technology glossary

Technology Glossary 2019

Technology is the collection of techniques, skills, methods, and processes used in the production of goods or services or in the accomplishment of objectives, such as scientific investigation. we will discuss trendy technology glossary in 2019.

Autonomous Things
abbreviated AuT, or the Internet of autonomous things, abbreviated as IoAT, is an emerging term for the technological developments that are expected to bring computers into the physical environment as autonomous entities without human direction, freely moving and interacting with humans and other objects.

Augmented Analytics
an approach that automates insights using machine learning and natural-language generation, marks the next wave of disruption in the data and analytics market. Data and analytics leaders should plan to adopt augmented analytics as platform capabilities mature.

AI-Driven Development
is a software engineering approach that uses a model to create a product. Model-driven development is sometimes used interchangeably with model-driven engineering and may refer to specific tools and resources, or a model-driven approach.

Application performance monitoring
 track the performance of applications in relation to end users’ experiences and to internal metrics that may be leading indicators of future performance issues. The goal of these tools is to automate tracking and improve the reliability of application performance.

is a growing list of records, called blocks, which are linked using cryptography. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data. By design, a blockchain is resistant to modification of the data.

Blended data center 
As institutions move services to the cloud, they usually move into a blended environment where they continue to maintain an on-premises data center while also managing a set of services that may run the gamut from software as a service to infrastructure as a service. While cloud-based solutions offer advantages related to agility, performance, and scalability, the blended environment requires a shift in strategy to one that encompasses both environments.

Career planning systems
These technologies allow students to engage in career planning, including previewing job-market data, salary data, and the financial impact of choosing a degree that prepares them for that career.

Course demand forecasting
These technologies use student program data to forecast course demand. It can be used for course scheduling and course forecasting. These solutions allow institutions to ensure they are offering the curriculum needed in the right sequence to support student success and completion.

Cloud monitoring platform 
 is challenging to support because it can result in a mix of distributed and centralized systems and tools, some under IT’s control and some not. Cloud monitoring platforms allow institutions to track the expanding set of cloud resources.

Cloud-based HPC
requires substantial processing, high-speed connections, and parallel input/output. When HPC is provided by cloud vendors, additional characteristics typical of a cloud are inherited the ability to scale up and down quickly on demand in a pay-as-you-go environment.

Digital Twins
Edge computing exploitation of microservices architectures where chunks of application functionality can be sent to each device.

 Digital Ethics and Privacy
is the study of how to manage oneself ethically, professionally and in a clinically sound manner via online and digital mediums. Every psychologist who uses the Internet or a cell phone which amounts to nearly all of us must look at issues.

Data center capacity planning 
allows IT to meet the institution’s evolving needs for data center resources such as storage, power load, and cooling capacity. Some vendors provide tools for capacity planning. IT service management frameworks such as ITIL describe subprocesses for capacity management that include business capacity management, service capacity management, and component capacity management.

Development tools to support multiple key platforms
Developers must program applications to run on a variety of mobile devices that use different operating systems. Design strategies include responsive web design, which provides an optimal experience across a wide range of devices. Development tools exist that aid cross-platform development.

Empowered Edge
to give someone more control over their life or more power to do something. Edge Computing and Cloud Computing Are Complementary Concepts. Exploiting Advanced Capabilities at the Edge. Communicating with the Edge.

Ethernet fabrics
 are  data center network protocol that enables connections between multiple physical and virtual devices as part of an integrated network system. The goal is to increase flexibility and bandwidth and provide a scalable, low-latency networking approach.

Flexible interactive platforms 
allow a wide range of users to perform interactive analysis of institutional data, reflecting a shift away from IT-centric analytics solutions to ones that do not require advanced technical or data-science skills.

High-precision location-sensing technologies
These technologies enable applications to use precise indoor location, allowing systems to know an individual’s location to within a few meters. This precise sensing, combined with the Internet of Things and mobile apps, will make possible more-personalized services and information.

Immersive Experience
is an illusory environment that completely surrounds you such that you feel that you are inside it and part of it. The term is associated with technology environments that command the senses such as virtual reality and mixed reality.

Institutional support for public-cloud storage 
provide easy access, sharing, and backup of files and data. Institutions are moving to such options to provide cloud storage and collaboration services that work with the university’s identity management system, integrate with other services, and provide contractual assurances of privacy, security, and uptime.

Integration platform as a service
is made up of a complex mix of applications and architectures, some in the cloud and some on-premises, that need to communicate with each other and share data appropriately. Instead of handling data integration in-house, some institutions are turning to integration platform as a service (iPaaS), which is a suite of generally cloud-based services that support and enable integration among disparate systems.

is designed to address several problems of IPv4, the most pressing of which is the exhaustion of IPv4 addresses. In addition to providing more addresses, IPv6 allows for greater efficiency of IT systems, streamlined systems administration, and security improvements.

IT accessibility assessment tools
 allow institutions to test the designs of their web pages and other online materials to ensure they are usable by individuals with disabilities.

IT asset management tools 
provide an account of the significant components of the IT environment, including dependencies and life cycles. As IT assets expand beyond central IT, both on campus and in the cloud, asset management becomes more complex. IT asset management tools can help institutions better understand, plan for, and make decisions about the resulting technology mix.

Institutional repositories for research data
including providing continued access to this data is an important role for many institutions. In addition, publisher or grant-agency guidelines may require data to be in a repository. Institutional repositories help enable local, ongoing management and access, as well as serve as a place to host and share data where appropriate discipline-specific or national repositories are not available.

Life-cycle contract management
refers to a formal process or system for managing contracts from the time of negotiation through compliance to renewal. Life-cycle contract management systems have the potential to create efficiencies and lead to cost savings. They also can increase compliance with regulations and other requirements.

Massively scalable database architectures and software
allow for the distributed processing of very large data sets by dividing the work across computer clusters. This technology allows for high performance and highly scalable data management that can handle massive data.

Mobile apps for institutional BI/analytics
allow users to access institutional BI and analytics resources and technologies via handheld devices.

Next-generation Wi-Fi 
the increasing need for connectivity related to the Internet of Things (IoT). IoT devices might need more than enterprise Wi-Fi and could require additional hardware, security, and management applications. Next-generation Wi-Fi such as 802.11ah operates at a low frequency, offers longer range, requires less power, and allows many more devices to connect to a base station.

Mobile app development
is the organizational capability for the development of mobile applications. Organizations must make decisions about native apps for specific devices and mobile web development strategies. Issues of accessibility, security, data protection, and responsive web design also must be addressed when considering mobile app development.

Mobile apps for enterprise applications and analytics
refers to web-based applications that run on mobile devices and are designed to integrate with all aspects of an organization’s businesses and processes. These apps make it possible to access enterprise-wide resources and conduct enterprise transactions from mobile devices.

Mobile device management
is the approach an institution takes for the policies, support, and procedures related to the variety of cell phones, tablets, and laptops on campus. Mobile device management involves a balance between the security of institutional data and user convenience and productivity. Some institutions use third-party products and services to manage mobile devices. Considerations include data-security issues, support for personally owned equipment, and application management.

Predictive analytics for institutional performance
is the application of analytics for improving institutional services and business practices. It uses modeling to determine what will happen based on historical and transactional data.

Predictive analytics for student success (institutional level)
is the statistical analysis of massive amounts of data to create models that establish risk factors relating to student persistence, retention, and completion. These models enable proactive institutional support of student success.

Predictive learning analytics (course level)
is the practice of gathering and analyzing a variety of learner data that results in predictions about the likelihood of future student outcomes in the course. These predictions can be used by students and instructors.

Private-cloud computing
refers to cloud infrastructure operating for a single institution and closed to other users. Some institutions have used virtualization technologies to run parts of their environments on private-cloud virtualized platforms.

Quantum Computing
 is computing using quantum-mechanical phenomena, such as superposition and entanglement. A quantum computer is a device that performs quantum computing. Such a computer is different from binary digital electronic computers based on transistors.

Smart Spaces
The concept of smart environments evolves from the definition of ubiquitous computing that, according to Mark Weiser, promotes the ideas of “a physical world that is richly and invisibly interwoven with sensors, actuators, displays, and computational elements, embedded seamlessly in the everyday objects of our lives.

Service-level reporting tools
allow institutions to track and report on IT service delivery and management. They facilitate tasks and workflows associated with delivering IT services and track how well the delivery of services conforms to service-level commitments.

Software-defined networks
are an approach to designing, building, and operating networks that allow system administrators and network engineers to respond quickly to ever-changing network requirements and to optimize resources. SDNs may do for networks what virtualization has done for servers, allowing administrators to manage the network services in a simpler way and enabling network end users and applications to configure the network according to their needs.

Science DMZ
provides a network-architecture approach that is optimized for high-performance scientific applications and the transfer of large research data sets over high-speed wide-area networks. It supports big-data movement by improving security, cost-effectiveness, and the nimble handling of large scientific data sets. it also addresses issues of system performance monitoring and file transfer and serves to simplify the use of software-defined networking (SDN) over wide-area network paths.

Talent/workforce analytics 
uses data from HR or other employee information sources to optimize workforce efforts and promote staff engagement. A mature workforce analytics practice links planning and decisions about staffing to institutional goals.

Text/content analytics
 is a set of techniques and processes that analyze unstructured, text-based information to discern themes and patterns that can be used as data for analysis and decision-making.

Tools to support cross-institutional and international collaborations
Collaborating with colleagues beyond the institution is getting easier through a variety of options that include enterprise-level collaboration tools and free web-based tools. Enterprise tools offer more assurance of privacy and security through the institution’s identity management system.

Uses of the Internet of Things for campus management
refers to the networking of small, often everyday objects equipped with both computing and sensing capabilities, as well as the capacity to send and receive data via the Internet. the IoT is being used in areas such as facilities management, where remote monitoring of conditions can allow more efficiency in HVAC and lighting. 

Uses of APIs
An API defines how a system interacts with other systems and how data can be shared and manipulated across programs. A good set of APIs is like building blocks that allow developers to more easily use data and technologies from various programs. APIs are used in many ways in higher education—for example, to pull data from the student information system into the learning management system, to integrate cloud-based with on-premises services, as an approach to security, and to access web-based resources.

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