10 top data science trends of this decade

With rapid digitalisation making businesses fast-paced, there are massive volumes of data which need to be monitored. This has further enhanced the relevance and significance of data science in the present era of ubiquitous technology. Data science is the domain in which scientific techniques, processes, algorithms, and frameworks are used to deal with mass amounts of data. It is mostly used to find unseen patterns, derive meaningful information, and make business decisions.

Predictive analysis has evolved as a major aspect of business operations to expand its capability with diverse forms of data. It can be applied in several business operations, like customer segmentation, risk assessment, sales forecasting, and market analysis.

Following are the top ten trends in the fastest-growing domain in the technology industry:

1. Natural language generation: It is the application of Artificial Intelligence (AI), to extract written or spoken narratives from a data set. It primarily involves machine to human and human to machine interaction, including computational linguistics, natural language processing (NLP) and natural language understanding (NLU).

Natural language generation is a multi-stage process which includes content analysis, data understanding, document structuring, sentence aggregation, grammatical structuring, and language presentation.

2. Speech recognition: Speech recognition or speech-to-text is the application of technology, mostly AI and machine learning (ML), to enable machines or programs to identify and understand human speech and convert it into readable texts. Speech recognition can often be confused with voice recognition, which is just identifying an individual’s voice.

Some of the major applications of speech recognition are language weighing, speaker labeling, acoustic training, and profanity filtering.

3: Machine learning platforms: As the amount of data businesses amass increases, the significance of machine learning (ML) platforms also gets enhanced. ML platforms are on the rise because of algorithms, application programming interfaces (APIs), development and training tools and massive data sets. Machine learning tools combine intelligent algorithms with data, provide business insights and help develop new solutions.

4. Virtual Agents: Virtual agents or intelligent virtual agents (IVA) or virtual rep or chatbots are software programs that use scripted rules and artificial intelligence applications enable the software agents to communicate with humans. The common application of virtual agents is in routine customer service functions to cater to standard requests or handle simple problems.

5. Decision Management: It is an automation approach with the blend of machine learning and business rules to enable organizations to understand appropriate actions to be taken and ease decision-making. In its application, artificially intelligent robots have the ability to instill logic into AI systems in order to prepare them for training, management, and tuning.

6. AI-optimised hardware: With the emergence of deep learning, cloud and parallel computing architectures, artificial intelligence has also evolved with more sophisticated capabilities like speech, image, video, and text recognition. AI hardware orchestrates and coordinates computations among accelerators.

7. Deep learning platforms: They are a subset of AI and machine learning that use neural circuits similar to those found in the human brain to process data and discover trends for decision-making. With the use of multi-layered artificial neural networks, deep learning platforms deliver immaculate accuracy in object detection, speech recognition, language translation, and others.

8. Robotic process automation: It refers to the software technology to build, deploy and manage robots to emulate humans’ actions interacting with digital systems and software. The process involves robots, where the term automation refers to the mimicking and automation of human functions.

9. Biometrics: It is the science of recognizing, measuring, and analyzing the physical characteristics of the human body. To achieve organic interactions between humans and machines, it uses touch, pictures, words, and body language.

10. Cyber defense: It refers to a system that detects, prevents, and mitigates cyber attacks and threats pertaining to a system’s data infrastructure.

This article is authored by Nirpeksh Kumbhat, Founder & CEO, SkillEnable.

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