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- Understanding database design concepts
- Using the Text to Columns feature
- Creating fields
- Using tables
- Adding total fields
- Formatting tables with the Design tab
- Using the Form tool to build and view data
- Using data validation to restrict data entries
Skill Level Appropriate for all
If you work with database software, for example, Access, you're probably familiar with the idea or the concept where each column or each field should contain the minimal amount of information necessary. And that's a bit vague. This particular worksheet has four potential problems, three major ones. As you look at this list, you might at some point say, well; I want to sort this by last name. Well, look at the data in Column A, first name, last name. That's great for mailing labels, but we cannot sort this list based on the data looking like that.
Ideally, we should have those names either in separate columns, or we need to reverse the order. And similarly in Column C, if we wanted to sort this data by State or by Zip code, we cannot do that. And so the idea that each column should contain a minimal amount of information, starts to make a little bit of sense. Ideally, we should have a separate column for City and State and Zip. And if we have hundreds and hundreds of records, thousands of records, not only do we want to sort by State, but we want to have within each State, have those in order by City.
So it would make good sense to split those into separate columns. Column B, perhaps less of an issue, depends upon the nature of the data, but you can imagine if this were data for a City Department, the Waterworks or the Street Works Department. If they need to notify people within a certain range of addresses on Harrison Street, there is no way to sort this data by Street name. And so, again, depending upon the nature of the data and what you're doing with it, the idea that you want to split your data into more columns is a good one. And it's much easier to pull data together when it's in separate columns, than to pull it apart when it's like the data we see here.
And in Column D we're seeing an unorthodox use of dates. We can all read them and understand them, but we can't work with dates like that in any kind of computational sense. And all these different issues of cleaning up data, you'll get some good tips in the lynda.com course on Cleaning up Your Data. All of the issues here can be dealt with directly and ultimately they can be fixed. But this is not good design from a number of different perspectives. Keep a minimal amount of data in each column, and then your use of database features and efficient use of Excel is going to improve greatly.