Data System Architecture
(Data System Architectures)
 

Data System Architecture

 - Almost in every of my past project

 - Data Collection, Data Processing, Data Modeling, etc. Cloud computing is good for remote operation; Big data is good to fast and workable operation.

- DevOps: Multiple ways for Data Processing.

Data System Architecture Projects Examples

Most projects started with Data. Quite a portion of my over 200 projects completed during consulting are the Data Systems. Data should be collected (via Cloud computing or local operation) and processed (via Big Data, modeling, etc.).

  - Data System: Most of my projects, software or even engineering AI related, started from designing data systems. I completed the projects either via direct modeling plus ML if I am familiar with the industries, or via Deep Learning for influences of multiple parameters in the final goals (productivities or qualities), if I am not familiar with the industry.

  - Data Modeling: Data processing based on accurate data model; High accuracy achieved via Machine Learning; Multi-Levels automation systems were integrated.

 - Database: Most of the database system I used in the industries are Oracle, e.g. in company C1, N1 and  S1. Other large systems are such as Informix (in E1). I rented SQL2000 with $50/mo for over 10 years to host my website www.metalpass.com. There are other free DBMS and also NoSQL DB that I used in my projects.

 - AWS Data: Cloud is an important way for data collection. Also as data servers (usually in data centers) and clients (usually in production lines) were not in the same location, Cloud computing was an essential way to finish the projects. This happened initially in the company B1.

 - Azure Data: Whatever my clients use certain Cloud platform, I should use. Due to my success in AWS Cloud computing, many companies who use Azure accepted my suggestion to use Cloud computing, so Azure are also frequently used in my projects.

 - Big Data: My projects usually handle large system. For example, even in my early projects I fixed several large systems, each with about 1 million lines of source code. With such large systems, my technical strength was fully demonstrated! If you fix one problem, you need to modify often dozens of related functions. Otherwise you will create big trouble for your clients. During projects, large amount of data were involved. Most Oracle DBMS needs to get rid of data (to backups, etc.) every three months!

 - AWS Big Data: Big Data collected and processes under AWS. AWS was the earliest Cloud platform.

 - Azure Big Data: Big Data collected and processes under Azure. Microsoft tool sets were the primary ones for my projects.

 - Cloud Big Data: Big Data collected and processes with Cloud computing..

 - Further Data System: e.g. a set of MES packages in the special categories, and so on.
　

Personal Quality

• High Quality & Low Cost Strategies: Clients usually have 1000% profits ...
  　

• Architect related Experiences: My Architectural project experiences, e.g. High Accuracy of models, Integration and Software architecture ...
  　
•  Personal Quality: Double Ph.D., over 200 projects completed, 25 years experiences...