Project Timeline - The Stages

Stages of the Career Statistics Tool (CST) Project


The CST project started in June 2019 and is scheduled for completion in September 2019. The stages below documents all the major tasks. Learning and accomplishments are documented in posts per participant.

Intermediate stages:


  • Stage 1: Getting Started
  • (June 2019)
    1. Researching prior work in this area
    2. Identifying technical requirements
    3. Identifying logistical requirements
    4. Creating organizational system for CST documents (Google Drive)
    5. Project Specifications document


  • Stage 2: Team Assembly
  • (June 2019)
    1. Recruiting. Team is a mix of interns and other students.
    2. Information meetings
      1. Understanding STEM-Away
      2. Understanding CST
    3. Project management tool
      1. Initial set of tasks identified and entered


  • Stage 3: Group Discussion and Assigning Responsibilities
  • (July 2019)
    1. First All-Team Meeting
    2. Assigning Tasks
    3. Researching
      1. Google Cloud Platform
      2. Data sources (API’s)
      3. Database technologies
      4. Web App technologies
      5. Visualization Tools
    4. Team Discussions
      1. Django or Flask (web app)
      2. BLS, CareerOneStop, Indeed API, Glassdoor API, or something else (data sources)
      3. PostgreSQL or mySQL (database)
      4. Data Studio, Pandas, Google API’s, Big Query, a combination, or something else (visualization)


  • Stage 4: Career Fair and The New Asana
  • (July 2019)
    Note: By now the whole team understands STEM-Away’s mission and the details of our specific project. We have researched, discussed, and decided which options suit the project best.
    1. Showcasing STEM-Away at Santa Clara Convention Center
    2. Asana, new project management structure created
    3. Weekly All-Team Meetings


  • Stage 5: Prototyping p.1
  • (August 2019)
    1. Creating the Python-Django virtual environment and web application skeleton
    2. Deploying to GCP
    3. Choosing/Researching visualization chart types
    4. Dashboard UI Prototype
    5. Making a request to BLS API
    6. Weekly All-Team Meetings


  • Stage 6: Prototyping p.2
  • (August 2019)
    1. Decoding BLS API URL codes
    2. Chart prototypes
    3. ERD
    4. Choosing BLS Data
    5. Designing the database schema
    6. Coding the database schema in the web application(models.py)
    7. Manual data entry (phase 1)
    8. Coding Script to pull data into our database tables (phase 2)


  • Stage 7: Present Day
  • (September 2019)
    1. Checking that the data persists and is accurate
    2. Final chart prototypes
    3. Embed charts into web application
    4. Written Work
      1. Database design documentation
      2. Python-Django app documentation & comments
      3. CST Admin
    5. Deciding future project goals
      1. Forum Integration
      2. Scripting all manual parts
      3. Machine learning


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