Qualitative and quantitative techniques and processes used to enhance productivity and business gain. (Source 3)
Models, policies, rules or standards that govern which data is collected and how it is stored, arranged, integrated and put to use in data systems and in organizations. (Source 3)
Data Integrity is the overall completeness, accuracy, and consistency of data. (Source 7)
Data Life-cycle Management
Data Life-cycle Management (DLM) is a policy-based approach to managing the flow of an information system's data throughout its life cycle: from creation and initial storage to the time when it becomes obsolete and is deleted. (Source 5)
Data Modelling refers to methods used in computer science for the formal representation of data objects and their relationships within a data set.
Data Monetization aims at generating measurable economic benefits from both raw data and mined resources. Data can be monetized in mainly two ways: either directly by selling or sharing data (explicit monetization), or indirectly by enhancing own data-based products known (implicit monetization).
Data Policy is a set of broad, high-level principles, which form the guiding framework in which Data Management can operate. (Source 8)
Data Science refers to the collective processes, theories, concepts, tools, and technologies that enable the review, analysis and extraction of valuable knowledge and information from raw data. (Source 7)
Data Stewardship is concerned with taking care of data assets that do not belong to the stewards themselves. Data Stewards represent the concerns of others. (Source 9)
Data Thinking is a framework to explore, design, develop and validate data-driven solutions and businesses with a user-, data- and future-oriented focus. Data Thinking combines data science with design thinking and therefore, the focus of this approach does not lie only on data-analytics technologies and data collection but also on the design of use-centered solutions with high business potential. The term was created by Mario Faria and Rogerio Panigassi in 2013 when they were writing a book about data science, data analytics, data management and how data practitioners were able to achieve their goals. (Source 10)
Machine learning method that uses layers of connected nodes to interpret complex patterns and acquire skills, and can learn from mistakes. (Source 3)
Design thinking is a process for creative problem solving.
DevOps (a clipped compound of "software DEVelopment" and "information technology OPerationS") is a term used to refer to a set of practices that emphasize the collaboration and communication of both software developers and information technology (IT) professionals while automating the process of software delivery and infrastructure changes. It aims at establishing a culture and environment where building, testing, and releasing software can happen rapidly, frequently, and more reliably.
(IG1137) DevOps is a combination of practices that embody a culture of end-to-end ownership and shared responsibility across teams from Development, Quality Assurance (QA), Security, Operations, and other areas as a single cohesive, service focused team. A key element in DevOps is the use of smaller releases and continuous delivery practices with continuous feedback loops to ensure quality as team velocity increases.
The best way to talk about DevOps in general is under the following categories:
• Culture and Attitude
• Processes and Practices
• Technology and Tools.
Digital Asset Management (DAM)
Systems to manage visual assets (photo and video) that are used to market and sell products. Also called product information management (PIM). (Source 3)
Digital Business Models
A digital business model is a form of creating value based on the development of customer benefits using digital technologies. The aim of the digital solution is to generate a significant advantage for which customers are willing to pay. (Source 10)
Distributed, adaptive, open socio-technical system with properties of self-organization, scalability and sustainability inspired by natural ecosystems. (Source 3)
Use of digital technology to enable or improve business models and processes.
Digital learning is the use of digital tools to enhance educational strategies (such as blended learning, flipped learning, personalized learning etc.).
Software that uses signs and screens in retail stores to showcase videos, digital ads, traditional store signage and messages for customers. (Source 3)
The analysis and guidance required to focus the enterprise on Digital opportunities and threats that will have the greatest impact on business success.
Digital technique is a well-formed approach or practice that uses digital technologies to deliver a solution. E.g., App-based payment, Digital Ticketing.
The process of exploiting the latest digital technologies and practices to create a robust new digital business model.
Software-based system for making e-commerce transactions. (Source 3)
Conversion of analog or physical information to digital format.