EHR Data Quality: Why You Should Worry and What You Can Do About It
Explore EHR data quality concerns and strategies for improvement. Learn to assess, validate, and enhance electronic health record data for more reliable research and clinical applications.
Ensuring Quality and Avoiding Inaccuracies in Data Insights
Learn techniques for validating business rules, ensuring data quality, and building automated testing into data solutions like Power BI reports, Synapse Pipelines, and Spark notebooks.
Implementing a Data Quality Framework for Databricks, Synapse, and Power BI Solutions
Implement a framework for data quality validation and monitoring across your end-to-end data platform, including Power BI, Databricks, and Synapse Analytics.
Before It's Too Late: Finding Real-Time Holes in Data
Discover techniques for identifying and addressing real-time data gaps, enhancing data integrity and decision-making in dynamic environments.
Dominating the DBIR Data
Explore data analysis techniques for cybersecurity incidents, covering data collection, processing, and validation. Learn to generate meaningful statistics and uncover novel findings in security datasets.
Real-Life Network and Security Automation
Explore network and security automation strategies, from latency monitoring to firewall deployment, with insights on custom scripts, proactive maintenance, and reducing deployment time.
OWASP Standard Classification - API Security Top 10 - A Beginner's Guide to Mitigation
Learn to mitigate API security risks using OWASP's Top 10 classification. Explore vulnerabilities, solutions, and strategies for implementing robust API security throughout the entire lifecycle.
Internet Plumbing for Security Professionals - The State of BGP Security
Explore BGP security, its vulnerabilities, and practical countermeasures to build trust in the Internet's foundation. Learn about routing leaks, hijacking risks, and implementation strategies for a more secure network infrastructure.
Never Again Without a Contract - Dry-Validation
Explore dry-validation in Ruby for robust input validation, clear contracts, and efficient error handling, enhancing system reliability and code quality.
Building RESTful APIs with Symfony Components
Explore building robust RESTful APIs using Symfony components, covering data representation, validation, authentication, and testing strategies with practical insights and real-world examples.
Reduce System Complexity with Data-Oriented Programming
Explore Data-Oriented Programming principles to reduce system complexity, focusing on immutable data, generic structures, and flexible validation techniques for more maintainable software systems.
Knowledge is Imperfect - Acting on Stale, Inconsistent or Missing Data
Explore strategies for handling imperfect data in decision support, disaster response, and connected devices. Learn to address challenges in distributed systems and improve data quality.
#FAIL • Kevlin Henney • GOTO 2022
Explore software failures, their consequences, and valuable lessons learned. Gain insights into preventing critical errors, validating data, and understanding common pitfalls in programming and system design.
#FAIL • Kevlin Henney • GOTO 2021
Exploring programming failures, bugs, and lessons learned over a decade, with insights on testing, data validation, and avoiding common pitfalls in software development.
OWASP Mobile Top Ten - Why They Matter and What We Can Do
Explore OWASP Mobile Top Ten vulnerabilities, their significance, and strategies for mitigation. Learn about transport layer protection, threat modeling, and best practices for mobile app security.
Spring Kafka Beyond the Basics - Lessons Learned on Our Kafka Journey at ING Bank
Explore advanced Spring Kafka concepts, real-world scenarios, and best practices for production-ready applications. Learn to handle exceptions, implement testing strategies, and monitor performance effectively.
The Security Toolbox for Node
Explore top Node.js security threats and learn practical tools to protect against vulnerabilities in dependencies, data, and servers. Gain a comprehensive security toolkit for robust application defense.
Hands-On Regular Expressions in Python
Learn to create, understand, and effectively use regular expressions in Python for data validation, parsing, and normalization. Discover when and how to apply regex for optimal results.
Statistical Typing - A Runtime Typing System for Data Science and Machine Learning
Statistical typing: A runtime typing system for data science and ML, extending primitive types to statistical data types. Enables multivariate schemas, generative data contracts, and easier data testing with pandera.
Large Scale Data Validation - with Spark and Dask
Explore data validation techniques for large-scale datasets using Spark and Dask. Learn to transition from single-machine to distributed computing, combining frameworks for efficient validation across partitions.
How Pydantic V2 Leverages Rust's Superpowers
Explore how Pydantic V2 utilizes Rust to enhance performance, extensibility, and maintainability in data validation. Learn about architecture changes and real-world trade-offs in combining Python and Rust.