## 5 Discussion
The wide spectrum of skills required for big data jobs is an important finding frequently mentioned in previous studies [4, 5, 8, 10]. Compared to earlier studies such as [4, 5], our findings confirm a broader spectrum of competencies, especially highlighting the simultaneous importance of technical and interpersonal skills in the current big data labor market. The emergence of soft skills--most notably \"communication skills\" and \"team working\"--among the top competencies across multiple roles reflects a shift towards more human-centric expectations in technically demanding roles, consistent with the evolving nature of data-driven team work and organizational adaptability [3, 6, 10]. Our findings clearly demonstrate that the vast majority of big data professions require employees at all levels to possess a collective set of technical, developer, analytical, and soft skills in order to drive decision-making processes that combine technical and analytical understandings with intuition and vision [10, 16, 17, 36]. This alignment suggests that the big data profession is increasingly interdisciplinary, requiring a fusion of analytical thinking, programming expertise, and interpersonal competencies, rather than purely technical proficiency. Our results reinforce the argument that in environments characterized by complex data infrastructures and agile development teams, soft skills play a decisive role in enabling collaboration, problem-solving, and cross-functional communication. It has been revealed by our study that valuable insights and predictions for businesses are provided by combining machine learning and business analytics approaches with big data skills [15, 37, 38, 39]. Our study also showed that big data is a multidisciplinary field comprised of various disciplines, as stated in previous studies [4, 8, 17]. The aforementioned studies argued that a variety of skills are required to analyze, interpret, and maintain big data in order to make effective business decisions, emphasizing that the discipline of big data is complex and multifaceted [4, 8, 17]. According to our topic modeling analysis, the top five skills emerged as \"big data processing\", \"big data tools\", \"communication skills\", \"remote development\", and \"big data architecture\". The topic of \"communication skills\" is another significant finding of our analysis. There are many studies supporting this finding [4, 6, 8, 17, 40]. As shown in Table 4, \"communication skills\" is the only skill required for all roles and is among the top ten skills. With a rate of 5.02%, it also ranks third among big data skills. This result demonstrates the significance of communication-focused abilities. Despite the increasing demand for new technological skills, many studies have clearly emphasized the necessity of communication and social skills for big data professions [4, 6, 8, 10, 17, 20, 26, 41]. \"Team working\" is another soft skill that should be emphasized. Employers expect a coordinated and collaborative team work style from employees with various qualifications. This is because big data is a work environment that requires different skill sets from experts in different roles (see Table 3). Another remarkable finding from our analysis is the topic \"bachelor degree\". As seen in Table 4, \"bachelor degree\" is only included in the tenth skill of the \"analyst\" role and remains passive compared to other skills. So, this skill was not in the top ten skills of the other six roles. As a result, it is seen that professional experience and competencies are more dominant than undergraduate degrees in the competencies required for big data professions. Among big data knowledge and skills, the number and high rates of competencies based on cloud services such as \"Amazon EMR\", \"Google Cloud\", \"AWS Data Services\",and \"Azure Cloud\" have revealed the close relationship between big data and cloud services (see Figure 2). Likewise, the fact that many tools and technologies used in big data processes are cloud-based confirms this finding.