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In todays increasingly digital world, data has become one of the most valuable assets for organizations. With the rise in cyberattacks, data breaches, and the stringent regulatory environment, it is imperative to adopt robust data…
Facing the new market challenges, service providers are looking for solutions to improve three major business areas namely the Customer Experience, The Operational Efficiency and Revenue and Margin. To meet the business requiements related…
Adopting DevOps practices is nowadays a recurring task in the industry. DevOps is a set of practices intended to reduce the friction between the software development (Dev) and the IT operations (Ops), resulting in higher quality software…
Information and communication technologies are permeating all aspects of industrial and manufacturing systems, expediting the generation of large volumes of industrial data. This article surveys the recent literature on data management as…
For companies developing web-based applications, the Dev and the Ops refer to different groups with either operational or development focus. Therefore, DevOps help these companies streamline software development and operations activities by…
Large organizations today are being served by different types of data processing and informations systems, ranging from the operational (OLTP) systems, data warehouse systems, to data mining and business intelligence applications. It is…
Development and Operations (DevOps), a particular type of Continuous Software Engineering, has become a popular Software System Engineering paradigm. Software architecture is critical in succeeding with DevOps. However, there is little…
Machine learning and AI have been recently embraced by many companies. Machine Learning Operations, (MLOps), refers to the use of continuous software engineering processes, such as DevOps, in the deployment of machine learning models to…
DevOps is an emerging practice to be followed in Software Development life cycle. The name DevOps indicates that its an integration of Development and Operations team. It is followed to integrate the various stages of the development…
The systems that operate the infrastructure of cities have evolved in a fragmented fashion across several generations of technology, causing city utilities and services to operate sub-optimally and limiting the creation of new value-added…
With the advent of Internet of Things (IoT) and Web 2.0 technologies, there has been a tremendous growth in the amount of data generated. This chapter emphasizes on the need for big data, technological advancements, tools and techniques…
Data has become a critical asset in the digital economy, yet it remains underutilized by Mobile Network Operators (MNOs), unlike Over-the-Top (OTT) players that lead global market valuations. To move beyond the commoditization of…
Operation technology networks, i.e. hard- and software used for monitoring and controlling physical/industrial processes, have been considered immune to cyber attacks for a long time. A recent increase of attacks in these networks proves…
Performing diagnostics in IT systems is an increasingly complicated task, and it is not doable in satisfactory time by even the most skillful operators. Systems and their architecture change very rapidly in response to business and user…
Introduction of DevOps into the software development life cycle represents a cultural shift in the IT culture, amalgamating development and operations to improve delivery speed in a rapid and maintainable manner. At the same time, security…
Data democratization is an ongoing process that broadens access to data and facilitates employees to find, access, self-analyze, and share data without additional support. This data access management process enables organizations to make…
The vision of the Internet of Things is to allow currently unconnected physical objects to be connected to the internet. There will be an extremely large number of internet connected devices that will be much more than the number of human…
In recent past, big data opportunities have gained much momentum to enhance knowledge management in organizations. However, big data due to its various properties like high volume, variety, and velocity can no longer be effectively stored…
As data continues to grow in scale and complexity, preparing, transforming, and analyzing it remains labor-intensive, repetitive, and difficult to scale. Since data contains knowledge and AI learns knowledge from it, the alignment between…
DevOps is a trend towards a tighter integration between development (Dev) and operations (Ops) teams. The need for such an integration is driven by the requirement to continuously adapt enterprise applications (EAs) to changes in the…