Data Science and Data analytics

Data Science and Data analytics

1. Key Performance Indicators (KPIs)

   • Definition
     • Measurable value for strategic goals
     • Navigation tools for performance
     • Form of communication
   • SMART criteria
     • Specific
     • Measurable
     • Attainable
     • Relevant
     • Time-bound
   • Types & Levels
     • High-level: Overall performance
       • Low-level: Departmental processes
         • Categories: Business, Finance, Sales, Marketing, Project Management
   • formulation questions
     • Desired outcomes
       • Improvement measures
         • Data availability
           • Target audience
     • Visualization methods
       • Review frequency

2. Critical Philosophy

   • Application in Cinema and Reality
     • The "Map is Not the Territory
       • "semantic disturbances" and systemic failures
       • "semantic disturbances" and systemic failures
       • Margin Call & The Big Short
         • The Financial Crisis
           • David created a data science model that was used to measure the risk of CDOs
           • vastly more correlation than anyone realized from the historical data
           • The films illustrate what happens when data scientists and decision-makers forget that models are imperfect approximations of the world

3. CRISP-DM Methodology

   • 1. Business Understanding
     • Define goals
   • 2. Data Understanding
     • Collection and quality verification
   • 3. Data Preparation
     • Cleaning and selection
   • 4. Modeling
     • Selecting techniques
   • 5. Evaluation
     • Reviewing results against business objectives.
   • 6. Deployment
     • Monitoring and reporting results.
   • this reliance on dashboards contributed to the crisis shown in the films

4. Career Path: Data Scientist

   • Core Skills
     • Tools: Python, R, SQL, Tableau, Excel
     • Data: Pre-processing & Insight extraction
     • Business: Market expertise
     • Soft Skills: Communication & Curiosity

5. Technological Evolution

   • Business Intelligence (BI)
   • Big Data & Machine Learning

6. Data

   • names and numbers to answer questions and achieve objectives.