Crystal Reports Administration: Data Validation

The subject of data validation is extensive and no article is going to provide complete coverage of the topic. The purpose of this article is to point out some key factors you should consider so your Crystal Reports tend to reflect accurate data.

While there is a definite line between Crystal Reports administration and database administration, the CR administrator may be the first one blamed if a report isn't accurate. In many situations, the two functions are occupied by one person. Where this is not the case, the people occupying the two functions benefit from working together. For one thing, when users stop trusting your Crystal Reports, there will be a decreased need for your services. So, you have a vested interest in database accuracy.

Your database is only as good as the information provided to it. Various database programs offer various data input validation functions for the designer to implement in an input screen. Examples include:

• Field length
• Minimum number of characters
• Data type
• Letter case
• Comparison to another field

While these tools are good, they are basically concerned with the format of the data. The reason for that focus is the limitation of automation. To accomplish a higher level of data validation, you must use education rather than automation. People can still enter poor or inaccurate data, while meeting format requirements.

Rather than try to exhaust this subject (and you) in the space of an article, let's look at a case history you can draw lessons from.

Steve was a supervisor in the research department of a magazine company. One day, he happened on the Website of one of the magazines his company put out. He noticed a link called "Reader Response," so he clicked on it. This showed some nice pie charts of what readers allegedly thought of the usefulness the articles in each issue.

Steve contacted the editor, and asked about this. The survey methods violated several principles of survey design. For example:

• The surveyed population was very small. Some articles had responses from only 5 readers out of 120,000.
• The population was self-selecting, and the bias was toward a particular type of reader rather than a representative spectrum of readers.
• The readers were to rate the articles as Excellent, Good, Fair, Average, or Poor. Only "Poor" is negative, so the bias in this survey was atrocious.
• Some range of responses for each article in each issue ranged from a few hundred to only 5--thus, the response density was inconsistent and comparison was meaningless.

Steve asked the editor if these results were every surprising or inconsistent with the staff's expectations, and the editor responded that they were. Steve then pointed out the invalidity of the survey.

The lesson here is you, as a Crystal Reports administrator, should not rely on automation to ensure the database contains accurate information. You must question the means of data collection. If you are not responsible for the entire database process, take heart--you have an opportunity to build a mutually beneficial working relationship with everyone involved in the process. Not only will that improve the usefulness and reliability of the Crystal Reports you are responsible for, but it will improve your personal network of contacts in an age of disappearing IT jobs.

See also:

• Data accuracy issues

• Data Parameter Validation

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