Technology is constantly evolving, and so are we. There will be massive growth in Artificial Intelligence and Machine Learning over the next few years. There is already a significant amount of data to manage, and with new technological advances, we can use big data in many ways. To do this, we need to keep up to date with the top 5 data science trends in 2020.
Data science covers a variety of topics that includes deep learning, internet of things and artificial intelligence, etc. we can say that data science is not a single term or it can solve the variety of business problems that includes algorithm computation, analysis, a mix of data inference, and technology.
It also provides companies with advanced tools and technologies to help them automate complex business processes related to extracting, analyzing, and presenting raw data. Since there is so much going on in the technical field and data is generated quickly, it is important to know the latest and upcoming trends in data science.
To keep you up to date on data science trends, we have compiled a list of the five most important data science trends that should help your business succeed.
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Artificial intelligence has become the common technology for small and large scale business and it will thrive in the next few years. We are in the early stages of using artificial intelligence technology but in 2020 we will see more advanced uses of this technology. What is the reason that AI is growing fast? The reason is companies can improve all of their business processes and customer data by using AI.
Although the use of AI remains a challenge for many, it is not so easy to research the evolution of this technology. In 2020, we will find more advanced applications developed with AI, machine learning and other technologies that can improve the way we work. Another trend that is conquering the market is automated machine learning, which will help transform data science through better data management. Therefore, you may need special training to perform deep learning.
According to an IDC report, investment in IoT technology is expected to reach $ 1 trillion by the end of 2020, signaling the growth of smart and connected devices. Even in 2019, we used apps and devices that we can use to control our household appliances like air conditioning, TV, etc. Most of you may no longer know this, as this is only possible via the Internet of Things.
IoT is continuously attracting user’s attention. If you have ever encountered smart devices like Google Assistant and Microsoft Cortana that we can use to automate normal things, then you will get to know the power of IoT. This will encourage the companies to invest in this technology, especially in the development of smartphones where IoT is most commonly used.
When we talk about data science, we cannot ignore big data. Most of the companies are using big data to achieve their business goals. Many enterprises are using different kinds of tools to analyze data; python is mostly used in this.
Businesses are also focusing on the predictive analysis that helps them to create smarter strategies for their businesses. Predictive analysis helps you to identify the interest of your customers based on their browsing history and their purchase. Depending on that, you can able to create strategies for your businesses.
Edge calculation is currently driven by sensors. With the growth of the IoT, however, edge computing will take over traditional cloud systems. Edge computing enables businesses to store streaming data near data sources so that they can be analyzed in real-time. It also provides an excellent alternative to big data analytics that require high-end storage devices and higher network bandwidth.
As the number of devices and sensors for data collection grows rapidly, companies are turning to advanced computing because it can solve bandwidth, latency, and connectivity issues. Combined with cloud technology, edge computing can provide a synchronized structure that helps minimize the risks associated with data analysis and management.
The introduction of artificial intelligence and machine learning will create many new roles in the industry. Data science security professionals will be in high demand. Since artificial intelligence and machine learning are completely dependent on data and are supposed to process this data effectively, data scientists must have specialist knowledge of data science as well as computer skills.
Although the corporate market already has access to much knowledgeable data science and IT professionals, there is still a need for more professional data security professionals who can safely process customer data. For this purpose, data security scientists must be familiar with the latest technologies in data science or big data analysis. For example, Python is one of the most commonly used languages in data science and data analysis. So, if you know the concepts of Python well, you can solve problems related to the security of data science.
Data science has become the popular technology of 2020. Here I have shown you the top 5 data science trends in 2020. You can check these trends and based on this you can analyze your business and get to know where you have to improve. I hope you have understood the popularity of data science.
Near Learn is the Best Data Science Training institute in Bangalore and provides training on Artificial Intelligence, Machine Learning, Deep Learning, Full-Stack Development, Mean-Stack development, Golang, React Native and other technologies as well.
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