1. Gather Data
1.1. Data Requirement
1.2. Data Collection/Acquisition
1.2.1. Data Ingestion
1.2.1.1. Data Types
1.2.1.1.1. Unstructured Data
1.2.1.1.2. Structured Data
1.2.1.1.3. Semi-Structured Data
1.2.1.2. Data Sources
1.2.1.2.1. API
1.2.1.2.2. Databases
1.2.1.2.3. Data Warehouse
1.2.1.2.4. Data Files (e.g. CSV, XLS, JSON)
1.2.1.3. Data Pipiline
1.2.1.3.1. Streaming
1.2.1.3.2. Batch
1.3. Data Understanding
1.3.1. Descriptive Statistics
1.3.2. Exploratory Data Analysis
2. Business Understanding
2.1. Define Problem Statement
2.2. Define Project Objective
2.3. Stakeholder Buy-In
3. Analytic Approach
3.1. Techniques
3.1.1. Clustering
3.1.2. Classification
3.1.3. Regression
4. Methodology
4.1. CRISP-DM
4.2. Team Data Science Process (TDSP)
4.3. OSEMN
4.4. Knowledge Discovery in Databases (KDD)
5. Feedback
5.1. Model Refinement
5.2. Redeployment
5.3. Model Performance Monitoring
6. Deployment
6.1. Data Visualization
6.1.1. Tools
6.1.1.1. Data Studio
6.1.1.2. D3.js
6.1.1.3. Plotly
6.1.1.4. Tableau
6.2. Data Reporting
6.2.1. Decision Making
6.2.2. Business Intelligence
6.3. A/B Testing
6.4. Tools
6.4.1. Web Frameworks
6.4.1.1. Flask
6.4.1.2. R Shiny
6.4.1.3. Node.js
6.4.2. Cloud
6.4.2.1. Google Cloud
6.4.2.2. AWS
6.4.2.3. Heroku
6.4.2.4. Azure
6.4.3. Container
6.4.3.1. Docker
6.4.3.2. Kubernetes
7. Modeling
7.1. Predictive Analysis
7.2. Machine Learning
7.2.1. Classification
7.2.2. Regression
7.2.3. Clustering
7.2.4. Recommendation
7.2.5. Anomaly Detection
7.2.6. Dimension Reduction
7.3. Tools
7.3.1. Programming
7.3.1.1. Python
7.3.1.2. R
7.3.1.3. Java
7.3.2. Machine Learning/Deep Learning Libraries
7.3.2.1. Scikit-Learn
7.3.2.2. Numpy
7.3.2.3. Pytorch
7.3.2.4. TensorFlow
8. Evaluation
8.1. Statistical Significance Test
8.2. Diagnostic Measures
8.2.1. Testing Set
8.2.2. Validation Set
8.2.3. Cross-Validation
8.2.4. Fine-Tuning
9. Data Preparation
9.1. Data Cleaning
9.1.1. Outliers
9.1.2. Duplication rows
9.1.3. Missing Value
9.1.4. Formatting
9.2. Feature Engineering
9.3. Data Transformation
9.3.1. Aggregation
9.3.2. Binning
9.3.3. Feature Selection
9.4. Text Analysis
9.5. Tools/Libraries
9.5.1. Pandas
9.5.2. Scipy
9.5.3. Dplyr
9.5.4. spaCy