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.
19 topics found for:
“data volume”
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.
Outliers
Data points that differ significantly from other observations and may indicate variability in a measurement, experimental errors, or novelty. Crucial for identifying anomalies and ensuring the accuracy and reliability of data in digital product design.
Repository
A central location where data is stored and managed. Important for ensuring data consistency, accessibility, and integrity in digital products.
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.
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.
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.
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.
Bucket Sort
A sorting algorithm that distributes elements into a number of buckets, sorts each bucket individually, and then combines the buckets to get the sorted list. Useful for understanding more advanced algorithmic techniques and their applications.
Multiple Classification
A method of categorizing information in more than one way to enhance findability and user experience. Crucial for improving navigation, search, and overall usability of complex information systems.
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.
Sentiment Analysis
The use of natural language processing to identify and extract subjective information from text, determining the sentiment expressed. Crucial for understanding public opinion and customer feedback.
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.
Anecdotal Fallacy
A logical fallacy where anecdotal evidence is used to make a broad generalization. Crucial for improving critical thinking and avoiding misleading conclusions.
Taxonomy
The practice and science of classification, often used to organize content and information. Essential for improving findability and usability in information systems.
LLM
Large Language Model (LLM) is an advanced artificial intelligence system trained on vast amounts of text data to understand and generate human-like text. Essential for natural language processing tasks, content generation, and enhancing human-computer interactions across various applications in product design and development.
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.
Cross-Selling
The practice of selling additional products or services to an existing customer. Essential for increasing revenue and enhancing customer value.
Scalability
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.