Security number (012-86-7180) faster than this unformatted one (012867180).

  • Masks prevent errors. Masks reject characters that don’t fit the mold. If you’re using the telephone mask, you can’t use letters.

  • Masks prevent confusion. With many types of data, you have several ways to present the same information. You can enter phone numbers both with and without area codes. By presenting the mask with the area code placeholder, you’re saying that this information’s required (and where it goes). It’s also obvious that you don’t need to type in parentheses or a dash to separate numbers, because those details are already there. You’ll see the same benefit if you use masks with dates, which can be entered in all sorts of different combinations (Year/Month/Day, Month-Day-Year, and so on).

Masks are best suited for when you’re storing numeric information in a text field. This scenario occurs with all sorts of data, including credit card numbers, postal codes, and phone numbers. These types of information shouldn’t be stored in number fields, because they aren’t meant to be interpreted as a single number. Instead, they’re meant to be understood as a series of digits. (If you do make the mistake of storing a phone number in a number field, you’ll find out that people can type in perfectly nonsensical phone numbers like 0 and –14 because these are valid numbers, even if they aren’t valid phone numbers. But an input mask on a text field catches these errors easily.)

Top: Here’s a PhoneNumber field with a mask that’s ready to go. So far, the person entering the record hasn’t typed anything. The PhoneNumber field automatically starts out with this placeholder text.Bottom: The mask formats the numbers as you type. If you type 1234567890 into this phone number mask, then you see the text (123) 456-7890. Behind the scenes, the databases stores 1234567890, but the information’s presented in the datasheet using a nicely formatted package. That package is the mask.
Figure 4-8. Top: Here’s a PhoneNumber field with a mask that’s ready to go. So far, the person entering the record hasn’t typed anything. The PhoneNumber field automatically starts out with this placeholder text. Bottom: The mask formats the numbers as you type. If you type 1234567890 into this phone number mask, then you see the text (123) 456-7890. Behind the scenes, the databases stores 1234567890, but the information’s presented in the datasheet using a nicely formatted package. That package is the mask.

Masks can’t help you with more sophisticated challenges, like data values that have varying lengths or subtle patterns. For instance, a mask doesn’t help you spot an incorrect email address.

Note

Text and Date/Time are the only data types that support masks.

Using a Ready-Made Mask

The easiest way to get started with masks is to use one of the many attractive options that Access has ready for you. This method’s great, because it means you don’t need to learn the arcane art of mask creation.

Here’s what you need to do to pick out a prebuilt mask:

  1. In Design view, select the text field where you want to apply the mask.

    For this test, try a PhoneNumber field.

  2. Look for the Input Mask field property. Click inside the field.

    When you do, a small ellipsis (…) button appears at the left edge, as shown in Figure 4-9.

    The ellipsis (…) button (circled) is just the way Access tells you that you don’t need to fill in this value by hand. Instead, you can click the ellipsis and pop up a wizard (like the Input Mask wizard) or some sort of helpful dialog box.
    Figure 4-9. The ellipsis (…) button (circled) is just the way Access tells you that you don’t need to fill in this value by hand. Instead, you can click the ellipsis and pop up a wizard (like the Input Mask wizard) or some sort of helpful dialog box.
  3. Click the ellipsis button.

    The Input Mask wizard starts (see Figure 4-10).

    The Input Mask wizard starts with a short list of commonly used masks. Next to every mask, Access shows you what a sample formatted value looks like. Once you select a mask, you can try using it in the Try It text box. The Try It text box gives you the same behavior that your field will have once you apply the mask.
    Figure 4-10. The Input Mask wizard starts with a short list of commonly used masks. Next to every mask, Access shows you what a sample formatted value looks like. Once you select a mask, you can try using it in the Try It text box. The Try It text box gives you the same behavior that your field will have once you apply the mask.
  4. Choose the mask you want from the list of options.

    In this case, choose the first item in the list (Phone Number).

    Note

    Don’t see what you want? You’ll need to create your own (an advanced topic covered in Access 2007: The Missing Manual). If you see one that’s close but not perfect, select it. You can tweak the mask in the wizard’s second step.

  5. Click Next.

    The wizard’s second step appears (see Figure 4-11).

  6. If you want, you can change the mask or the placeholder character.

    To change the mask, you’ll need to learn what every mask character means (see Access 2007: The Missing Manual for details).

    The phone number mask is !(999) 000-000. Each 9 represents an optional number from 0 to 9. Each 0 represents a required number from 0 to 9. So according to this mask, (123) 456-7890 is a valid phone number, as is 123-4567, but (123) 456 isn’t.
    Figure 4-11. The phone number mask is !(999) 000-000. Each 9 represents an optional number from 0 to 9. Each 0 represents a required number from 0 to 9. So according to this mask, (123) 456-7890 is a valid phone number, as is 123-4567, but (123) 456 isn’t.

    You use the placeholder to show the empty slots where you enter information. The standard choice is the underscore. Optionally, you can use a space, dash, asterisk, or any other character by typing it in the “Placeholder character” box.

  7. Click Next.

    If you’re adding a mask to a text field, then the wizard’s final step appears (see Figure 4-12).

    If you’re adding a mask to a date field, then Access doesn’t need to ask you how to store the information—it already knows. In this case, you can jump to step 9 and click Finish.

  8. Choose how you want to store the value in this field.

    The standard choice is to store just the characters you’ve typed in (in other words, everything you type into the field). If you use this option, the placeholders aren’t included. For example, the phone number (416) 123-4567 is stored as 4161234567. This option saves a little space, and it also lets you change the mask later on to present the information in a slightly different way.

    The final step lets you choose how the data in your field is chosen—with or without the mask symbols.
    Figure 4-12. The final step lets you choose how the data in your field is chosen—with or without the mask symbols.

    You could also store the mask complete with all the extra characters. Then a phone number’s stored complete with hyphens, dashes, and spaces, like (416) 123-4567. This approach isn’t nearly as flexible because you can’t change the mask later.

  9. Click Finish.

    The final mask appears in the Input Mask field property.

    Before going any further, you may want to make sure that the length you’ve reserved for your field matches the mask. In the phone number example, you need a Field Size of 10 if you’ve chosen to store unformatted values (because there are 10 digits), or a Field Size of 14 for the whole shebang, complete with placeholders (one dash, one space, and two parentheses).

  10. Switch back to the Datasheet view, and click Yes when Access asks you to save changes.

    Your input mask is now in place.

Note

Access uses the input mask information to control how you enter information in the datasheet. However, it’s possible to circumvent the mask by entering the information in other ways. You could, for instance, create a form (as described in Part Three), and switch off the mask. A mask’s not an absolute guarantee against invalid data—if you want such a guarantee, then you need a validation rule instead.

Validation Rules

Input masks are a great tool, but they apply to only a few specific types of information—usually fixed-length text that has a single, unchanging pattern. To create a truly bulletproof table, you need to use more sophisticated restrictions, like making sure a number falls in a certain range, checking that a date hasn’t yet occurred, or verifying that a text value starts with a certain letter. Validation rules can help you create all these restrictions.

A validation rule’s premise is simple. You set up a restriction that tells Access which values to allow in a field and which ones are no good. Whenever someone adds a new record or edits a record, Access makes sure the data lives up to your validation rules. If it doesn’t, then Access presents an error message and forces you to edit the offending data and try again.

To add your own mask, use the record scrolling buttons (at the bottom of the window) to scroll to the end. Or you can use this window to change a mask. For example, the prebuilt telephone mask doesn’t require an area code. If that’s a liberty you’re not willing to take, then replace it with the more restrictive version (000) 000-0000.
Figure 4-13. To add your own mask, use the record scrolling buttons (at the bottom of the window) to scroll to the end. Or you can use this window to change a mask. For example, the prebuilt telephone mask doesn’t require an area code. If that’s a liberty you’re not willing to take, then replace it with the more restrictive version (000) 000-0000.

Applying a Field Validation Rule

Each field can have a single validation rule. The following set of steps show you how to set one up. You’ll start out easy, with a validation rule that prevents a numeric field from accepting 0 or any negative number (and in the following sections you’ll hone your rule-writing abilities so you can tackle other data types).

Here’s how to add your validation rule:

  1. In Design view, select the field to which you want to apply the rule.

    All data types—except Memo, AutoNumber, and OLE Object—support validation. The validation rule in this example works with any numeric data type (like Number or Currency).

  2. In the Validation Rule field property, type a validation expression (Figure 4-14).

    An expression’s a bit of SQL that performs a check on the data you’ve entered. Access performs its validation check when you finish entering a piece of data, and try to navigate to another field or another record. For example, >0 is a validation rule that forces the value in a Number field to be larger than 0. You’ll learn more validation rules in the following sections.

    Here, the Validation Rule property prevents impossible prices, and the Validation Text provides an error message.
    Figure 4-14. Here, the Validation Rule property prevents impossible prices, and the Validation Text provides an error message.
  3. Type some error-message text in the Validation Text field property.

    If you enter a value that fails the validation check, then Access rejects the value and displays this error text in a dialog box. If you don’t supply any text, then Access shows the validation rule for the field (whatever you entered in step 2), which is more than a little confusing for most mere mortals.

  4. Right-click the tab title, and then choose Datasheet View.

    If your table has existing records, Access gives you the option of checking them to make sure they meet the requirements of your validation rule. You decide whether you want to perform this check, or skip it altogether.

    Once you’re in Datasheet view, you’re ready to try out your validation rule (Figure 4-15).

Note

Just because your table has validation rules doesn’t mean the data inside follows these rules. A discrepancy can occur if you added records before the validation rules came into effect. (You learned about the same potential problem with required fields in Section 4.1.) To avoid these headaches, set up your validation rules before you start adding data.

Here, a validation rule of >0 prevents negative numbers in the Price field. When you enter a negative number, Access pops up a message box with the validation text you defined, as shown here. Once you click OK, you return to your field, which remains in edit mode. You can change the value to a positive number, or press Esc to cancel the record edit or insertion.
Figure 4-15. Here, a validation rule of >0 prevents negative numbers in the Price field. When you enter a negative number, Access pops up a message box with the validation text you defined, as shown here. Once you click OK, you return to your field, which remains in edit mode. You can change the value to a positive number, or press Esc to cancel the record edit or insertion.

Writing a Field Validation Rule

As you can see, it’s easy enough to apply a validation rule to a field. But creating the right validation rule takes more thought.

Although validation’s limited only by your imagination, Access pros turn to a few basic patterns again and again. The following sections give you some quick and easy starting points for validating different data types.

Note

Access uses your validation rule only if a field contains some content. If you leave it blank, then Access accepts if without any checks. If this isn’t the behavior you want, then just set the Required property to Yes to make the field mandatory, as described in Section 4.1.

Validating numbers

For numbers, the most common technique’s to check that the value falls in a certain range. In other words, you want to check that a number’s less than or greater than another value. Your tools are the comparison signs < and >. Table 4-1 shows some common examples.

Table 4-2. Expressions for Numbers

Comparison

Sample Expression

Description

Less than

<100

The value must be less than 100.

Greater than

>0

The value must be greater than 0.

Not equal to

<>42

The value can be anything except 42.

Less than or equal to

<=100

The value must be less than or equal to 100.

Greater than or equal to

>=0

The value must be greater than or equal to 0.

Equal to

=42

The value must be 42. (Not much point in asking anyone to type it in, is there?)

Between

Between 0 and 100

The value must be 0, 100, or somewhere in between.

Validating dates

As with numbers, date validation usually involves checking to see if the value falls within a specified range. Here, your challenge is making sure that your date’s in the right format for an expression. If you use the validation rule >Jan 30, 2007, Access is utterly confused, because it doesn’t realize that the text (Jan 30, 2007) is supposed to represent a date. Similarly, if you try >1/30/07, then Access assumes the numbers on the right are part of a division calculation.

To solve this problem, use Access universal date syntax, which looks like this:

	#1/30/2007#

A universal date always has the date components in the order month/day/year, and it’s always bracketed by the # symbol on either side. Using this syntax, you can craft a condition like >#1/30/2007#, which states that a given date must be larger than (fall after) the date January 30, 2007. January 31, 2007 fits the bill, but a date in 2006 is out.

The universal date syntax can also include a time component, like this:

	#1/30/2007 5:30PM#

Note

When comparing two dates, Access takes the time information into consideration. The date #1/30/2007# doesn’t include any time information, so it’s treated as though it occurs on the very first second of the day. As a result, Access considers the date value #1/30/2007 8:00 AM# larger, because it occurs eight hours later.

Once you’ve learned the universal date syntax, you can use any of the comparison operators you used with numbers. You can also use these handy functions to get information about the current date and time:

  • Date( )gets the current date (without any time information, so it counts as the first second of the day).

  • Now( )gets the current instant in time, including the date and time information.

Note

A function’s a built-in code routine that performs some task, like fetching the current date from the computer clock.

Table 4-2 has some examples.

Table 4-3. Expressions for Dates

Comparison

Sample Expression

Description

Less than

<#1/30/2007#

The date occurs before January 30, 2007.

Greater than

>#1/30/2007 5:30 PM#

The date occurs after January 30, 2007, or on January 30, 2007, after 5:30 p.m.

Less than or equal to

<=#1/30/2007#

The date occurs before January 30, 2007, or on the first second of January 30, 2007.

Greater than or equal to

>=#1/30/2007#

The date occurs on or after January 30, 2007.

Greater than the current date

>Date( )

The date occurs today or after.

Less than the current date

<Date( )

The date occurs yesterday or before.

Greater than the current date (and time)

>Now()

The date occurs today after the current time, or any day in the future.

Less than the current date (and time)

<Now()

The date occurs today before the current time, or any day in the past.

Validating text

With text, validation lets you verify that a value starts with, ends with, or contains specific characters. You perform all these tasks with the Like operator, which compares text to a pattern.

This condition forces a field to start with the letter R:

	Like "R*"

The asterisk (*) represents zero or more characters. Thus, the complete expression asks Access to check that the value starts with R (or r), followed by a series of zero or more characters.

You can use a similar expression to make sure a piece of text ends with specific characters:

	Like "*ed"

This expression allows the values talked, walked, and 34z%($)#ed, but not talking, walkable, or 34z%($)#.

For a slightly less common trick, you can use more than one asterisk. The following expression requires that the letter a and b appear (in that order but not necessarily next to each other) somewhere in a text field:

	Like "*a*b*"

Along with the asterisk, the Like operator also supports a few more characters. You can use ? to match a single character, which is handy if you know how long text should be or where a certain letter should appear. Here’s the validation rule for an eight-character product code that ends in 0ZB:

	Like "?????0ZB"

The # character plays a similar role, but it represents a number. Thus, the following validation rule defines a product code that ends in 0ZB and is preceded by five numbers:

	Like "#####0ZB"

And finally, you can restrict any character to certain letters or symbols. The trick’s to put the allowed characters inside square brackets.

Suppose your company uses an eight-character product code that always begins with A or E. Here’s the validation rule you need:

	Like "[AE]???????"

Note that the [AE] part represents one character, which can be either A or E. If you wanted to allow A, B, C, D, you’d write [ABCD] instead, or you’d use the handy shortcut [A-D], which means “allow any character from A to D, including A and D.”

Here’s one more validation expression, which allows a seven-letter word, and doesn’t allow numbers or symbols. It works by repeating the [A-Z] code (which allows any letter) seven times:

	Like [A-Z][A-Z][A-Z][A-Z][A-Z][A-Z][A-Z]

As you can see, text validation expressions aren’t always pretty. Not only can they grow to ridiculous sizes, but there are lots of restrictions they can’t apply. You can’t, for instance, let the length of the text vary between a minimum and maximum that you set. And you can’t distinguish between capitalized and lowercase letters.

Combining validation conditions

No matter what the data type, you can also combine your conditions in two different ways. Using the And keyword, you can create a validation rule that enforces two requirements. This trick’s handy, because each field can have at most a single validation rule.

To use the And keyword, just write two validation rules and put the word And in between. It doesn’t matter which validation rule’s first. Here’s a validation rule that forces a date to be before today but later than January 1, 2000:

	<Date() And >#1/1/2000#

You can also use the Or keyword to accept a value if it meets either one of two conditions. Here’s a validation rule that allows numbers greater than 1000 or less than –1000:

	>1000 Or <-1000

Creating a Table Validation Rule

Field validation rules always apply to a single field. However, database designers often need a way to compare the values in different fields. Suppose you have an Orders table that logs purchases from your monogrammed sock store. In your Orders table, you use two date fields: DateOrdered and DateShipped. To keep everything kosher, you need a validation rule that makes sure DateOrdered falls before DateShipped. After all, how can you ship a product out before someone orders it?

Because this validation rule involves two fields, the only way to put it in place is to create a validation rule for the whole table. Table validation rules can use all the tricks you’ve learned about so far, and they can pull the values out of any field in the current record.

Here’s how to create a table validation rule:

  1. In Design view, choose Table Tools | Design → Show/Hide → Property Sheet.

    A box with extra settings appears on the right side of the window (Figure 4-16).

    Note

    You can create only a single validation rule for a table. This limit might sound like a problem, but you can get around it by using the And keyword (Section 4.3.2.4) to yoke together as many conditions as you want. The validation rule may be a little difficult to read, but it still works without a hitch.

    The Property Sheet shows some information about the entire table, including the sorting (Section 3.2.1) and filtering settings (Section 3.2.2) you’ve applied to the datasheet, and the table validation rule. Here, the validation rule prevents orders from being shipped before they’re ordered.
    Figure 4-16. The Property Sheet shows some information about the entire table, including the sorting (Section 3.2.1) and filtering settings (Section 3.2.2) you’ve applied to the datasheet, and the table validation rule. Here, the validation rule prevents orders from being shipped before they’re ordered.
  2. In the Property Sheet tab, set the Validation Rule.

    A table validation rule can use all the same keywords you learned about earlier. However, table validation rules usually compare two or more fields. The validation rule [DateOrdered] < [DateShipped] ensures that the value for the DateOrdered field is older than that used for the DateShipped.

    When referring to a field in a table validation rule, you need to include square brackets around your field names. That way, Access can tell the difference between fields and functions (like the Date( ) function you learned about in Section 4.1.3).

  3. Set the Validation Text.

    This message is the error message that’s shown if the validation fails. It works the same as the validation text for a field rule.

    When you insert a new record, Access checks the field validation rules first. If your data passes the test (and has the right data types), then Access checks the table validation rule.

Tip

Once you set the table validation rule, you might want to close the Property Sheet to get more room in your design window. To do so, choose Table Tools | Design → Show/Hide → Property Sheet.

Lookups

In a database, minor variations can add up to big trouble. Suppose you’re running International Cinnamon, a multinational cinnamon bun bakery with hundreds of orders a day. In your Orders table, you have entries like this:

	Quantity  Product
	10        Frosted Cinnamon Buns
	24        Cinnamon Buns with Icing
	16        Buns, Cinnamon (Frosted)
	120       FCBs
	…

(Other fields, like the ID column and the information about the client making the order, are left out of this example.)

All the orders shown here amount to the same thing: different quantities of tasty cinnamon and icing confections. But the text in the Product column’s slightly different. This difference doesn’t pose a problem for ordinary human beings (for example, you’ll have no trouble filling these orders), but it does create a small disaster if you want to analyze your sales performance later. Since Access has no way to tell that a Frosted Cinnamon Bun and an FCB are the same thing, it treats them differently. If you try to total up the top-selling products or look at long-range cinnamon sales trends, then you’re out of luck.

Note

This example emphasizes a point that you’ve seen before. Namely, databases are strict, no-nonsense programs that don’t tolerate minor discrepancies. In order for your databases to be useful, you need to make sure you store top-notch information in them.

Lookups are one more tool to help standardize your data. Essentially, a lookup lets you fill a value in a field by choosing from a ready-made list of choices. Used properly, this tool solves the problem in the Orders table—you simply need a lookup that includes all the products you sell. That way, instead of typing the product name in by hand, you can choose Frosted Cinnamon Buns from the list. Not only do you save some time, but you also avoid variants like FCBs, thereby ensuring that the orders list is consistent.

Access has two basic types of lookup lists: lists with a set of fixed values that you specify, and lists that are drawn from a linked table. In the next section, you’ll learn how to create the first type. Then, in Chapter 5, you’ll graduate to the second.

Note

The following data types don’t support lookups: Memo, Date/Time, Currency, AutoNumber, Yes/No, OLE Object, Hyperlink, and Attachment.

Creating a Simple Lookup with Fixed Values

Simple lookups make sense if you have a simple, short list that’s unlikely to change. The state prefix in an address is a perfect example. In this case, there’s a set of just 50 two-letter abbreviations (AL, AK, AZ, and so on).

To try out the process in the following list of steps, you can use the Bachelors table included with the online examples for this chapter (look for the DatingService.accdb database file). Or, you can jump straight to the completed lookup by checking out the DatingServiceLookup.accdb file:

  1. Open the table in Design view.

    If you’re using the DatingService.accdb example, then open the Bachelors table.

  2. Find the field where you want to add the lookup.

    In the Bachelors table, it’s the State field.

  3. Make sure your field has the correct data type.

    Text and Number are the most common data types that you’ll use in conjunction with the lookup feature.

  4. Choose Lookup Wizard from the data type list.

    This action doesn’t actually change your data type. Instead, it tells Access you want to run the Lookup wizard based on the current data type. When you select this option, the first step of the Lookup wizard appears (Figure 4-17).

    First you choose the source of your lookup: fixed values or data from another table.
    Figure 4-17. First you choose the source of your lookup: fixed values or data from another table.
  5. Choose “I will type in the values that I need”.

    Section 5.2.5 describes your other choice: drawing the lookup list from another table.

  6. Click Next.

    The second step of the wizard gives you the chance to supply the list of values that should be used, one per row (Figure 4-18). In this case, it’s a list of abbreviations for the 50 U.S. states.

    You may notice that you can supply multiple columns of information. For now, stick to one column. You’ll learn why you may use more in Section 5.2.5.

    This lookup includes the abbreviations for all the American states. This list’s unlikely to change in the near future, so it’s safe to hard-code this rather than store it in another table.
    Figure 4-18. This lookup includes the abbreviations for all the American states. This list’s unlikely to change in the near future, so it’s safe to hard-code this rather than store it in another table.
  7. Click Next.

    The final step of the Lookup wizard appears.

  8. Choose whether or not you want the lookup column to store multiple values.

    If you allow multiple values, then the lookup list displays a checkbox next to each item. You can select several values for a single record by checking more than one item.

    In the State field, it doesn’t make sense to allow multiple values—after all, a person can physically inhabit only one state (discounting the effects of quantum teleportation). However, you can probably think of examples where multiple selection does make sense. For example, in the Products table used by International Cinnamon, a multiple-value lookup would let you create an order for more than one product. (You’ll learn more about multiple value selections and table relationships in Chapter 5.)

  9. Click Finish.

    Switch to Datasheet view (right-click the tab title, and then choose Datasheet View), and then save the table changes. Figure 4-19 shows the lookup in action.

When you move to a field that has a lookup, you’ll see a down-pointing arrow on the right side. Click this arrow, and a drop-down list appears with all your possibilities. Choose one to insert it into the field.
Figure 4-19. When you move to a field that has a lookup, you’ll see a down-pointing arrow on the right side. Click this arrow, and a drop-down list appears with all your possibilities. Choose one to insert it into the field.

Adding New Values to Your Lookup List

When you create a lookup that uses fixed values, the lookup list provides a list of suggestions. You can choose to ignore the lookup list and type in a completely different value (like a state prefix of ZI), even if it isn’t on the list. This design lets you use the lookup list as a timesaving convenience without limiting your flexibility.

In many cases, you don’t want this behavior. In the Bachelors table, you probably want to prevent people from entering something different in the State field. In this case, you want the lookup to be an error-checking and validation tool that actually stops entries that don’t belong.

Fortunately, even though this option’s mysteriously absent in the Lookup wizard, it’s easy enough to add after the fact. Here’s what you need to do:

  1. In Design view, go to the field that has the lookup.

  2. In the Field Properties section, click the Lookup tab.

    The Lookup tab provides options for fine-tuning your lookup, most of which you can configure more easily in the Lookup wizard. In the Row Source box, for example, you can edit the list of values you supplied. (Each value’s on the same line, in quotation marks, separated from the next value with a semicolon.)

  3. Set the Limit to List property to Yes.

    This action prevents you from entering values that aren’t in the list.

  4. Optionally, set Value List Edits to Yes.

    This action lets people modify the list of values at any time. This way, if something’s missing from the lookup list, you can add it on the fly (Figure 4-20).

If you set Value List Edits to Yes, an icon appears under the lookup list when you use it (left). Click this icon to open an Edit List Items dialog box (right) where you can edit the items in the lookup list and change the default value.
Figure 4-20. If you set Value List Edits to Yes, an icon appears under the lookup list when you use it (left). Click this icon to open an Edit List Items dialog box (right) where you can edit the items in the lookup list and change the default value.

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