Blog ▸ Candidates ▸ Hottest Trends on Data Science Jobs in 2022
Hottest Trends on Data Science Jobs in 2022
By Vahid Haghzare, Director Silicon Valley Associates Recruitment &
Armae Garcia, Marketing Associate, Silicon Valley Associates Recruitment
One of the top IT Recruitment Agencies in Hong Kong, Dubai, Shenzhen, Shanghai, Singapore, and Japan, SVA Recruitment is an IT and employment agency that provides jobs, executive search, and recruitment services.
Data Science is a multifaceted method used by various sectors by companies in Hong Kong, Shanghai, Shenzhen, Singapore, Dubai, and Japan to derive useful information from their company’s growing amount of data.
It includes data processing, executing complex data analysis, and unveiling the output that will uncover patterns to validate rational conclusions for companies and businesses.
With this, Silicon Valley Associates Recruitment has listed the hottest technical trends in Data Science jobs to look out for this 2022 according to our IT Recruiters, in case you are planning to take on the data science career path.
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Cloud Data
The accumulation of data in large quantities is boundless and the real challenge now is where and how the structuring, collecting, formatting, tagging, cleaning and analyzing of this immense amount of data in one safe place. This is where data science and AI come in. One more problem is data storage.
This year, the utilization of cloud services (public or private) for data analysis is considered as one of the major data management trends.
SVA Recruitment discovered that about 45% of companies across Asia are adapting to cloud services and transferring huge volumes of data to cloud platforms.
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Augmented Analytics
Augmented analytics applies artificial intelligence, machine learning, and natural language processing to automate data analysis of massive amounts of data. A data scientist, normally tasked with providing insights, is now aided by software that delivers those insights in actual time. Enterprises can process large amounts of data in much less time and gain useful insights from that data. The resulting accuracy makes better decisions for IT Recruiters much more possible.
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Data as a service exchange (DaaS)
The practice of acquiring and using data as a service is now trending. Websites often integrate Covid-19 data to display the number of cases in a region or the number of deaths, and other status updates. The data presented here is acquired from other companies that offer the information as a service. Companies can use this data to be more efficient in their business processes.
In order to minimize data security risks, businesses are developing policies to minimize the possibility of a data breach or legal action. Data from the vendor’s system can be moved to the buyer’s without any data loss or breach. Data-as-a-service, or DaaS, is one of the most promising data analytics trends for 2022.
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Actionable Data
Unless data is analyzed to achieve actionable insights, expensive data software is of no value. Through these insights, you can better assess the present status of your business, both external and internal challenges, and opportunities. Actionable data helps you make better decisions and protect the company's interests. Through this actionable data, you can improve the organization’s general productivity including streamlining workflows, distribution of projects, and planning activities for the organization.
Check out also: What trends to look forward to in 2022 as a Data Scientist
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Edge Computing
Edge computing refers to the practice of processing data near the source where the information is captured. Companies seek to use the internet of things (IoT) and data transformation services to access edge computing. This leads to a better overall performance of the organization.
Furthermore, latency is reduced and processing speed is increased by using edge computing. With the integration of cloud computing services and edge intelligence, employees can work remotely while greatly improving the quality and speed of their productivity.
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Data Cleaning
By 2022, data alone will not be sufficient for advanced analytics. The term "data cleaning" refers to removing duplicate or redundant entries from a database, and to correcting incorrect data which leads to slowing down of data retrieval and waste of money and time for the organization.
Several companies and IT researchers are investing in data cleaning automation to speed up data analytics and gain valuable insights from large datasets. Artificial intelligence will be used to automate processes involving data cleaning.
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Usage of Natural Language Processing (NLP)
NLP is originally a subset of artificial intelligence, now being utilized to study data and discover trends, patterns, and insights. It can be predicted that in 2022, there will be an increase in the use of NLP for retrieving information from data repositories. NLP will be able to derive quality information from the comprehensive information that is collected.
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Hyper Automation
In 2022, hyper-automation—a trend that began in 2020—will be a domineering trend in data science. According to Vahid Haghzare, Director of Silicon Valley Associates Recruitment, hyper-automation is unavoidable and irreversible, and anything that can be automated should be automated to increase efficiency.
Automating processes to leverage artificial intelligence and machine learning across a wide range of business applications is the key first step in digital transformation. Hyper-automation uses advanced analytics, business process management, and robotic process automation as its basis. Robotic process automation is expected to continue growing in the next several years.
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Silicon Valley Associates is ideally positioned to support the continual demand from tech companies and IT Departments looking to hire in Hong Kong, Asia, and Worldwide. Please let us know if you would further advise on the above topic or your hiring needs
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