Digital enterprise transformation focuses on alignment of processes, products, services, business models, and technologies to perceive business value. Digital business integration in an organization utilizes information technology and its tools to drive and manage the life cycle of digital enterprise transformation. It utilizes the practices and approaches of IT governance with modern application tools and APIs. The millennium brought many technological advancements over internet technologies and these technologies operate numerous applications and business services. The span of digital enterprises is expanding and continues to grow with their evolution on a web scale. This chapter is an effort to present understanding about machine learning and automation around businesses intelligence and analytics on a web scale. The chapter provides a brief summary of technologies used in digital enterprise transformation for all the domains of an organization.
TopIntroduction
Digital technologies have made our world a digital globe. Each individual interacts with technology and digital devices in some way or the other. With regard to digital enterprises of varied extent, their in-house and outward business operations are carried over automated platforms. Businesses excel and enhance their customer experiences by adopting innovative ways and delivering automated solutions through technology strengthened business practices. This also opens a window of opportunity to keep business management flexible and agile.
Distributed data processing has been applied so far in developing web-oriented digital platforms. With significant advancements and recent developments in deep learning methods, there is much to offer to digital enterprises. Artificial intelligence, machine learning and cloud computing provide personalized experiences to a varied customer base and tackle ongoing enterprise data, applications and services for a competitive edge. The implementation of machine learning solutions increments the customer value of enterprise and boosts the internal operating models. Machine learning is the most powerful tool to achieve automation and it could afford limitless applications and tools. The view proposed by Jasney (2020) explains that the operational efficiency of DBMS increases with machine learning in a digital enterprise transformation.
Echo from Amazon, Google Home, Siri from Apple are interactive apps and tools were only possible through machine learning technology. With NLP uniting the prominent features of these applications, it has made text and GUI old fashioned. Machine learning makes decisions faster. The work of Obukhova et al. (2020) explains that latest tools and models of computing with machine learning in digital enterprises leads to faster production and enhances scalability of the system. Businesses get help through machine learning in innovation and to elevate the right kind of services and products. Machine learning advocates minimum human error and stronger cyber security to transform digital enterprises. Key elements of a digital enterprise are -
- 1.
Product - The unique component of a business platform which is sold or which caters to the needs of customers and the range of outcomes which are offered by the enterprise.
- 2.
Services - Set of physical, hardware, software, goods or assets and custom-tailored solutions by the enterprise.
- 3.
Work process - Products and services along with the revenue generation and customer interaction dimensions comprises the work process of a digital enterprise.
- 4.
Business models - The technologies and tools, workflow process, life cycle and management of products and services are studied under business models.
Figure 1. Salient features in Digital Enterprise Management (Sucoso)
The Figure 1 illustrates features in Digital Enterprise Management. These are the major underlying components of an enterprise. Each feature is discussed below:
Governance:
It is the process of monitoring and managing an entire enterprise and all of its elements. It encompasses management of end user business and vendor technologies. Governance takes into consideration all the four elements, that is, product, services, work processes and business models. It is further classified in following categories: