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Fees
| Initial Consultation |
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There is no charge for the initial consultation. |
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| Hourly Fee |
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All work is charged at the rate of $80/hr.
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| Data Cleanup |
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Data cleanup is charged at the regular rate of $80/hr. See below for additional details about data cleanup.
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| Typical Database Costs |
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The following cost table is very general because of the tremendous variation in database application requirements. The actual cost depends on both the number and complexity of the various forms, reports, scripts, and field rules and must be evaluated for each specific application.
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| Typical costs for a professionally developed database. |
| Basic |
Intermediate |
Advanced |
| 3-5 primary data tables |
6-12 primary data tables |
10-30 primary data tables |
| 3-10 custom scripts |
10-30 custom scripts |
20-100 custom scripts |
| 3-5 main screen forms |
6-12 main screen forms |
10-30 main screen forms |
| 3-5 reports |
6-12 reports multi-user
(2-5 users) |
10-30 reports multi-user |
| single computer |
multi-user (2-5 users) |
multi-user |
| simple security |
existing security routines |
custom security |
| $2,000 - $8,000 |
$5,000 -$25,000 |
$8,000 - $40,000 |
Just what is 'Data Cleanup' and why is it needed?
Many existing databases have 'bad' data which needs to be corrected before the new database can function correctly. This can happen regardless of the original data structure but databases which were originally kept as a spreadsheet are particularly susceptible to this type of problem because, unlike a professionally designed database application, spreadsheets have little, if any, means of controlling the data that is entered. The need for cleanup could be the result of any number of things such as:
- Values that have been entered as the wrong type - dates or numbers entered as character fields.
- Capitalization errors - The Abc Tool And Die Company -or- THE ABC TOOL AND DIE COMPANY instead of The ABC Tool and Die Company. And, of course, Mcdonald instead of McDonald.
- Values out of range - bill payment dates for the year 0299 or 2099, a value of 132 in a percent field with a range limit of 1-100.
- Fields not properly separated - city, state, and zip in one field and first, middle and last name in one field are common examples of this.
- Address fields with the street address and post office box on the same line.
- ... and many others.
The extent of these data errors is usually difficult to determine until the new application has at least reached the stage of minimal functionality. This means that data cleanup is an extra cost that usually cannot be determined until after significant work as been completed. In some cases, the data cleanup itself has taken as much as two full days. It is always possible for the client to do the cleanup but, due to the inherent efficiencies of using the database itself for the cleanup process and the developer's knowledge of the specific requirements, it is often more cost effective to have it done by the developer. In addition, AIMS DataCom has already built some proprietary routines which can significantly reduce cleanup times for certain types of data.
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