johannarangel/finalproject_yelpgooglemaps

LABS Final Project: Yelp_GoogleMaps_Reviews - Roles: Data Engineer, Data Analyst, Machine Learning Engineer, Data Scientist | Bootcamp Henry: Data Science Career | DataFT Cohort 17

finalproject_yelpgooglemaps's Issues

3.10. Incremental Data Loading

4.2 Connect Power BI Dashboard to Google Cloud

3.8. Create definitive ETL's (ML)

Make the presentation for the demo 2

III. Sprint 2: Data Ingest & Process

1.3.1. Agile

2.10. Wiki - Technical Report

1.1.3. Define Company Name/Create Logo

We use AI - ChatGPT / Bard

2.5. Exploratory Data Analysis (EDA)

2.6. Industry / Category / Business Selection

4.1 Calculation of KPI Indicators

1.2.4. Research About Cloud Technology / Pipeline

2.9. Define Key Performance Indicators (KPIs)

2.11. Make the presentation for the demo 1

1.1. GitHub Repository

4.3 Creation of the Dashboard for Demo

3.1. Wiki - Technical Report (Update)

II. Sprint 1: Project Launch

Setting up the development environment and preparing tools. Preliminary data collection and analysis. Designing the system architecture and project planning.

During Sprint 1, the team will focus on the initial project setup. This includes configuring the development environment, installing and setting up key tools and technologies. Preliminary data collection and exploratory analysis will be conducted to understand the data quality and structure. The team will also dedicate time to training sessions, upskilling, and gaining proficiency in the specific tools and technologies required for the project. Additionally, the system architecture will be designed, defining databases, cloud infrastructure, and core components. Detailed project planning, resource allocation, and client goal review will also be integral to this sprint.

3.3. Define Architecture

3.4. Create Project in Google Cloud Platform

1.2.2. GoogleMaps DataSets Preliminar Analysis

1.2.2. Upload parquet files

2.2. Define Roles and Responsibilities

3.7. Create definitive ETL's (Data Analysis)

2.3. Extract, Transform, and Load (ETL) Yelp

2.8. Technological Stack

1.2.3. Investigate About Work Methodology

2.7. Project Scope / Goals

3.9. Batch Data Loading

2.12. Demo 1

1.3.3. CRISP-DM

Cross-Industry Standard Process for Data Mining

Demo 2

IV. Sprint 3: Data Analytics & ML

Presenting final results, demonstrating models, and reviewing with the client.

The third sprint will be the culmination of the project, with the presentation of the final results to the client. A detailed demonstration of the developed machine learning models will be conducted, and the analyses and conclusions derived from the project will be presented. A thorough review with the client will take place to ensure alignment with the initial project objectives, and final adjustments will be made as necessary.

3.2. Wiki - Executive‐Summary (Update)

3.5. Pipeline.py

1.1.1. Create Repository/Contributors

Create public repository ProyectoFinal_YelpGoogleMaps

3.6. Initial Connection and Load Tests

1.1.6. Create/Update Wiki/Upload Documents

1.1.4. Create Repository Structure

1.1.2. Create Branches/Project

We decided to create a branch for each team member and restrict the main one in which we will be applying only the final changes through requests

1.2.1. ETL's Preliminar Analysis

1.2. Understanding the Current Situation

1.1.7. Wiki - Guidelines

2.4. Extract, Transform, and Load (ETL) Google

1.1.8. Wiki - Executive Summary

2.1. Choose Work Methodology

1.3.2. Scrum

I. Sprint 0: Preparation and Initial Planning

3.11. Diagrams and Workflows

Wiki - Executive Summary (Update)