Research on Intelligent Task Management and Control Mode of Space Information Networks Based on Big-Data Driven

The research question of this paper is concerned with the investigation of the links between Internet of Things and related big data as input parameters for stochastic estimates in business planning and corporate evaluation analytics. Financial forecasts and company appraisals represent a core corporate ownership and control issue, impacting on stakeholder remuneration, information asymmetries, and other aspects. Optimal business planning and related corporate evaluations derive from an equilibrated mix of top-down and bottom-up approaches. While the former follows a traditional dirigistic methodology where companies set up their strategic goals, the latter are grass-rooted with big data-driven timely evidence. Real options can be embedded in big data-driven forecasting to make expected cash flows more flexible and resilient, improving Value for Money of the investment and reducing its risk profile. More accurate and timely big data-driven predictions reduce uncertainties and information asymmetries, making risk management easier and decreasing the cost of capital. Whereas stochastic modeling is traditionally used for budgeting and business planning, this probabilistic process is seldom nurtured by big data that can refresh forecasts in real time, improving their predictive ability. Combination of big data and stochastic estimates for corporate appraisal and governance issues represents a methodological innovation that goes beyond the traditional literature and practice.

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Data Analysis Services Related to the IoT and Big Data

Web Services ◽

10.4018/978-1-5225-7501-6.ch048 ◽

2019 ◽

pp. 882-903

Author(s):

Izabella V. Lokshina ◽

Barbara J. Durkin ◽

Cees J.M. Lanting

Keyword(s):

Big Data ◽

Data Analysis ◽

Business Models ◽

Third Party ◽

Data Driven ◽

Easy Access ◽

Provision Of Services ◽

And Control ◽

Measurement And Control ◽

The Internet Of Things

The Internet of Things (IoT) provides the tools for the development of a major, global data-driven ecosystem. When accessible to people and businesses, this information can make every area of life, including business, more data-driven. In this ecosystem, with its emphasis on Big Data, there has been a focus on building business models for the provision of services, the so-called Internet of Services (IoS). These models assume the existence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated by any party. Different business models may support opportunities that generate revenue and value for various types of customers. This paper contributes to the literature by considering business models and opportunities for third-party data analysis services and discusses access to information generated by third parties in relation to Big Data techniques and potential business opportunities.

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Data Analysis Services Related to the IoT and Big Data

International Journal of Interdisciplinary Telecommunications and Networking ◽

10.4018/ijitn.2017040104 ◽

2017 ◽

Vol 9 (2) ◽

pp. 37-56 ◽

Cited By ~ 8

Author(s):

Izabella V. Lokshina ◽

Barbara J. Durkin ◽

Cees J.M. Lanting

Keyword(s):

Big Data ◽

Data Analysis ◽

Business Models ◽

Third Party ◽

Data Driven ◽

Easy Access ◽

Provision Of Services ◽

And Control ◽

Measurement And Control ◽

The Internet Of Things

The Internet of Things (IoT) provides the tools for the development of a major, global data-driven ecosystem. When accessible to people and businesses, this information can make every area of life, including business, more data-driven. In this ecosystem, with its emphasis on Big Data, there has been a focus on building business models for the provision of services, the so-called Internet of Services (IoS). These models assume the existence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated by any party. Different business models may support opportunities that generate revenue and value for various types of customers. This paper contributes to the literature by considering business models and opportunities for third-party data analysis services and discusses access to information generated by third parties in relation to Big Data techniques and potential business opportunities.

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Are They Ready for the Big Thing?

Advances in Library and Information Science - Handbook of Research on Information and Records Management in the Fourth Industrial Revolution ◽

10.4018/978-1-7998-7740-0.ch013 ◽

2021 ◽

pp. 200-210

Author(s):

Matthias Lederer ◽

Juluis Lederer

Keyword(s):

Big Data ◽

Data Management ◽

Process Management ◽

Business Processes ◽

Future Trend ◽

Data Driven ◽

Big Data Applications ◽

All Solutions ◽

Management Approaches ◽

And Control

Data-driven business processes management (BPM) is regarded as a central future trend because automation often makes huge amounts of data (big data) available for the optimisation and control of workflows. Software manufacturers also use this trend and call their solutions big data applications, even if some features are reminiscent of traditional data management approaches. This chapter derives from the basic definitions of big data including 13 central requirements that a big data BPM solution must meet in order to be described as such. One hundred twenty-one process management solutions are evaluated on the basis of these to determine whether they are real big data applications. As a result, less than 5% of all solutions analysed meet all requirements.

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