Software-based visualization of a go-to market optimization model
Journals
05/05/2023 (Group Meeting)
Finished up all documentations
Added backend tests
Finished the hand-off plan
04/25/2023 (Group Meeting)
Added frontend tests
04/24/2023 (Coach Meeting)
Talked about the handoff plan
Talked about the final presentation
04/23/2023 (Group Meeting)
Finishing up final presentation sliders
Finishing up final presentation demo
Fix some error on our simulation app
04/21/2023 (Group Meeting)
Distribute final presentation tasks to each member
04/20/2023 (Client Meeting)
Show our simulation app to Mr. Hughes
Show our template to client
Demonstrate the simulation input template to our client
04/19/2023 (Group Meeting)
Create a scoreboard to show the quarterly win and loss.
Decide to use the alertify.js package for error handling.
04/09/2023 (Group Meeting)
Finished up the Tech Talk presentation slides.
Practice the presentation together.
Finished up the documentation plan assignment.
04/07/2023 (Group Meeting)
Discuss the role for each member in the Tech Talk.
Create the google slides for the Tech Talk.
04/06/2023 (Group Meeting)
Set up the Nivo package.
Graph the data fetch back from the Lambda Function using Nivo Package.
04/05/2023 (Group Meeting)
Finished up the AWS Lambda Function.
Now our frontend can call the lambda function and get the response of data.
04/04/2023 (Group Meeting)
Configure the AWS Lambda Function.
Host the application using AWS Amplify.
04/03/2023 (Coach Meeting)
Discuss the parsing csv file with coach.
Review the test plan with coach.
04/02/2023 (Group Meeting)
Meeting as a group to discuss the parsing of uploaded csv file.
Finished the parsing code in JS to parse csv file to different arrays.
Next step is to format the data into JSON in order to input it to the AWS Lambda function
03/30/2023 (Client Meeting)
Meeting with AWS people and get clarification for AWS architecture.
03/26/2023 (Group Meeting)
Discussed the values and impacts of our project
Finished the APPLES Reflection and published into our website
03/23/2023 (Client Meeting)
Send some questions to client about AWS:
If we use Amplify to connect to a DynamoDB database, what is the best way to store user specific variables? Would we need to set up Amazon Cognito to do this?
Can we define a new API that takes user input from the React front-end and calculates the simulation output using Amplify? (Possibly using the “amplify add api” command)
If so, what is the best way to incorporate the existing Python code that does the calculation?
03/20/2023 (Coach Meeting)
Discuss simplifying UI design because of time constraints
Show demo of simple AWS app
Discuss solutions to testing problem (need to set random numbers to be consistent in excel)
03/20/2023 (Group Meeting)
Talk about simple AWS Amplify app created to gain familiarity with AWS technologies and set-up
Discuss how we want to structure code and combine front end (React) with the Python simulation
Go over potential problems with setting the Excel seed for testing (cannot do this in Excel directly, but may be able to use Jupyter notebook)
03/06/2023(Coach Meeting)
Discuss visual representation of model
Need to update y-axis to be consistent from week to week in simulation output
Talk about potential architecture changes involving code optimization by baking model into front end, but this may not be necessary
03/02/2023(Client Meeting)
Demonstrate model with graph output and discuss potential changes
Discuss implementation of sliders
Meet with AWS team to discuss cloud hosting and database storage for the application
02/27/2023(Coach Meeting)
Discuss model updates, code formatting, as well as the Ethics assignment
02/26/2023 (Group Meeting)
Practice for midterm presentation
02/20/2023 (Coach Meeting)
Discuss the model demo with Louie
Show the model input/output flowchart to Louie
02/20/2023 (Group Meeting)
Explore the model in Python
Add more documentations in user stories
Midterm presentation coming up
02/16/2023 (Client Meeting)
Mr. Hughes verified the flow chart with us
Show Mr. Hughes our draft model on Pycharm
Clarify the the input file format of the model
02/16/2023 (Group Meeting)
Discuss the next step for replicating the model
Allowing more input variables into the model
Discuss how to read the input file into our model
Discuss the upcoming platform selection assignment
Decide what programming languages, libraries, framework to use in our project
Languages: Python (Client Preference), JavaScript (Recommended by Client)
Frameworks: React
Libraries: NumPy, Plotly
Hosting: AWS (Client Preference)
Database: AWS (Client Preference)
02/06/2023 (Coach Meeting)
Show the Excel model to coach
Recommend to draw a flow chart of the model
Need to add low-level user stories on our website
First priority is to understand the data flow of the Excel model
02/02/2023 (Client Meeting & Followed be a Group Meeting)
Met with Mr. Hughes at the new Launch Chapel Hill.
Mr. Hughes presented his go-to market simulation model to us on Excel. He explained how the model works and what is his expectations of the MVP software.
We introduced our February plan to Mr. Hughes (https://docs.google.com/document/d/154e-Iy9etBTzYXAUiN1DbzGwKw6T1V_S2fGvKKX6u2E/edit?usp=sharing)
Replicate the Excel model in Python (Pycharm?)
Variables, changeable opportunities…
Use fake data
Push to Github for now
Test Plan: Perform unit tests for the model, ask professors to verify the python model with us
Possibly need to do data transfer. How do clients give their data? In what format?
Logs, csv, excel, json files?
Create a structural object to save this data (SQL).
Test Plan: Test the python model with real data.
We decided our next step is to replicate the model functionalities in Pycharm.
01/30/2023 (Coach Meeting)
Talks about our progress with coach Louie, our project is very straightforward and has a list of tasks to do.
Achieved the plan for last week, finished User Stories, finished updating our website.
The next step we need to do is to ask Mr. Hughes to present his Excel model with us.
01/26/2023 (First In-Person Client Meeting)
Meet with our client Mr. David Hughes
Mr. Hughes introduces his kinetik project to us
Weekly in-person client meeting at Launch Chapel Hill on Thursday at 3:30 pm
Define 10 technical sprints for the project
Upload file to AWS through kinetik.solutions
Convert Figma design to AWS Amplify interface
Validate forecasting model with UNC Statistics professor or grad student
Review excel model and replicate functionality in Python (test Jeff’s code)
Publish code to AWS from GitHub
Meet with Amazon Development team weekly
Meet with K-F MBA team to hear market feedback
Natural Language Processing model for sales and marketing issues, best practices and optimization methods
Recruit technical mentors (Data Science, Statistics / Monte Carlo, AWS)
Determine JavaScript vs. TypeScript (https://www.toptal.com/typescript/typescript-vs-javascript-guide)
Created an iMessage group chat with Mr. Hughes
01/20/2023
Change one of our project prefrences
01/18/2023 (Group Meeting 2)
Discuss team rules
Assign team roles
Discuss every member’s skill stack
Read through all projects together and select projects 6 project prefrences
01/13/2023 (Group Meeting 1)
First group meeting!
Created our group website
Discuss every member’s availability and assign weekly meeting time