SOSIALISASI DATA SPESIALIS PENGETAHUAN MEMAHAMI PROSPEK DAN PELUANG SEBAGAI DATA SPESIALIS DI ERA DIGITALISASI
Abstract
The socialization of specialist knowledge data is an important initiative in educating the public about the prospects and opportunities offered by the role of data specialists in the digital era. In the midst of the development of information and communication technology, data has become a valuable asset for organizations and individuals. In this context, data specialists are expected to be able to process, analyze and interpret data to help make more effective decisions. The digital era brings new challenges where the volume of data generated is getting bigger, complexity is increasing and the speed of data processing is becoming more critical. This socialization covers various aspects, from basic understanding of data, technical analysis, to the application of the latest technologies such as artificial intelligence (AI) and machine learning. By increasing awareness of the importance of data, it is hoped that the public can recognize career opportunities in this field, and understand how data can be used to solve social, economic and environmental problems. In addition, this socialization aims to encourage collaboration between professions to produce innovative solutions that can be utilized by various sectors. Through a structured socialization program, skills and knowledge in the field of data are expected to be widely disseminated, increasing the competitiveness of individuals and organizations in facing global challenges. Thus, the role of data specialists will become increasingly vital in shaping a better and more sustainable future in the digital era.
References
Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). "Digital Business Strategy: Toward a Next Generation of Insights". MIS Quarterly, 37(2), 471-482.
Chen, M., Mao, S., & Liu, Y. (2014). "Big Data: A New Frontier for Innovation and Research". IEEE Access, 2, 1-4.
Davenport, T. H., & Harris, J. G. (2007). Competing on Analytics: The New Science of Winning. Harvard Business Review Press.
Kitchin, R. (2014). The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. Sage.
McKinsey Global Institute. (2011). "Big Data: The Next Frontier for Innovation, Competition, and Productivity". McKinsey & Company.
Manyika, J., Chui, M., & Bughin, J. (2011). "Big Data: The Next Frontier for Innovation, Competition, and Productivity". McKinsey Global Institute.
Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Eamon Dolan/Houghton Mifflin Harcourt
O'Reilly, T. (2013). WTF?: What’s the Future and Why It's Up to Us. HarperBusiness
Provost, F., & Fawcett, T. (2013). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. O'Reilly Media.
Sharma, R., & Iyer, L. S. (2012). "Cloud Computing and Its Impact on Business". International Journal of Cloud Computing and Services Science, 1(1), 1-12.
Sharma, A., & Gupta, A. (2020). "Data Analytics in the Digital Age: Opportunities and Challenges". International Journal of Information Management, 50, 36-45.
Siegel, E. (2016). Data Science for Business: How to Use Data to Grow Your Business. Wiley.
Harris, J., & Davenport, T. (2005). "Competing on Analytics". Harvard Business Review, 83(4), 96-104.
Wang, Y., Kung, L. A., & Byrd, T. A. (2018). "Big Data in Health Care: A Systematic Literature Review". Health Services Research, 53(2), 1622-1637.
Zikopoulos, P., & Eaton, C. (2011). Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw-Hill.
