What Technologies Are Emerging In The Data Science Industry?
As one of the most in-demand and quickly developing fields in tech, data science is very much an industry on the rise, as businesses look to tap into the immense power of data analysis to benefit their business functions.
In the modern day, technology permeates essentially every area of a person’s life, having an impact on areas of work, study, and play – and with this exponentially increasing rate of human interaction with technology, the amount of data being produced by tech devices daily is truly difficult to comprehend.
The problem for employers and business owners is that a data science skill set is quite rare, especially when put into the context that the number of jobs available in data science is increasing significantly, to the point that it is the fastest growing job sector in the world, by many metrics.
However, those that join the data science workforce will be entering a sector that is benefitting from huge funding and expansion, with new technologies entering the data science field and continuing to revolutionize the way that businesses strategize and make decisions.
Read on to find out more about the technologies emerging in the data science sector.
One of the most prominent technologies making an impact on data science is artificial intelligence. AI is so effective and so potentially revolutionary in its applications that you are likely to find AI affecting any industry that is looking to push the boundaries of what is possible.
Artificial intelligence has applications in a number of cutting-edge areas, such as in driverless cars, voice assistants such as Alexa and Siri, and in a large range of predictive technologies that affect areas such as science and healthcare.
Not only are significant amounts of data required to build algorithms and artificially intelligent systems, using methods such as machine learning, but they are a rich source of data within themselves.
When interacting with humans, the environment, or a predetermined set of data, AI actively collects data, compares it, analyses it, and uses it going forward to perform functions with increased proficiency.
Cloud storage and computing
With the ever-increasing demand for data to make better-informed business decisions, and the sheer amount of data that companies are now capable of harvesting, comes the dilemma of storage.
There are two main priorities for ensuring successful data storage, and they are efficiency and security. Unfortunately, traditional servers are neither efficient in their energy consumption, nor necessarily secure, as they can be breached or broken physically, and require expensive maintenance and repair.
When studying on a Pluralsight data science course, you’ll learn more about data and the cloud, such as how cloud computing offers to change this completely by giving companies access to completely cloud-based data storage solutions, which don’t require energy costs and maintenance, and is scalable instantly when necessary.
Internet of things
With the internet of things increasingly a feature of the everyday person’s life, there is huge potential for significant amounts of data to be collected that can actively improve the functionality of internet-connected devices, and in turn how effective they are in making lives easier and more convenient.
By analyzing patterns of use of energy in your home, an AI-based heating system could scale temperature up and down with maximum efficiency in mind.
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