Ghost in the data
  • Home
  • About
  • Posts
  • Topics
  • Resources
  • Tags
  • AI
  • AI Agents
  • AI Business Applications
  • AI Communication
  • AI Concepts
  • AI Productivity
  • AI Prompting
  • AI Workflows
  • Ai-Tools
  • Airflow
  • Analytics
  • AnalyticsEngineering
  • Anonymization
  • Apache Airflow
  • Apache Iceberg
  • Athena
  • Automation
  • AVRO
  • AWS
  • BankingData
  • Bedrock Edition
  • BigData
  • Blue-Green Deployment
  • Budgeting
  • Business Case
  • Business Value
  • Business-Communication
  • Career Advice
  • Career Development
  • Career Growth
  • Chapter Lead
  • ChatGPT
  • CI/CD
  • Claude
  • Claude-Code
  • Cloud Computing
  • Cloud Gaming
  • Code Review
  • Communication
  • ConceptualDataModeling
  • Continuous Learning
  • ContinuousIntegration
  • CSV
  • Culture
  • Data Architecture
  • Data Culture
  • Data Engineering
  • Data Ethics
  • Data Governance
  • Data Impact
  • Data Ingestion
  • Data Leadership
  • Data Modeling
  • Data Modelling
  • Data Pipeline
  • Data Pipelines
  • Data Quality
  • Data Reliability
  • Data Solutions
  • Data System Resilience
  • Data Testing
  • Data Transformation
  • Data Validation
  • Data Vault
  • Data Warehouse
  • Data Warehouse Architecture
  • Database Design
  • DataDemocratization
  • DataEngineering
  • Datafold
  • DataGovernance
  • DataMinimization
  • DataModeling
  • DataPipelines
  • DataPrivacy
  • DataQuality
  • DataTools
  • DataValidation
  • DataWarehouse
  • Dbt
  • Decision Making
  • Delta-Lake
  • Development
  • Development Tools
  • DevOps
  • DimensionalModeling
  • Emergency Fund
  • Emotional Intelligence
  • EmpatheticDesign
  • Employee Engagement
  • Employee Productivity
  • Engineering Career
  • ETL
  • ETL Pipeline
  • Family Gaming
  • Feedback
  • File Formats
  • Financial Independence
  • Frameworks
  • GCP
  • GDPR
  • Git
  • GitBash
  • GitHub
  • GitHub Actions
  • Hiring Strategies
  • Incident Response
  • Industry Trends
  • Inspirational Quote
  • Intergroup Conflict
  • Interviews
  • Job Security
  • Journal
  • Journaling Techniques
  • JSON
  • Kimball
  • Lambda
  • Language Models
  • Leadership
  • LLM
  • LLM Interaction
  • MacOS
  • Management
  • Mental Health
  • Mentorship
  • Mindfulness Practices
  • Minecraft
  • Moral Development
  • Onboarding
  • One-on-One Meetings
  • OpenSource
  • ORC
  • Organizational Culture
  • Parquet
  • Performance Optimization
  • Personal Growth
  • Pipeline
  • PostegreSQL
  • Presentation-Skills
  • Problem Solving
  • Production Issues
  • Professional Development
  • Professional Growth
  • Professional-Skills
  • Promotion
  • Psychological Safety
  • Public-Speaking
  • Python
  • RAG
  • Recruitment
  • Redundancy
  • Remote Work
  • RequirementGathering
  • RetentionPolicies
  • Risk Management
  • Robbers Cave Experiment
  • ROI
  • Roleplaying
  • S3
  • Schema Evolution
  • Self-Awareness
  • Self-Reflection
  • Server Setup
  • ServiceDesign
  • ShadowIT
  • SQL
  • SQL Standards
  • Sql-Agents
  • Sql-Validation
  • SSH
  • SSH Keys
  • Staff Engineer
  • Stakeholder Engagement
  • Stakeholder Management
  • StakeholderManagement
  • Star Schema
  • Starburst
  • Strategy
  • Strengths
  • Success Habits
  • Talent Acquisition
  • Team Building
  • Team Collaboration
  • Team Enablement
  • Team-Management
  • Technical Assessment
  • Technical Leadership
  • Testing
  • Tools and Access
  • Trino
  • Trust Building
  • UserExperience
  • UV
  • UV Package Manager
  • Value Creation
  • Vector Databases
  • Virtual Environments
  • Visualization
  • Vocal-Techniques
  • Vscode
  • WAP Pattern
  • Windows
  • Workplace Communication
  • Workplace Relationships
  • Workplace Stress
  • Write-Audit-Publish
  • Zsh
Hero Image
Setting Up Your Data Engineering Environment on Windows

Introduction Setting up a development environment for data engineering on Windows requires some specific considerations that differ from Unix-based systems. This guide will walk you through creating a robust Python development environment on Windows, with detailed explanations of each component and why it’s important. Clean Slate: Removing Existing Python Installations Before starting, it’s important to remove any existing Python installations to avoid conflicts: Open Windows Settings > Apps > Apps & Features Search for “Python” Uninstall any Python versions listed Also check and remove Python from these locations:

  • Python
  • DBT
  • Windows
  • UV Package Manager
  • VSCode
Monday, February 3, 2025 Read
Hero Image
Setting Up Your Data Engineering Environment on MacOS

Introduction Setting up a development environment for data engineering on MacOS requires careful consideration of package management, Python version control, and tool configuration. This guide will walk you through the process, explaining not just how to set up these tools, but why each component is important. Clean Slate: Removing Existing Python Installations Before we begin, it’s important to ensure we’re starting with a clean slate. Multiple Python installations can cause confusion and conflicts. Let’s remove any existing Python installations:

  • Python
  • DBT
  • MacOS
  • UV Package Manager
  • VSCode
Sunday, February 2, 2025 Read