top of page

Revolutionizing Enterprise Systems with Automated Data Transfer

Data transfer is the fourth of five principles that will allow us to create open-source enterprise systems that have an inherent capability to exchange data and aggregate it for reporting and AI.

Data transfer enables systems to automatically share master and transaction data without requiring any programming. It provides a way to enter data once and share it securely with other systems that need it, allowing the creation of a global network where all systems can exchange data.

The data transfer feature is based on a decentralized architecture, where each system is a self-contained enterprise system that exchanges data via a central data server. This server hosts data that is communicated between publisher and subscriber systems and currently operates on AWS but could be converted to a blockchain repository.

Data transfer will allow us to address the insurmountable challenges we currently have with conglomerates. It enables the creation of fully contained enterprise systems by business unit, which can be networked together to securely share data without requiring redundant data entry. Furthermore, it is the cornerstone that makes it possible to automatically aggregate data from many business unit systems into a data warehouse for reporting.

Data transfer includes the following ten features:

1. Identifies logical groupings of records (record groups) that need to be exchanged.

2. Identifies groups of systems (subscribers) that have an interest in the data

3. Allows subscriptions to record groups by subscribers for single records, multiple records controlled by a filtering clause, or all records within a table.

4. Leverages built-in features for audit logging, enabling automatic broadcasting of data changes.

5. Provides a subnet capability for conglomerates, which automatically moves data from the publisher to the subscriber without going through the public data server.

6. Allows information to be redacted by setting attributes to specific values based on business rules.

7. Automatically exports header data for foreign key references.

8. Integrates with a central data dictionary.

9. Leverages QR Codes for manual data exchange.

10. Includes the following features for importing data:

a) Allows business units to assess whether updates of a particular type will be reviewed and approved or automatically applied.

b) Flags differences in database structures and integrity rules between the publisher and subscriber.

c) Allows users to view the change history log before applying updates.

Data transfer builds upon the first three principles – globally unique primary keys, core data models and record governance.

For further information on automated data transfer, please check out .

I appreciate your comments, questions and likes.

Thank you for your attention.

1 view0 comments

Recent Posts

See All

In this post I am going to describe the financial roll-up procedure that was developed using Postgres that is a part of an enterprise system platform that has an inherent capability to exchange data b

In this post, I have a #QuestionForGroup about creating an application framework to connect to the open-source platform I created using Postgres. The platform allows us to create enterprise systems th

In this post I am going to describe the data warehouse generate procedure (DW procedure) that was developed using Postgres that is a part of an enterprise system platform that has an inherent capabili

bottom of page