Introduction

For a very long time, we heard about the future of data science is the future. However, the question that needs to be answered is, What is the future of Data Science?

Once computers were introduced as mainstream computing devices, there was a change in the industry to the Digital Age. The rise of the internet exponentially grew the data available to what we know as Big Data. This explosion of information required the need for expertise to manage, process, analyze and visualize this data for decision making in the organizations through diverse models. This gave origin to big term Data Science.

Let’s  look at some areas which indicate the future of  data science;

Data Explosion: Today massive amounts of data is generated daily. Whether it is entertainment, manufacturing, medicine, sports, transport, or agriculture, it is all dependent on data. There would be a constant rise in the demand for proficiency to extract worthy insights from the data.

Rise of Automation: With the rise in the difficulty of operations, we will always strive to make processes simpler. Most machine learning frameworks would include libraries of models that are pre-trained and pre-structured. Data Visualization is a soft skill that would come to the forefront for Data Scientists.

Scarcity or Abundance of Data Scientists: Every day, thousands of individuals enrol to learn Data Science allied skills through college degrees or online courses. This might result in getting a feeling of saturation in this field. But it is important to understand that data science is not a realm that you can learn; it requires to be inculcated. Certainly, the skill learned is of great importance, but skills are just the tools that help understand and work with the data.

The approach and the ability to apply these tools to achieve various analytical tasks is what it means to be a true data scientist. Always remember there could be plenty of persons who have studied Data Science, but always there would be a shortage of true Data Scientists with an applicative sense.

Here are some of the top data science job future options;

  • Data Scientist
  • Machine Learning Engineer
  • Machine Learning Scientist
  • Applications Architect
  • Enterprise Architect
  • Data Architect
  • Infrastructure Architect
  • Data Engineer
  • Business Intelligence (BI) Developer
  • Statistician

Data science trends

The existence of data in every field is why organizations are paying attention to data science. It’s truly very important to stay updated with the latest data science future trends that could be a blessing for the growth of the business.

Here are the top 10 data science trends:

Predictive analysis: For a company to flourish, it is vital to know what the future of data science might seem like. This is precisely where predictive analysis comes into the picture. This technique comes up with the finest strategies to aim the customers for retaining the loyal ones and also get new ones.

Machine learning: Over the years, automation has changed the world. This is the main reason why machine learning has garnered importance. In the future of data science, we will observe more automation, and hence the increase in the number of companies implementing machine learning will certainly outshine our imagination.

IoT: Those days are gone when IoT was thought to behave as restricted applications. Today, our smartphones can direct appliances like TV, AC, etc. All of this is achievable because of IoT. Google Assistant is an incredible innovation in the field of IoT.

Blockchain: Cryptocurrencies like Ethereum, Bitcoin, Litecoin, Ripple, etc., have to turn out to be the talk of the globe. All of these cryptocurrencies utilize blockchain technology.

Edge computing: Edge computing is recognized for quicker processing of information, and it also brags of reducing cost, latency, and traffic. With this computing technique, managing real-time applications got better.

DataOps: Tasks right from testing automation, collecting to preparing to analysis, executing automated testing, delivery to provide enhanced data quality are enclosed in DataOps.

Artificial Intelligence: Tech giant or a small scale enterprise, all of them have counted on AI in one way or the other. Also, the decrease in errors is another main reason why Artificial Intelligence stands apart.

Data visualization: This is one of the major trends that we can depend on. Organizations are Changing their traditional data warehouses to cloud computing.

Better user experience: The degree to which user experience is given significance tells about the organisation’s success. Companies are trying hard to provide the best feasible user experience – be it in personal assistance, chatbots, or AI-driven tools.

Data governance: Many companies are still fighting to comply with government rules and regulations. Data science experts who have good knowledge about data governance are in demand.

Courses on data science

Some of the numerous data science courses available online are;

  • Data Science with Python
  • Machine Learning
  • Deep Learning with Keras and TensorFlow
  • Tableau Training
  • Data Science Capstone
  • Data Science with R Programming
  • Python for Data Science

Conclusion

If organizations want to triumph with the future of data science jobs, they have to meticulously understand the length and breadth of data with a diversity of all kinds of data, not just those which are compliant to statistical techniques. You can prepare for the future of data science by signing up for Jigsaw Academy’s courses on data science.

Data science specialists are required in every field. Organizations and government departments depend on the future of data science to better serve their customer base.