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How to set up Different Kinds of Apps

Data Management Apps

Apps that provide both data entry and data analysis functions can use the DataGater “GaterBase” component as their primary data repository.  Customers collect and edit their data directly into their project’s GaterBase.  When they want to begin analysis, they pay through the DataGater service, and their app converts the RAW data to PAID. The PAID data is now available for whatever analysis or export routines the app has provisions for. Users can’t use the app’s analysis or export functions without paying.

FlowChart - Paying for Data Management Apps

Data Entry Apps

With a data entry program, users configure and enter/review/edit the RAW data for free. When they are ready to analyze, they pay through DataGater, and the app exports the data in whatever open format they choose. The GaterBase repository is currently pre-wired to export PAID data into a MS Access database with a single method call.  The code samples supplied with this kit contain routines for exporting to ASCII (CSV) files and XML file formats.  Users can’t export their data into analyzable format without having first paid through DataGater.

Flow Chart - Paying for DataEntry Apps

Analytics Apps – Direct Access Model

If you are writing a brand new analysis app for DataGater billing, you may decide to do all data access directly from the GaterBase repository.

The customer, starting with an existing data file, imports it into the app, which packs it into a GaterBase repository. After paying they can then proceed to the analysis. Without paying, they can edit, but they can’t analyze.

  Flow Chart - Paying for Analytics - Direct Access

Analytics Apps – Using existing code.

If you have an existing analytics app and would like to adapt it to DataGater billing, there are two ways of doing so: one way exports paid-for data to a new file in a format that is compatible with your existing code, the other continues to work on the original data source.  Both entail data-validation components that ensure that all the analyzed data has been properly paid for.

 

To customers, the principal difference from earlier versions is that rather than paying a flat fee for the app up front, they now pay once per project, after data acquisition, at a fee based on project size.  The analysis procedures of the app cannot be used unless the data it uses is verified as paid-for

Exported Data Model 

Flow Chart - Paying for Analytics using existing code

Original Data Model

Flow Chart - paying for Analytics on original data

Data Vending

If you are selling access to pre-collected data, the implementation of DataGater billing is even more direct.  First pack your proprietary data into a GaterBase repository, as RAW data.  You can now distribute the whole, unpaid file to customers for free.  When they want to access all or part of it, they select what they want, pay for it through DataGater, and get the paid-for data in whatever format they (or you) choose.  They cannot get the data into an aggregation-capable format without having paid for it.

 This gives you, the data vendor, a simple way to let the customer do the selection and slicing off of the data they want with no burden, infrastructure or bandwidth on your part, while it gives the customer direct control over what they get – along with fair pricing that reflects the value they get.

Flow Chart - Paying for Data - Vending Model