---
# System prepended metadata

title: Data Architect

---

#    Data Architect
> ref : [Data Architect_數據架構師｜OpenNet_開網｜台北市－104 人力銀行](https://drive.google.com/file/d/1aLzdv1H9ISK331XRcGUUC7ydQ9xOeBAD/view?usp=sharing)

## Key Purpose :
- Positive
    1. Build the skill of next stage of career. 
    2. Keep motivate in career.
    3. Learn more english.
- Passtive
    1. Fill the gap from the position. 
    2. Find point worth to learn in the compangy. 

## Requirement
- Large-Scale RDBMS and Data Model.
    - Redshift.
    - MySQL and MongoDB.
- AWS.
    - AWS RDS, EC2.
    - AWS CloudWatch, Secrets Manager, etc.
- Open Source.
    - Airflow.
    - Metabase.
    - CentOS.

## Study Point
- Large-Scale RDBMS, like MySQL or Redshift.
- MongoDB.
- AWS Cost Management.
- AWS EC2 Linux like CentOS.
- Airflow.

## Study List
- Large-Scale RDBMS.
    - how to handling large-scale data in MySQL.
    - how to handling large-scale data in Redshift.
    - how to handling large-scale data in MongoDB.
    - what is MongoDB?
        - why using MongoDB instead of others?
        - why MongoDB so rich?
- AWS
    - how to manage cost in aws?
        - what is AWS CloudWatch and how to use it?
        - what is AWS Secret Manager and how to use it?
- Open Source
    - how to use Metabase?
        - the best practice of Metabase.
        - the tips and tricks of Metabase.
        - why using Metabase reviewed by reddit.
    - what is CentOS?
        - why using CentOS instead of normal linux?
        - what is the benefit of using CentOS.
    - what is the best practice of using Airflow?
        - the tips and tricks of Airflow, <br/> like the top point to list down. 