5V’s of Big Data
Characteristics of big data defined as Volume, Velocity, Variety, Veracity, and Value. Important for understanding the complexities and potential of big data in driving business insights and innovation.
224 topics found for:
“data management”
Data Architect
A professional responsible for designing and managing data structures, storage solutions, and data flows within an organization. Important for ensuring efficient data management and supporting data-driven decision-making in digital product design.
Big Data Engineer
A professional who designs, builds, and maintains systems for processing large-scale data sets. Essential for enabling data-driven decision-making and supporting advanced analytics in organizations.
Ethical Data Use
The practice of collecting, processing, and using data in ways that respect privacy, consent, and the well-being of individuals. Essential for building trust and ensuring compliance with legal and ethical standards.
Data Distribution
The spread and pattern of data values in a dataset, often visualized through graphs or statistical measures. Critical for understanding the characteristics of data and informing appropriate analysis techniques in digital product development.
Repository
A central location where data is stored and managed. Important for ensuring data consistency, accessibility, and integrity in digital products.
Metadata
Data that provides information about other data, such as its content, format, and structure. Essential for organizing, managing, and retrieving digital assets and information efficiently in product design and development.
Analytics
The systematic computational analysis of data or statistics to understand and improve business performance. Essential for data-driven decision making in design, product management, and marketing.
Knowledge Graphs
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.
Relationship Intelligence
The use of data and insights to understand and manage relationships with customers and prospects. Crucial for enhancing customer engagement and building stronger relationships.
Standard Deviation
A statistical measure that quantifies the amount of variation or dispersion of a set of data values. Essential for understanding data spread and variability, which helps in making informed decisions in product design and analysis.
Cookie Permissions
User consent settings for allowing or denying the storage of cookies on their device. Important for complying with privacy regulations and providing users control over their data.
State Persistence
The ability of a system to maintain its state and data across sessions, ensuring continuity and consistency in user experience. Crucial for designing reliable and user-friendly systems that retain data and settings across interactions.
Normal Data Distribution
A symmetrical, bell-shaped distribution of data where most observations cluster around the mean. Fundamental in statistics and crucial for many analytical techniques used in digital product design and data-driven decision making.
Stakeholder Management
The systematic identification, analysis, planning, and implementation of actions designed to engage and influence stakeholders in a project. Crucial for maintaining positive relationships and ensuring stakeholder support throughout the project lifecycle.
GIGO
Garbage In-Garbage Out (GIGO) is a principle stating that the quality of output is determined by the quality of the input, especially in computing and data processing. Crucial for ensuring accurate and reliable data inputs in design and decision-making processes.
Ontology
A structured framework for organizing information, defining the relationships between concepts within a specific domain to enable better understanding, sharing, and reuse of knowledge. Important for creating clear and consistent data models, improving communication, and enhancing the efficiency of information retrieval and management.
c14n
Numeronym for the word "Canonicalization" (C + 14 letters + N), converting data to a standard, normalized form to ensure consistency and eliminate ambiguities, often used in URLs to avoid duplicate content issues in SEO. Important for ensuring consistency and reducing redundancy.
Moneyball
The practice of using data analytics and metrics to make informed decisions, focusing on measurable outcomes and efficiency rather than intuition or traditional methods. Important for optimizing design processes, improving product performance, and making data-driven decisions that enhance user experience and business success.
Ontology vs. Taxonomy
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.
EPM
Enterprise Project Management (EPM) is a comprehensive approach to managing projects across an entire organization. Essential for coordinating complex, cross-functional projects and achieving organizational objectives.
ERD
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.
TQM
Total Quality Management (TQM) is a comprehensive management approach focused on continuous improvement in all aspects of an organization. Essential for ensuring high-quality products and services and achieving customer satisfaction.
OCM
Organizational Change Management (OCM) is the process of managing the people side of change to achieve desired business outcomes. Essential for ensuring successful implementation of changes within an organization.
Demand Forecasting
The process of predicting future customer demand using historical data and other information. Crucial for optimizing inventory levels, production schedules, and supply chain management.
Scatter Plot
A type of data visualization that uses dots to represent values for two different numeric variables, plotted along two axes. Essential for identifying relationships, patterns, and outliers in datasets used in digital product design and analysis.
BI
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.
Sunsetting
The process of phasing out or retiring a product or feature that is no longer viable or needed. Important for managing the lifecycle of digital products and ensuring resources are allocated to more valuable initiatives.
Dublin Core
A set of metadata standards used to describe digital resources, facilitating their discovery and management. Important for ensuring effective organization and retrieval of digital assets in product design and development.
3-Tiered Architecture
3-Tiered Architecture is a software design pattern that separates an application into three layers: presentation, logic, and data. Crucial for improving scalability, maintainability, and flexibility in software development.
Server-Side
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.
Business Logic
The part of an application that encodes the real-world business rules that determine how data is created, stored, and modified. Crucial for ensuring that digital products align with business processes and deliver value to users.
Privacy Zuckering
A dark pattern where the user is tricked into publicly sharing more information about themselves than they intended. Designers must avoid this deceptive practice and ensure clear, consensual data sharing to respect user privacy.
Data Science
An interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Essential for driving data-informed decision making, predicting trends, and uncovering valuable insights in digital product design and development.
Growth Product Manager
A role focused on driving user acquisition, engagement, and retention through data-driven strategies and experiments. Essential for scaling products and optimizing user growth.
Lead Management
The process of tracking and managing potential customers from initial contact through to sale. Important for ensuring that leads are properly engaged and converted.
Portfolio Management
Portfolio Management is the process of overseeing and coordinating an organization's collection of products to achieve strategic objectives. Crucial for balancing resources, maximizing ROI, and aligning products with business goals.
Risk Management
The process of identifying, assessing, and mitigating potential threats that could impact the success of a digital product, including usability issues, technical failures, and user data security. Essential for maintaining product reliability, user satisfaction, and data protection, while minimizing the impact of potential design and development challenges.
Technical Product Manager
A role that involves overseeing the development and improvement of technical products, ensuring they meet user needs and business goals. Crucial for bridging the gap between technical teams and business objectives, ensuring successful product development.
Digital Product Manager
A role focused on overseeing the development, launch, and lifecycle of digital products, ensuring they meet market needs and business goals. Essential for integrating digital product strategy and development.
PMP
Project Management Professional (PMP) is a globally recognized certification for project managers, awarded by the Project Management Institute (PMI). Essential for validating project management expertise and enhancing career prospects.
Gantt Chart
A type of bar chart that represents a project schedule, showing the start and finish dates of elements within the project. Important for planning and visualizing project timelines and dependencies.
Forecasting
The process of making predictions about future trends based on current and historical data. Useful for anticipating user needs and market trends to inform design decisions.
Clustering Illusion
A cognitive bias where people see patterns in random data. Important for designers to improve data interpretation and avoid false conclusions based on perceived random patterns.
DAM
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.
PMO
A Project Management Office (PMO) is a centralized unit within an organization that oversees and standardizes project management practices. Essential for ensuring consistency, efficiency, and alignment with strategic goals across projects.
Unfreeze-Change-Refreeze
A model of organizational change management that involves preparing for change (unfreeze), implementing change (change), and solidifying the new state (refreeze). Important for successfully implementing and sustaining changes in product design processes and organizational practices.
Instrumentation
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.
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.
KOS
Knowledge Organization System (KOS) refers to a structured framework for organizing, managing, and retrieving information within a specific domain or across multiple domains. Essential for improving information findability, enhancing semantic interoperability, and supporting effective knowledge management in digital environments.
ERP
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.
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.
McNamara Fallacy
The error of making decisions based solely on quantitative observations and ignoring all other factors. Important for ensuring a holistic approach to decision-making.
CRM
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.
Digital Phenotyping
The use of data from digital devices to measure and understand individual behavior and health patterns. Crucial for developing personalized user experiences and health interventions.
Development Cycle
The sequence of phases through which a product or project passes from conception to completion. Essential for managing and tracking the progress of development projects.
SOW
Statement of Work (SOW) is a formal document that outlines the scope, objectives, deliverables, and timelines for a project. Essential for defining project expectations and ensuring all parties have a clear understanding of their responsibilities.
Prioritization Matrix
A decision-making tool that helps prioritize tasks or projects based on specific criteria, such as impact and effort. Essential for effective project management and resource allocation.
Sales Metrics
Data points that represent an individual's, team's, or company's performance in the sales process. Essential for tracking progress, identifying issues, and optimizing sales strategies.
Planning Fallacy
A cognitive bias where individuals underestimate the time, costs, and risks of future actions while overestimating the benefits. Important for realistic project planning and setting achievable goals for designers.