23 topics found for:

“distributed teams”

LeSS

Large-Scale Scrum (LeSS) is a framework for scaling agile product development to multiple teams working on a single product. It provides a minimalist, large-scale agile approach that maintains the simplicity and effectiveness of Scrum while addressing the challenges of coordination and integration in multi-team environments.

Story Mapping

A visual exercise that helps product teams understand and prioritize features by organizing user stories into a cohesive narrative that aligns with user journeys and goals. Essential for planning and prioritizing product features and ensuring alignment with user needs.

T-Shirt Sizing

A relative estimation technique used in Agile project management to quickly assess the size and complexity of tasks by assigning them T-shirt sizes (e.g., small, medium, large). Crucial for efficient project planning and workload management.

OKR

Objectives and Key Results (OKR) is a goal-setting framework for defining and tracking objectives and their outcomes. Essential for aligning organizational goals, improving focus and engagement, and driving measurable results across teams and individuals.

SDLC

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.

JAD

Joint Application Development (JAD) is a collaborative approach to gathering requirements and designing solutions in software development projects. It facilitates rapid decision-making and consensus-building by bringing together key stakeholders, including users, developers, and project managers, in structured workshop sessions.

IDE

Integrated Development Environment (IDE) is a software suite that combines tools like code editors, debuggers, and compilers. Essential for improving developer productivity and ensuring efficient and error-free coding practices.

ModelOps

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.

MBSE

Model-Based Systems Engineering (MBSE) is a methodology that uses visual modeling to support system requirements, design, analysis, and validation activities throughout the development lifecycle. Essential for managing complex systems, improving communication among stakeholders, and enhancing the overall quality and efficiency of systems engineering processes.