Product Adoption Rate
The speed at which users start using a new product, typically measured as a percentage of the target market over a specific period. Essential for evaluating the success of a product launch and planning subsequent strategies.
The speed at which users start using a new product, typically measured as a percentage of the target market over a specific period. Essential for evaluating the success of a product launch and planning subsequent strategies.
A comprehensive analysis of a website to assess its performance in search engine rankings and identify areas for improvement. Essential for diagnosing and enhancing a website's SEO performance.
A Japanese word meaning excessive strain on people or processes. Crucial for preventing burnout and maintaining sustainable work practices.
A research approach that starts with a theory or hypothesis and uses data to test it, often moving from general to specific. Essential for validating theories and making informed decisions based on data.
A network of real-world entities and their interrelations, organized in a graph structure, used to improve data integration and retrieval. Crucial for enhancing data connectivity and providing deeper insights.
Software Development Life Cycle (SDLC) is a process for planning, creating, testing, and deploying an information system. Essential for managing the complexities of software development and ensuring project success.
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.
Case-Based Reasoning (CBR) is an AI method that solves new problems based on the solutions of similar past problems. This approach is essential for developing intelligent systems that learn from past experiences to improve problem-solving capabilities.
A strategic planning tool that outlines the future direction of a project or product using Kanban principles, emphasizing continuous delivery and improvement. Important for aligning team efforts and maintaining focus on long-term goals.
A simple sorting algorithm that repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order. Important for understanding basic algorithmic principles and their applications.
Ontology is a comprehensive model that includes entities, their attributes, and the complex relationships between them, while taxonomy is a hierarchical classification system that organizes entities into parent-child relationships. Essential for understanding the depth and scope of data organization, helping to choose the appropriate structure for information management and retrieval.
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.
A list of tasks and deliverables that a team commits to completing during a sprint, providing a clear focus and scope for the sprint's duration. Essential for organizing and prioritizing work within an Agile sprint.
The use of biological data (e.g., fingerprints, facial recognition) for user authentication and interaction with digital systems. Crucial for enhancing security and user experience through advanced authentication methods.
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 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.
An ongoing effort to improve products, services, or processes over time through incremental and breakthrough improvements. Crucial for fostering a culture of constant enhancement and adaptation.
A non-production environment used for development and testing before deployment to production. Important for ensuring that changes are thoroughly tested before going live.