Data science has become a household name for people who are remotely tech savvy. With rapid developments in machine learning and AI driven analysis an increasing number of industries are investing and focusing on data science. The discipline of data science is characterized by two things right now, expanding applications and constant change. It is often hard to keep track of the evolution of the field. Hence, the necessity of looking into the trends is felt time and again.
1. The overhaul by Python
In 2019 Python took a lead on JavaScript in the number of questions on stack overflow. Now, it is the most used language by data analysts and far along in its way to becoming the most popular language in general.
Varied libraries for data science like Pandas and machine learning like ScikitLearn contribute to the overwhelming popularity and widespread acceptance of Python as a suitable language for programming algorithms and building models. A friendly learning curve does add to the advantages.
Python developers are highly in demand and analysts with Python skills are sought after with a lot of vigour by the employers.
2. The demand for data analysts is through the floor
The global data storage is predicted to reach 175 zettabytes by 2025. Well, that is a lot of data to be parsed. With machine learning in the game no one expects human analysts to take such a task up, not that it is possible at all. Then what fuels the rising demand for data analytics professionals?
The expansion of the data science industry means the inclusion of new features and new parameters to analyze the data according to the corresponding industry. While a trained algorithm can handle a ton of data the process of training is what takes the human intervention. A machine learning algorithm can improve itself through exposition to data, but the training data comes in all shapes, sizes, formats, and varied degrees of mess.
Tidying up the training data, managing the pipelines, ensuring security measures, engineering the features, are all tasks that need human intervention, hence the skyrocketing demand for data analytics professionals and data scientists around the globe.
3. End to end data science services are at the vogue
Now that businesses have realized the value of a comprehensive data science practice, they want end to end solutions where a service provider takes care of every step of the process from collecting data to visualizing the results. There are AI driven tools that can automate a lot of the processes. These tools along with skilled analysts who can tidy up the data and develop the models work in tandem to create end to end data science frameworks.
4. Data privacy concerns
The Cambridge analytica revelations changed the way people and government perceived data privacy on the internet. Both Google and Facebook faced legal as well as public scrutiny for their apparently questionable data sharing practices. These revelations were followed by the enforcement of stringent data security regulations like GDPR and CCPA.
Currently, as many new businesses are starting their data analytics practices, the need for data privacy and governance is realized. Data architects and engineers are in high demand because of this trend. The market for data governance is growing as fast as the expansion of the data science industry is taking place.
If you are pursuing a data science course in Bangalore, this is one more field of employment that you should consider.
5. The deep fake nuisance
Deep fake refers to the use of deep learning to create fake videos and audios of people usually for legally untoward practices. It has become awfully simple for skilled machine learning operatives to plant one person’s face on another’s action. And we are not just talking about a face swap but a complete swapping of the personas.
The practice of deep fake has caused quite a few disturbances. It is used to portray celebrated figures in the wrong light. It can be a raging weapon for political anarchists. In fact there have been instances where fake audio has been used to extort money.
Governments and authorities are well aware of the dangers of deep fake. Many measures are taken to control its effect including the development of counter-technologies.
That is it for this one. The world of data science will keep on changing and we will keep writing about it. You will get a mix of stale and fresh news, but it should help you plan your steps in the industry, nonetheless.