Numeronym for the word "Observability" (O + 11 letters + N), the ability to observe the internal states of a system based on its external outputs, facilitating troubleshooting and performance optimization. Crucial for monitoring and understanding system performance and behavior.
The ability of a system, product, or process to handle increased loads or expand without compromising performance or efficiency. Essential for ensuring that products and systems can grow and adapt to increasing demands.
The mental and physical effort required to complete a task, influencing user experience and performance. Crucial for designing systems that minimize cognitive and physical load, enhancing usability and efficiency.
A performance testing method that evaluates the system's behavior and stability over an extended period under a high load. Essential for identifying memory leaks and ensuring the reliability and performance of digital products under prolonged use.
Site Reliability Engineering (SRE) is a discipline that incorporates aspects of software engineering and applies them to infrastructure and operations problems to create scalable and highly reliable software systems. Crucial for maintaining the reliability and efficiency of complex software systems.
The process of determining which tasks should be performed by humans and which by machines in a system. Essential for optimizing system efficiency and usability.
Redundant, outdated, or unnecessary code or design elements that accumulate over time in a system. Important for identifying and removing to maintain clean, efficient, and maintainable systems and interfaces.
The process of designing, developing, and managing tools and techniques for measuring performance and collecting data. Essential for monitoring and improving system performance and user experience.
A detailed description of a system's behavior as it responds to a request from one of its stakeholders, often used to capture functional requirements. Essential for understanding and documenting how users will interact with a system to achieve their goals.
Software that acts as an intermediary between different systems or applications, enabling them to communicate and function together. Crucial for integrating various components and ensuring seamless interaction within digital products.
The study of how humans interact with systems and products, focusing on improving usability and performance. Crucial for designing user-friendly systems and products.
The practice of designing applications specifically for a particular operating system or platform, leveraging its unique features and capabilities. Important for delivering high-performance and responsive user experiences.
A principle stating that productivity increases when the computer and its user interact at a pace that ensures neither has to wait on the other. Important for designing responsive systems that enhance user productivity.
Balanced Scorecard (BSC) is a strategic planning and management system used to align business activities to the vision and strategy of the organization. Essential for aligning business activities with organizational strategy and improving performance.
A testing methodology that verifies the complete workflow of an application from start to finish, ensuring all components work together as expected. Important for ensuring the reliability and performance of digital products, leading to better user satisfaction and fewer post-launch issues.
The process of running a system for an extended period to detect early failures and ensure reliability. Important for ensuring the stability and performance of digital products before full-scale deployment.
Content or functionality that is built into a platform or device rather than being provided by an external application. Important for ensuring seamless integration and optimal performance.
A statistical technique that uses random sampling and statistical modeling to estimate mathematical functions and simulate systems. Useful for risk assessment, decision-making, and performance optimization in digital product design.
The process of maintaining, updating, and improving a product or system after its initial deployment to ensure its continued functionality, performance, and relevance to users. Crucial for ensuring long-term user satisfaction, product reliability, and adaptation to changing user needs and technological advancements.
Key Performance Indicators (KPIs) are quantifiable measures used to evaluate the success of an organization, employee, or project in meeting objectives for performance. Essential for tracking progress, making informed decisions, and aligning efforts with strategic goals across various business functions, including product design and development.
The degree to which a system's components may be separated and recombined, often used in the context of software or hardware design. Important for enhancing flexibility, reusability, and ease of maintenance in design.
Enterprise Resource Planning (ERP) are integrated software systems that manage business processes across various departments, such as finance, HR, and supply chain. Essential for improving operational efficiency and providing a unified view of business operations.
The process of integrating knowledge into computer systems to solve complex problems, often used in AI development. Important for developing intelligent systems that can perform complex tasks and support decision-making in digital products.
A type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
A cognitive bias where people underestimate the complexity and challenges involved in scaling systems, processes, or businesses. Important for understanding the difficulties of scaling and designing systems that address these challenges.
The process of self-examination and adaptation in AI systems, where models evaluate and improve their own outputs or behaviors based on feedback. Crucial for enhancing the performance and reliability of AI-driven design solutions by fostering continuous learning and improvement.
The setting where software and systems are actually put into operation for their intended use. Essential for ensuring that products are fully functional and meet user requirements in a real-world setting.
Customer Relationship Management (CRM) is a strategy for managing an organization's relationships and interactions with current and potential customers. Essential for improving business relationships and driving sales growth.
Numeronym for the term "10,000 Concurrent Clients", the challenge of optimizing network software to handle ten thousand simultaneous client connections. Important for ensuring scalability and performance in high-demand scenarios.
The process by which a measure or metric comes to replace the underlying objective it is intended to represent, leading to distorted decision-making. Important for ensuring that metrics accurately reflect true objectives and designing systems that prevent metric manipulation.
A model by Don Norman outlining the cognitive steps users take when interacting with a system: goal formation, planning, specifying, performing, perceiving, interpreting, and comparing. Important for designing user-friendly and effective products by understanding and supporting user behavior at each stage.
Application Support Engineer (ASE) is a professional responsible for maintaining and supporting software applications, ensuring their availability and performance. Crucial for ensuring the reliability and user satisfaction of digital products through effective support and maintenance.
The drive to perform an activity due to external rewards or pressures rather than for the inherent enjoyment of the activity itself. Important for designing systems that effectively use external incentives to motivate user behavior.
A system that allows customers to access information and perform tasks on their own without the need for assistance from customer service representatives. Important for improving customer experience and reducing support costs.
A method of splitting a dataset into two subsets: one for training a model and another for testing its performance. Fundamental for developing and evaluating machine learning models in digital product design.
A metric that shows the revenue that a company can expect to receive annually from its customers for subscriptions or services. Essential for understanding business performance and growth potential.
An environment closer to production where final testing and validation occur. Crucial for ensuring that products are ready for production deployment.
The process of designing and refining prompts to elicit accurate and relevant responses from AI models. Crucial for optimizing the performance of AI applications.
The hardware and software environment used to deploy and manage applications and services. Essential for ensuring reliable and scalable application deployment.
A statistical method used to assess the generalizability of a model to unseen data, involving partitioning a dataset into subsets for training and validation. Essential for evaluating model performance and preventing overfitting in digital product analytics.
The tendency for individuals to put in less effort when working in a group compared to when working alone, due to reduced accountability. Crucial for understanding group dynamics and designing systems that ensure individual accountability.
The high-level structure of a software application, defining its components and their interactions. Essential for designing robust, scalable, and maintainable digital products.
A cognitive bias where individuals underestimate their own abilities and performance relative to others, believing they are worse than average. Important for understanding self-perception biases among designers and designing systems that support accurate self-assessment.
The phenomenon where external incentives diminish intrinsic motivation, leading to reduced performance or engagement. Important for designing motivational strategies that do not undermine intrinsic motivation.
Integrated Business Planning (IBP) is a process that aligns strategic, operational, and financial planning to optimize business performance. It ensures cohesive and efficient planning across all functions.
Representational State Transfer (REST) is an architectural style for designing networked applications based on stateless, client-server communication. Essential for building scalable and efficient web services.
A technique used to evaluate a product or system by testing it with real users to identify any usability issues and gather qualitative and quantitative data on their interactions. Crucial for identifying and resolving usability issues to improve user satisfaction and performance.
Operations and processes that occur on a server rather than on the user's computer. Important for handling data processing, storage, and complex computations efficiently.
Entity Relationship Diagram (ERD) is a visual representation of the relationships between entities in a database. Essential for designing and understanding the data structure and relationships within digital products.
Business Intelligence (BI) encompasses technologies, applications, and practices for the collection, integration, analysis, and presentation of business information. Crucial for making data-driven decisions and improving business performance.
A structured set of breakpoints used to create responsive designs that work seamlessly across multiple devices. Important for maintaining consistency and usability in responsive design.
Digital Asset Management (DAM) is a system that stores, organizes, and manages digital assets, such as images, videos, and documents. Essential for maintaining and leveraging digital content efficiently in product design and marketing.
A practice of performing testing activities in the production environment to monitor and validate the behavior and performance of software in real-world conditions. Crucial for ensuring the stability, reliability, and user satisfaction of digital products in a live environment.
Software Requirements Specification (SRS) is a detailed document that outlines the functional and non-functional requirements of a software system. Crucial for ensuring clear communication and understanding between stakeholders and the development team.
ModelOps (Model Operations) is a set of practices for deploying, monitoring, and maintaining machine learning models in production environments. Crucial for ensuring the reliability, scalability, and performance of AI systems throughout their lifecycle, bridging the gap between model development and operational implementation.
The process of training an AI model on a large dataset before fine-tuning it for a specific task. Crucial for building robust AI models that perform well on various tasks.
A systematic evaluation of behaviors within an organization or process to identify areas for improvement and ensure alignment with goals. Crucial for understanding and improving user behaviors and organizational processes.
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that uses human input to guide the training of AI models. Essential for improving the alignment and performance of AI systems in real-world applications.
A set of algorithms, modeled loosely after the human brain, designed to recognize patterns and perform complex tasks. Essential for developing advanced AI applications in various fields.
Simple Object Access Protoco (SOAPl) is a protocol for exchanging structured information in web services. Crucial for enabling communication between applications over a network.