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  /  Cloud   /  How Does Cloud Computing Affect Data Science Work in the 21st Century?
Data science

How Does Cloud Computing Affect Data Science Work in the 21st Century?

Global Tech Outlook lays an emphasis on the effect of cloud computing on data science

Cloud computing and data science are two of the most essential disruptive technologies in the 21st century. Organizations across the world have realized the importance of cloud computing as well as data science for effective data management. Data scientists are leveraging both the cutting-edge technologies to boost productivity with utmost cybersecurity in different kinds of clouds such as public, private, multi, as well as hybrid. Cloud computing has started affecting data science works in the 21st century in multiple means.

Organizations were facing certain challenges in data analysis, data management, and data storage in this data-driven culture. The data explosion has created an unlimited supply of raw and enormous datasets including structured and unstructured data. The outbreak of the pandemic is one of the major reasons for data supply from different smart devices due to IoT and artificial intelligence. Data scientists need appropriate places for data storage to protect all confidential and sensitive data from the malicious eyes of cybercriminals. Here comes the emergence of cloud computing for providing utmost protection to these organizations. Digital transformation or digitalization has instigated organizations to shift work and processes to the digital mode.

The impact of cloud computing on data science has opened ample opportunities to professional data analysts, data scientists, and data engineers for effective data management to earn higher revenue in this cut-throat competitive market. Data scientists need to have a clear understanding of cloud computing to store enormous datasets in different kinds of clouds. Cloud computing in data science can provide platforms like Azure, AWS, Google Cloud storage, IBM cloud, and many more for clear access to multiple programming languages such as Python, R, Java, C++, etc. There are free frameworks and tools for data scientists for effective data management within a short period of time.

Data scientists need flexibility, scalability, agility and multiple processing systems for blending data science with cloud computing with robust security. Cloud computing is helping to raise the salaries of data scientists because digital transformation has reduced the cost of infrastructure.

There is an interdependent relationship between cloud computing and data science through Software-as-a-Service (SaaS). Data scientists can harness real-time data through cloud platforms and utilize it in different ways for the benefit of an organization. Meanwhile, cloud computing will have a few smart functionalities without the availability of large-scale data from devices across the world.

Effective data management and data analytics through cloud computing are helping companies steer the growth of revenue to the right direction in this 21st century. Cloud computing in data science helps to eliminate certain limitations of traditional storage systems in existing computers. Recently, companies need to run a data analytics program through a public cloud service provider. It helps to maintain and store a large customer database with maximum security. Thus, cloud computing can unlock new possibilities of data science for effective data management.