Future Of Data Science: 10 Predictions You Should Know/data-science-insights/future-of-data-science-10-predictions-you-should-know

Future Of Data Science: 10 Predictions You Should Know

Future Of Data Science: 10 Predictions You Should Know

Data Science has evolved all the way long from statistics– with simple statistical models, the organizations collected, managed, and analyzed the data from the 19th century. Later, once computers emerged in the scenario, the digital era began generating massive amounts of data. The internet has made a breakthrough with the explosion of data, and the need to manage Big Data has led to the growth of Data Science. 

Data Scientist skills help organizations to make informed business decisions through effective data management. Data science technologies trigger personalized healthcare systems, targeted advertising, risk and fraud detection, airline route management, financial applications, and many other processes of various industries.

The future of data science is uncertain; however, it would definitely bring further innovation in business processes with the technological revolution. This article, let us know the top 10 predictions of data science.

Why is the Future of Data Science the most debated topic?

Data Science is the most emerging opportunity where data scientists use advanced techniques like Machine learning and intense algorithms to let organizations perform data extraction, data visualization, and data maintenance. 

As data science keeps growing, there are numerous job opportunities for every data science professional with relevant data science skills. According to Naukri, there are 50,000+ data science jobs listed for data scientists as of March 2022. It is expected that the market would witness a growth of 46% in employment opportunities for data scientists by 2026.

It is a wide career path that continuously evolves with promising job opportunities. A Data Science career is likely to become highly specific with more specializations in this field. It makes new technologies operational with real-world processes like IoT (Internet of Things) and 5G that improves steadily. 

Predictions about the future of Data Science 

With cloud deployment and data analytics, data science has made it easy to access data through serverless technology. More data scientists focus on using the hybrid cloud to solve complex business concerns at a faster pace. Natural Language Processing (NLP), Artificial Intelligence (AI), IoT, and ML algorithms in conjunction with data science have been helping the business solve huge datasets and empower human-machine interactions. 

  1. The tasks of Data Scientists hired to augment business processes could be automated in the near future
    The field of data science research is expected to grow at a 22% rate from 2020 to 2030, says the US Bureau of Labor Statistics. This doesn’t mean that machines would replace data scientists entirely, but it shows that AI and other automation tools can help them relieve the work with augmentation. Data scientists are still required to supervise, monitor, and interpret the outcomes of automated systems. The no-code platforms and low-code programs will keep growing and organizations will largely adopt them more than anyone could think.
  2. Data Science will incorporate concepts from various fields like sociology and psychology– it will soon become interdisciplinary
    Data science is a combination of many concepts like computer science, statistics, and mathematics. But since the datasets are more complex, data scientists need to depend upon the concepts derived from other fields such as sociology, psychology, etc. to interpret the data easily. With this interdisciplinary approach, the data science career lets you understand and analyze the data to make real-time business decisions.
  3. Social Media and other online platforms will become the source for the collection of more data
    Data will be gathered mostly from Twitter, Facebook, and other social media platforms or websites. These sources help businesses gain a great understanding of the thoughts and opinions of people about various topics. Also, this data can help to make decisions about product development and marketing strategies. Companies and organizations can customize the needs and wants of the customers when they get to know what people talk about online.
  4. Data Science will help businesses predict the consumer behavior
    Data Science will be used more to understand and predict customer behavior. Data Science helps to figure out the data patterns which helps in this process. For instance, if a business knows a group of customers who buy a certain product and also search for another product to purchase, they can target these buyers to promote the second product.
  5. Data Science is moving into an era of becoming a team activity. It speaks not about creating a model, but what would you use it for once you build it.
    The major challenge lies in how you utilize the models and make them actionable. Businesses should be able to leverage the functionality of the models and use them for real-time decisions. The future of data science would think about this concern and form techniques to operationalize the models.
  6. Data Science will grow more conscious of the increased cybersecurity threats
    Data scientists will face a rise in demand for cybersecurity skills. Since the world has already begun chasing everything digitally, it is necessary to protect the information from intruders. Data scientists should be aware of the cybersecurity techniques and tools to safeguard business data.
  7. Data Scientists will face a growing Cloud Computing prevalence
    By 2025, about 463 exabytes of data will be produced per day– this is the same as 212,765,957 DVDs, says World Economic Forum. Cloud computing gives data scientists access to computing resources, which they can use to process big datasets. Since more businesses move to the cloud, the data science professional needs to understand and use cloud-based tools and techniques for data processing.
  8. Data Scientist’s jobs become more operationalized with advanced tools to capture their workflows and train enterprise on their best practices
    New tooling is largely coming in to augment the workflows of data science professionals. These can automate the workflows and create a platform to let companies train organizations based on how to utilize the workflows effectively. This makes the job of a data scientist more operation-specific.
  9. Coding and AI skills will become more essential, and data scientists need to be more business-minded
    Earlier, data scientists focused more on modeling and statistics, while less on coding. However, with data science growing at a faster pace, the tools data scientists utilize for data analysis have become highly sophisticated. Since datasets have become more complex, data scientists should develop a data science career with powerful coding skills in the future.
  10. Data Scientists will get the opportunity to initiate a “quantum leap”
    Quantum computers can make data processing faster than conventional computers, which helps data scientists to make data analysis effective. It uses a new algorithm with quantum mechanical properties to extract information. The data scientists will focus on quantum algorithms and use them to solve real-time problems.

Final Thoughts

Data science makes the way forward powerful with many emerging trends that help organizations to thrive. However, these changes would lead the organizations to look for candidates with advanced Data scientist skills. To make the most of this demand and win opportunities, Data science certifications can be a great pick. With data science certifications from an expert program provider, you can build all the necessary skills to make a revolution in data science.

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