🗃️Posts

The following section contains a list of the posts grouped by topic. Just click on the link to jump to the post.

General

Azure Synapse & Microsoft Fabrics


Business Intelligence

  • Notes

  • Perspectives
    • Part 1: General Issues
    • Part 2: The Complexity Myth
    • Part 3: Self Service BI
    • Part 4: How Big is Your Report?
    • Part 5: Data Soup - From BI to Analytics
    • Part 6: Data Soup - Reports vs Data Visualization
    • Part 7: Insights - Aha Moments!
    • Part 8: Insights - The Complexity Perspective
    • Part 9: Dashboards are Dead & Other Crap
    • Part 10: The Top 5 Pains of a BI/Analytics Manager
    • Part 11: Ways of Thinking about Data
    • Part 12: From Data to Data Models
    • Part 13-15: From Data to Storytelling (Part III, III
    • Part 16: On the Cusps of Complexity
    • Part 17: Creating Value for Organizations
    • Part 18: There’s More to Noise
    • Part 19: Data Visualization between Art, Pragmatism and Kitsch
    • Part 20: From BI to AI
    • Part 21: Data Visualization Revised
    • Part 22: Queries' Complexity
    • Part 23: In between the Many Destinations
    • Part 24: Building Castles in the Air
    • Part 25: Grounding the Roots
    • Part 26: Monitoring - A Cockpit View
    • Part 27: A Tale of Two Cities II
    • Part 28: Cutting through Complexity
    • Part 29: Navigating into the Unknown
    • Part 30: The Artificial Intelligence Connection
    • Part 31: More on Data Visualization
    • Part 32: Data Storytelling in Visualizations
  • Power BI
  • Software Engineering
  • Reports
    • Strategy
    • Python
    • R Language
    • SSRS (& Paginated Reports)
    • Test Drives
    • Data Management

      Data Migrations

      Data Warehousing

      Database Management Systems (DBMS)

      ERP Systems

      Metablogging

      MS Office

      Process Management

      Project Management

      Software Engineering

      • Application Design
      • Business Intelligence 
      • Copilot Unabridged

        (Answers to Copilot Prompts, so feel free to experiment with them as well!) 🤖〽️
        • Part 1: The Importance of AI in Society: A Transformational Force I
        • Part 2: The Importance of AI in Society: A Transformational Force II
        • Part 3: Why AI in Society Doesn’t Matter (Or Does It?)
        • Part 4: Why Society Doesn't Matter for AI
        • Part 5: Why There Are Limits to AI Growth
        • Part 6: Why There Are No Limits to AI Growth
        • Part 7: The Risks Associated with AI - Challenges in a Rapidly Advancing World
        • Part 8: Critical Points in the Development of AI - Milestones and Challenges
        • Part 9: The Perils of AI - Risks and Challenges in a Rapidly Evolving Technology
        • Part 10: When Will AI Become a Danger for Society?
        • Part 11: How the Danger of AI on Society Can Be Alleviated
        • Part 12: How Humanity Can Respond When AI Becomes a Danger to Society
        • Part 13: What Humanity Can't Do When AI Becomes a Danger to Society
        • Part 14: How Fast Humanity Could Face Extinction Due to AI Intervention
        • Part 15: What AI Can Use Its Intelligence to Damage Society
        • Part 16: How AI Can Use Its Intelligence to Help Society
        • Part 17: Can AI Become Self-Conscious? Exploring the Possibilities
        • Part 18: How Fast Can AI Surpass Human Intelligence?
        • Part 19: How Much AI Influences the Recruitment Process
        • Part 20: The Negative Influence of AI on the Recruitment Process
        • Part 21: Can AI Be Fooled? Understanding Its Vulnerabilities
        • Part 22: How AI Can Fight Against Other AI - The Battle of Algorithms
        • Part 23: How AI Can Be Tamed - Ensuring Responsible Development and Use
        • Part 24: The Next Steps in the Development of AI
        • Part 25: How AI Can Outsmart Us - The Rise of Machine Intelligence
        • Part 26: How Humans Can Outsmart AI - The Power of Human Ingenuity
        • Part 27: The Negative Impact of AI on the Economy
        • Part 28: The Gray Areas of AI: Navigating Ethical and Practical Uncertainty
        • Part 29: The Duality of AI - Innovation and Ethical Challenges
        • Part 30: The Multiplicity of AI - Expanding Perspectives in Artificial Intelligence
        • Part 31: The Potential of AI to Reach Singularity
        • Part 32: Can AI Be Stopped from Reaching Singularity?
        • Part 33: The Conflict of Interests Among Superintelligent AIs
        • Part 34: How the Average Citizen Can Use AI in Everyday Life
        • Part 35: How AI Impacts the Average Citizen
        • Part 36: How AI Can Reduce Unemployment
        • Part 37: How AI Can Increase Unemployment
        • Part 38: The Growing Backlog of AI Policies - How Much Needs to Be Done?
        • Part 39: How Fast Does Humanity Move in Enforcing Policies to Cope with AI’s Rapid Growth?
        • Part 40: How Disruptive Is AI as a Technology?
        • Part 41: How AI Can Play Devil’s Advocate - Challenging Assumptions and Expanding
        • Part 42: How AI Can Help in Understanding Complex Systems
        • Part 43: How Can I Use AI for Blogging? 
        • Part 44: How Can I Misuse AI for Blogging? 
        • Part 45: How Fast a Conflict with AI can escaladate
        • Part 46: Understanding AI Governance - Balancing Innovation and Responsibility
        • Part 47: The Future of AI - How Artificial Intelligence Could Evolve in the Next Decade
        • Part 48: AI - Society’s Illusion of Progress
        • Part 49: The End of AI - Will We Ever Stop Using Artificial Intelligence?
        • Part 50: The Obsolescence Effect - How AI May Render Technologies and Jobs Redundant
        • Part 51: Will AI Make Programmers Obsolete?
        • Part 52: Will AI Make Project Managers Obsolete?
        • Part 53: Will AI Make Software Engineering Obsolete?
        • Part 54: The Future of Business Intelligence - Will AI Make It Obsolete?
        • Part 55: Will AI Make Data Analysis Obsolete?
        • Part 56: AI and the Search for Immortality - A Digital Quest for Eternal Life
        • Part 57: AI and the Search for Spirituality - A New Frontier
        • Part 58: AI and the Search for Consciousness - Can Machines Truly Think?
        • Part 59: The Exploitable Weaknesses of AI - Risks and Challenges
        • Part 60: The Foolishness of AI: Weaknesses That Can Be Exploited
        • Part 61: The Competitive Gap: AI-Adopting vs. AI-Resistant Organizations
        • Part 62: When AI Goes Terribly Wrong: Risks and Consequences
        • Part 63: Is AI Making Humanity Dumber? The Risks of Over-Reliance
        • Part 64: How AI Can Make Humanity Smarter
        • Part 65: AI: A Reflection of Humanity 
        • Part 66: The Rise of AI: A New Era of Power Transition 
        • Part 67: The Reality of AI: A World Beyond Human Perception 
        • Part 68: AI: A Reflection of Intelligence, Not a Replica 
        • Part 69: AI and the Illusion of Knowledge: Learning Without Understanding 
        • Part 70: AI and the Illusion of Consciousness: Can Machines Truly Think?
      • Documentation
      • Knowledge Management
      • Mea Culpa 
      • Programming
        • Part I: Learning SQL
        • Part II: To get or not Certified?!
        • Part III: Football and Software Development
        • Part IV: Believe and Not Doubt?!
        • Part V: Is MS Access or Excel the Answer to your Problems?
        • Part VI: What is Programming About?
        • Part VII: Documentation - Lessons Learned
        • Part VIII: Pair Programming
        • Part IX: Programmer, Coder or Developer?
        • Part X: Programming as Art
        • Part XI: The Dark Side of Programming
        • Part XII: Misconceptions about Programming I
        • Part XIII: Misconceptions about Programming II
        • Part XIV: Good Programmer, Bad Programmer
        • Part XV: Rapid Prototyping - Introduction
        • Part XVI: The Software Quality Perspective and AI
        • Part XVII: More on AI

      Strategic Management

      Systems Engineering


          

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      Koeln, NRW, Germany
      IT Professional with more than 25 years experience in IT in the area of full life-cycle of Web/Desktop/Database Applications Development, Software Engineering, Consultancy, Data Management, Data Quality, Data Migrations, Reporting, ERP implementations & support, Team/Project/IT Management, etc.