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Data Analytics

Qualitative and quantitative techniques and processes used to enhance productivity and business gain. (Source 3)

Data Architecture 

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 

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 

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 

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 

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 

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 

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

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)

Deep Learning 

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 

Design thinking is a process for creative problem solving.

DevOps

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)

Digital Ecosystem 

Distributed, adaptive, open socio-technical system with properties of self-organization, scalability and sustainability inspired by natural ecosystems. (Source 3)

Digitalization 

Use of digital technology to enable or improve business models and processes.

Digital learning

Digital learning is the use of digital tools to enhance educational strategies (such as blended learning, flipped learning, personalized learning etc.). 

Digital Signage

Software that uses signs and screens in retail stores to showcase videos, digital ads, traditional store signage and messages for customers. (Source 3)​​​​​​​

Digital Strategy

The analysis and guidance required to focus the enterprise on Digital opportunities and threats that will have the greatest impact on business success.

Digital techniques 

Digital technique is a well-formed approach or practice that uses digital technologies to deliver a solution. E.g., App-based payment, Digital Ticketing. 

Digital Transformation 

The process of exploiting the latest digital technologies and practices to create a robust new digital business model.

Digital Wallet 

Software-based system for making e-commerce transactions. (Source 3)

Digitization 

Conversion of analog or physical information to digital format.

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