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!
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AWS Big Data: Big Data collected and processes under AWS. AWS was
the earliest Cloud platform.
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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
***Architected Projects
(i)
General IT Projects Architecture Details:
Projects Architecture Details in general IT Software Development I have completed, dozens
of pages to even over a 1000 pages for each design ...
(ii)
Engineering
Projects Architecture Details: Projects Architecture Details on
Engineering Software Development I have completed, dozens
of pages to even over a 1000 pages for each design ...
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