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Have you ever jumped on a roller coaster and regretted it right away? 2020 has been what the roller coaster has to offer. It opened with an Australian wildfire and a major act – the Covid epidemic has killed 1.84 million people and counts.
But 2020 has given the emergence of technology a strong push and it has moved rapidly. The year also reminded us how easy it is to lose track of critical changes in the technological world during a major human catastrophe. We’ve seen every business go online, and everyone has to work from home at some point this year. As a result, there has been an unexpected turnaround in the way data is handled. Data science as a business tool and AI used was already very large in 2019 itself. 2020 has given the existing framework to work for its own finances. Now, as the year 2021 begins, it is important that data science and AI enthusiasts focus on trends.
The world will see the development of natural language processing; computer vision will grow stronger and more important in areas such as defense and security; Health care statistics will have a year of unprecedented growth, just to name a few. As data science enthusiasts and students, you need to align your mind with ever-changing field perspectives.
Luckily enough, AnalytixLabs and Analytix India Magazine have been collaborating for the past few years to come up with the most important trends for AnalytixLabs and Data Science that are likely to continue to showcase the year.
The 2021 edition of the report gives you access to the ideas of some of the best minds in the industry. You will find captions for the report here, but it is highly recommended that you go through all of this.
1. Increased Cloud Dependence
The cloud will be the backbone of remote workers – Revitalizing data centers and new IT infrastructure to provide the efficiency and balance needed to keep remote employees stable will be extremely difficult. Dependence on clouds will increase. Using a computer and cloud computing will be very important, data security will be a top priority.
Use of cloud for analysis – Cloud-based data management will grow in monetary terms, and analytics efforts will revolve around the cloud. Cloud technology will pass from the purchase mode to the research and analysis area.
Hybrid cloud dominance – Relying on a cloud of mixed business management and data analysis will be an important trend this year. Businesses need a combination of agility and security, and that is exactly the promise of a mixed cloud.
Cloud Democratization with the rapid adoption of AI and ML – Sectors such as health care and manufacturing are always trying to incorporate used AI and machine learning into their processes. This increases the demand and production of public and private clouds. As a result, the cloud is very affordable to launch.
2. RPA and IPA become Industrial Center
Automated data mining robot process – The RPA will be used with great force to make low-cost efforts automatically. This will add great momentum to the data analysis.
Intelligent process automation for decision making – AI will enhance the knowledge of decision-making staff by helping them enter more data points while making calls.
Lots of chatbots – The current year will see a strong reliance on AI-based chatbots among businesses.
3. NLP Earns More Money Than Ever Before
Indigenous language processing will grow everywhere – NLP has been one of the main concerns of AI researchers since its inception. NLP technology is now mature enough to be used by all sectors to discuss machines.
Cognitive bots as de-facto human helpers – NLP-enabled bots will increase the skills of knowledge workers.
Improved access to random data – Businesses will be able to access additional black data with the help of NLP.
NLP security and detection fraud – Multimodal technology that combines NLP with computer vision will allow KYC video and fake detection.
4. Filling Spaces with AI on Non-Traditional Domains
Complete solutions to unexpected problems – Artificial intelligence has so far been used to perform specific tasks in specific areas. 2021 will see a comprehensive approach to everything related to AI used.
Data science as a core business activity – Instead of being a support function, data science online training has become a major business activity. This will be a pillar in 2021.
Full use of AI in health care – Adding health care systems to AI will be one of the most important.
5. Dealing with Cybersecurity Barriers through AI
Dealing with threats – 2020 ends with the discovery of a massive data theft known as the Solarwinds scandal. This also opens our eyes to the growing dangers of data security. It will be a challenge for companies in 2021 to address these threats.
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