The Transformational Impacts of Data Science on Business and Society

Download Full-Text PDF Cite this Publication

Text Only Version

The Transformational Impacts of Data Science on Business and Society

Eng. Mohamed Khalif Ali

Dean Faculty of Engineering and Computer Technology Somali International University (SIU)

Master of Science in Information Technology (MScIT)

Abstract:- This research paper summarizes the immense impacts of data science by analyzing information system technology and its relations with business and society. Digitization advancements have enhanced the generation of data that is used to provide insights that are essential in transforming businesses and society. The society has benefitted through the creation of job opportunities amongst knowledge workers or the researchers who are tasked with the role of creating and analyzing crucial data while businesses are reshaping the way things are run. This work holds that data science has transformed the lives of people and provided businesses with the opportunity to analyze data and come up with an effective business strategy. Therefore, this paper aims at presenting a central research subject to explore and intellectualize evident transformations in society and business models as a result of the digitalized data science.

Keywords Data science, transformed, transformations, intellectualize, Digitization


The sector of Data Science is in a transformative stage based on ways in which the current data advancements are being utilized to address both business and societal predicaments for a strategic gain. The technological era designed a prodigious amount of data expected to intensify to 44 zettabytes soon (Bu & Wang, 2019). This implies that this significant amount of information has proven to be enormously crucial especially to the big business firms since they can now incorporate disparate data into important sources for algorithms; hence enhancing the understanding and manipulation of behaviors. On the other hand, data science, or what is commonly referred to as the extraction of knowledge and discernment from sets of data, is a sector characterized by the potential to have crucial impacts on human society. In that, in todays technological era, digitization exists in all dynamics of life and has developed new methods of how we do things, communications, and interactions (Avital, Dennis, Rossi, Sørensen, & French, 2019). Through the digital connections in the business and the society at large, it has created easier ways of social interactions, stress-free transactions, and collaborations hence the massive accessible data sources.

Data science is present in multiple types of data-intensive sectors such as genome study, network traffic monitor, and atmospheric research. Immense sizes of data are developed every day particularly through the connections of billions of users through the use of technological gadgets such as computers, mobile phones, medical devises, censors, and GPS devices among others (Bu & Wang, 2019). As a result of the incredible amount of information generated daily in areas such

as sciences, business, and research, big data is believed to be in all aspects of our lives. Therefore, the availability of data science in our society has presented various opportunities to the individuals who are capable of utilizing it meritoriously as opposed to the past when this data was not given too much consideration. Subsequently, due to the technological advancements era, this paper will focus on extending our knowledge on the transformative impacts of data science particularly in the context of business and society.

Digitalization entails the change of analog to digital data and progressions in a technical dimension. However, this viewpoint study will objectively outline the changes of the developed patterns under the lens of data science revolution and complementary modernizations in the society and business platforms. Notably, the inclusion of big data analytics is to evaluate and create more understanding of various forms of digital information since they ascertain the functional latitude of todays digital creation among other services (Avital et al., 2019). Data plays a critical role in understanding vital acumens concerning target demographics and customer predilections.

In every interaction with technology, without putting into consideration whether it is passive or active, new data is created which tends to describe an individual. This implies that, with every information obtained through commodities, cellphones, video cameras, other technological devices, the data or the profile of clientele and businesses continues to grow exponentially. Therefore, when this type of available information is analyzed effectively, these data insights can depict the behavior of a business and the personalities as well as the life events of the users (Avital et al., 2019). On the aspect of the business, large firms can take an advantage of these data points to promote or improve their products and services, marketing drives, and business strategy to meet the demands of the targeted consumers.


Data science is significantly characterized by a high degree of impacting human society for the better. This work aims at shedding more light on how data science has been utilized from the constantly growing collection of information to transform the world through its interaction business and society. The availability of data is largely based on the rapid technological advancements being experienced across the globe. The ever-increasing number of different physical gadgets that are designed with applications and location-based devices plays a critical role in connecting millions of people

(Weihs&Ickstadt, 2018). As a consequence of the network connection across the world, there is an enormous exchange and creation of data, which is constantly changing the way of life through the creation of several opportunities.

Data science has attained a momentous focus on information systems. This is attributed by the swiftly growing market and demand coming from an extensive range of participants who are significantly comprised of business companies, and consumers as well as government agencies (Murtagh, & Devlin, 2018). Many stakeholders are now viewing data science as the next biggest industrial revolution whereby intersected technological devices can program skills and tasks. With this viewpoint, data science has profoundly revolutionized commerce and society by augmenting transparency, minimizing overall production costs, and heightened production processes. Transformative effects highlighted in this work are arguable as a result of the hyper- connected economy.

The understanding of information management is frequently changing with routine advancements of technology, business needs, and ideas. On the other hand, data has a life cycle that is centered on its level of expediency to a company. Data needs to be interpreted so that crucial information is obtained which in the long run will be used as a source of knowledge and finally enhance effective decision making. The extensive availability of data science comes with some shreds of complexity to the aspect of managing information. On the same breath, it presents numerous opportunities to acquire actionable intuitions that could never be derived before.

Subsequently, current information management specialists have benefitted a lot from the new opportunities brought by the immense data availability. In that, they have taken advantage of the insights derived from the data to assist companies to make the right choices and develop more value for their clients and the organization. Without the expertise of practitioners wh transform the cutting-edge technological advancements into practical shape, Big Data could not have been a reality today. It is because of these professionals that more business firms are adapting the element of big data in their day-to-day operations by unlocking their powers. This is a clear indication that there is significant value in data generation and evaluation.


The high volume of data that is generated from different sources such as humans, networks, and software applications among others along with the complication of the study environment demands a pedagogical discovery in academic programs on the study approach. This paper derives information from an extensive research project evaluating the present-day studies that are conducted for academic purposes. The data was acquired through the use of an online inquiry or questionnaire on some of the transformative effects of data science that are being experienced. This was attributed to the notion that data science is significantly determined by the accessibility of information hence the need to use the data already available for public use. To take an experimental approach, this work adopted the technique of combining

different databases that significantly enhanced analytical accuracy.

The present study used a survey approach through the application of an online questionnaire, which had open and closed-ended inquiries. The research puts more effort into a descriptive and interpretative methodology to attain an extensive indulgence of current practices and the transforming nature of data science. Additionally, more focus was directed towards the process used in conducting the study, and recursively discuss how theoretical advancement can occur through a systematic process of knowledge analysis as well as information abstraction. However, due to the significant availability of data for research, collecting, and evaluating large datasets was identified to be not only time-consuming but it also required special skills so that the study can record quality research findings. Therefore, the selections of the cases used to study the transformations were particularly based on the diversity of how information and analytics are utilized in matters related to innovations results and activities.


Data Science has been identified as an integral emergent scientific sector and paradigm promoting study revolutions in different fields of learning such as computer science, statistics, science engineering, and intelligence science among others. This sector entails the extensive element of artificial intelligence, national language learning, big data manipulation, pattern recognition, data analytics, and machine knowledge. Subsequently, it also addresses related modern scientific problems for instance, data collection, storage, sharing, creation, optimization, retrieval, and visualization.

Scientific challenges experienced are solved through the integrative scrutiny across diverse and interdependent multifaceted resources for proper decision making, value establishment, and cooperation. According to Weihs and Ickstadt (2018), data science analytics creates a platform where researchers, leaders, potential users of data science, industry experts, and analytics come together to deliberate on the modern trends and opportunities. Additionally, they also brainstorm and exchange new ideas and services which play an integral role in enhancing transdisciplinary and cross- domain alliances.


The emergence of the new technology has promoted the rapid growth and development of the aspect of making systematic extrapolations from data. As a consequence, social and economic transactions are rapidly conducted using easily available online avenues. This in return promotes the digital capture of big data that derives essential insights from a pool of data sets on human behaviors (Murtagh& Devlin, 2018). The connection of the world through networking has enhanced scientific inquiries economy and researchers are now able to design and perform experiments as well as obtaining the information required to offer answers to multiple questions presented.

Therefore, due to the availability of data science techniques, people can make automated decisions, which can positively help to improve their lives. In that, the rapid

advancements in science and technology, different opportunities have been raised and are being utilized in society to pave a better path. As a result, people are using data science technology to rise out of poverty.

Data science has identified crucial priorities and investment opportunities in the society. The social impacts of data science can significantly help local leaders to discover new insights and trends from the available information. This is to say that they can establish more impactful programs to their communities provided they have the required talents knowledge, and tools, data science can have a transformative real human impact to the communities they serve.



Business benefits are now at a higher level due to the availability of data analytics in organizations. Data science and tool knowledge is having profound positive effects on business, and are swiftly becoming crucial for diversity and also survival means. The new information technology has fostered a new way of thinking or innovation through the use of data science. Data experts can frame intricate business challenges as tool learning or operations study glitches. Therefore, data scientists can drive better results by unveiling solutions that are now addressing the old problems that were previously not talked about for lack of remedy (Griol&Callejas, 2019). For instance, in the case of Moneyball where old methods of assessing performance in baseball were outdone by the utilization of data science. This was achieved by using data science to overcome financial disadvantage. In that, by applying analytics to ascertain high-performing players who were disregarded by other teams using the old evaluation methods. Therefore, the baseball team was able to acquire services of high performing players are relatively low cost and ended up winning games by beating the higher- spending opponents in their league.

The ever-expanding world of data has increasingly made the aspect of business decision making processes inadequate in the new technological era. Data science particularly machine learning have made greater strides in addressing the kind of highly complicated data with deep problems that have stunned even the shrewdest individuals. For instance, the police department in U.SA needed competent approaches to conduct actionable intuitions derived from the already available large volumes of crime data. Consequently, the predictive analytics solution implemented was able to provide insights into the likelihood of crimes being committed in different states. This helped the agency to deploy police forces before the crimes were committed and this played a crucial role in decreasing theft cases by 22% and the homicide rates by 36% for one year (Murtagh& Devlin, 2018).

Data science helps to challenge business players to adopt ideal practices and center their focus on issues that matter most. To achieve this, data scientists help businesses with the relevant knowledge of the companys analytics tools. They conduct illustrations of the operative use of the system to excerpt insights which will help the organization to attain success by performing better-driven actions (Griol&Callejas, 2019). Therefore, once the business is well-versed and

familiar with the data science product competences, their attention can now shift to solving primary business predicaments being encountered in the organization.


Data science plays a significant role in learning about valuable insights based on the targeted population and customer inclinations. The application and learning about dat science is an integral competitive strategy for leading corporations and developing societies. This paper has demonstrated the transformative effects of data science on both business and society by providing ways in which new hidden insights can be discovered from the pool of available data. Data science can add significance to any business, which in return can enhance the development of the society at large by addressing some of the challenges facing the community. Ranging from data and insights from different workflows and employing new taskforce as well as helping local leaders make informed decisions on the challenges encountered in the society, data science holds the key to success in both business and society.


  1. Avital, M., Dennis, A. R., Rossi, M., Sørensen, C., & French, A. (2019). The Transformative Effect of the Internet of Things on Business and Society. Communications of the Association for Information Systems,44, 129-140. doi:10.17705/1cais.04405

  2. Bu, L., & Wang, F. (2019). Data Science and Digital Business. Data Science and Digital Business, 23-40. doi: 10.1007/978-3-319-95651- 0_2

  3. Griol, D., & Callejas, Z. (2019). Data Science and Conversational Interfaces: A New Revolution in Digital Business. Data Science and Digital Business, 41-56. doi:10.1007/978-3-319- 95651-0_3

  4. Murtagh, F., & Devlin, K. (2018). The Development of Data Science: Implications for Education, Employment, Research, and the Data Revolution for Sustainable Development. Big Data and Cognitive Computing, 2(2), 14. doi: 10.3390/bdcc2020014

  5. Weihs, C., &Ickstadt, K. (2018). Data Science: The impact of statistics. International Journal of Data Science and Analytics,6(3), 189-194. doi:10.1007/s41060-018-0102-5.

Leave a Reply

Your email address will not be published. Required fields are marked *