Skip to main content
How Can We Help?Contact

Articles

One decision per article, argued all the way through.

Each article takes one decision leaders face with data and AI, says what usually goes wrong, and what to do instead.

The latest argumentRecentExecutive BytesEvery past article

Recent

Recently published

Executive Bytes

The weekly newsletter, written up in full

More than 1,400 readers subscribe to Executive Bytes on LinkedIn. Each edition gets a fuller write-up here, with the sources and next steps a newsletter has no room for, and the two link to each other.

Subscribe on LinkedIn All editions

Every past article

Newest first, back to October 2019

Choose a subject to see only those, or scroll back through the years.

2024

  1. AI Devs Combating Adversarial Machine LearningGovernance and security
  2. Data Products CEO, Dr. Mechie Nkengla, Appointed to Illinois Generative AI & NLP Task ForceEvents and news
  3. Deep Learning for Computer Vision: The Complete GuideMachine learning
  4. Data Mining: What You Need to Know and WhyMachine learning
  5. The AI Revolution: Adaptive RadarStrategy and the business case
  6. Leveraging Machine Learning for Cyber-Attack Prediction and PreventionGovernance and security
  7. Data Simplified Episode 8.24: Maximizing ROI with AI InvestmentsData Simplified
  8. Data Simplified: AI and Data Ethics for LeadersData Simplified
  9. Biometric Authentication: Advancements and Challenges in ImplementationGovernance and security
  10. Data Simplified Episode 6.24: Big Data Challenges and SolutionsData Simplified
  11. Driving Product Development Using AIStrategy and the business case
  12. Data Simplified Episode 5.24: Data Visualization and StorytellingData Simplified
  13. Exploring Generative AI in Content Creation: A Data Professional's HandbookGenerative AI
  14. Python: Streamlining Data Analysis with Pandas — Tips and TricksTips and tools
  15. Data Simplified Episode 4.24: Data Literacy Amongst Business LeadersData Simplified
  16. LLMs Decoded: Leveraging Large Language Models for Big Data SolutionsGenerative AI
  17. Generative AI in Healthcare: Engineering Innovative Solutions for Diagnosis and TreatmentGenerative AI
  18. Data Simplified Episode 3.24: AI-driven decision-makingData Simplified
  19. Data Infrastructure – Making the Case for Immutable Infrastructure in Your OrganizationData engineering and analytics
  20. Data Simplified 2.24: Developing a Data-driven CultureData Simplified
  21. Making an Impact as a Prompt EngineerGenerative AI
  22. Data Simplified 1.24: Foundations of AI Literacy for Business LeadersData Simplified
  23. GANs for Engineers: A Guide to Developing Unique Art Creation AlgorithmsGenerative AI
  24. AI 2024: Predicting the Next Big Trends in AI for Data and Engineering ProfessionalsStrategy and the business case

2021

  1. Data Simplified Interview with HabibaData Simplified
  2. Data Simplified Interview with John ThompsonData Simplified
  3. Data Simplified Interview with Dr. Calvin NoblesData Simplified
  4. Data Simplified Interview with Author Amy WilsonData Simplified
  5. Python: Building Data Driven Classes with DataclassTips and tools
  6. Data Infrastructure: What is Infrastructure as Code and why you should consider adopting it?Data engineering and analytics
  7. Docker: Four Useful Docker Commands that Could Boost Your WorkflowData engineering and analytics
  8. Data Infrastructure: Why You Should Consider Using Serverless Containers for Deploying Your Next Data PipelineData engineering and analytics
  9. Docker: How to Create Event-Driven Containers for Your Next Data Project and WhyData engineering and analytics
  10. Python: The Benefits of Passing Generators between Functions Instead of ListsTips and tools
  11. Python: Why You Should Start Using Logging Instead of Print()Tips and tools
  12. VSCode: The Benefits of Using .py file with Jupyter Kernel vs. Jupyter Notebook for Your Data ProjectTips and tools
  13. Jupyter Notebook: Use Jupyter Notebook within Virtual EnvironmentTips and tools
  14. Setting Up Data Science Development Environment on Apple M1/BigSurTips and tools
  15. Big Data: Three Different Ways to Handle Data That Can’t Fit into Memory (Part III)Data engineering and analytics
  16. Big Data: Three Different Ways to Handle Data That Can’t Fit into Memory (Part II)Data engineering and analytics
  17. Big Data: Three Different Ways to Handle Data That Can’t Fit into Memory (Part I)Data engineering and analytics
  18. Python: Three Hidden Ways to Create Potential Bugs with Mutable Data Structures (Part III)Tips and tools
  19. DataYap Virtual Conference HighlightsEvents and news
  20. Python: Three Hidden Ways to Create Potential Bugs with Mutable Data Structures (Part II)Tips and tools
  21. Python: Three Hidden Ways to Create Potential Bugs with Mutable Data Structures (Part I)Tips and tools
  22. Pandas: Detect Mixed Data Types and Fix itTips and tools
  23. Data Simplified – Interview with Troy HernandezData Simplified
  24. Python: When to Use Set vs. ListTips and tools
  25. Data Simplified: Interview with Mark SchwartzData Simplified
  26. Data Simplified: Interview with Professor David BaderData Simplified
  27. Data Simplified – Interview with Scott TaylorData Simplified
  28. Data Science Simplified: Interview with Sonja PetrovićData Simplified
  29. Data Science Simplified: Understanding DataData Simplified

2020

  1. Data Science Simplified: Interview with David WeeklyData Simplified
  2. Data Science Simplified: Interview with Katy PuschData Simplified
  3. Cal Poly Pomona Colloquium SeriesEvents and news
  4. Ep. 2: Big vs. Complex vs. Unstructured Data (Data Science Simplified)Data Simplified
  5. Ep. 1: AI vs. ML vs. DL (Data Science Simplified)Data Simplified
  6. ColumnsTips and tools
  7. Intro to linear regressionMachine learning
  8. The AEC Industry Has a Moral Obligation to Upgrade to Smart BuildingsStrategy and the business case
  9. Descriptive, prescriptive, or predictive?Machine learning
  10. Harness the Power of Data Science to Optimize Your Core Business ApplicationsStrategy and the business case
  11. Data SecurityGovernance and security
  12. DSUM of all thingsTips and tools
  13. Method or Function?Tips and tools
  14. Style with Conditional FormattingTips and tools
  15. How to add Table of ContentsTips and tools
  16. Investigating Unexpected Data SourcesTips and tools
  17. Outline Your CodeTips and tools
  18. How to Deal with Empty ValuesTips and tools
  19. Data FrameTips and tools
  20. Jupyter NotebookTips and tools
  21. Precision and RecallMachine learning
  22. PandasTips and tools
  23. Data Profiling for Business AnalyticsTips and tools
  24. Keep Track of Your Data LineageTips and tools
  25. Avoid These Time KillersTips and tools
  26. Develop a Rigid WorkflowTips and tools
  27. Keep an internal inventory of data sourcesTips and tools
  28. Think about Design FirstTips and tools
  29. Cleaning Data in ExcelTips and tools
  30. Cross-validationMachine learning
  31. Interactive debuggerTips and tools
  32. Using the .Plot() FunctionTips and tools
  33. A New Day Will Dawn: It’s Time to Update and OptimizeStrategy and the business case
  34. Introduction to Data Management for NonprofitsEvents and news
  35. 5 Easy Ways to Make the Most of Your Business DataTips and tools

Bring the decision you would like argued.

A question your leadership keeps returning to about data or AI. Tell us, and it may become the next article, or a 30-minute conversation about your own case.

Suggest a decision to argue

A decision you would like argued? Tell us the question; it may become the next article.