(MENAFN- The Peninsula)
Deepak John/ The Peninsula
Data science, which enables better decision making, predictive analysis, and pattern discovery is crucial for entrepreneurs trying to solve their business problems, an expert has said during a webinar organised by the Ministry of Transport and Communications (MoTC) recently.
Speaking on the“Latest Trends and Challenges in Data Science”, Diaa Eldin Ali, a Data and AI Technical Consultant and Information Governance expert with several years of experience researching and engineering mission-critical, and data-intensive applications for IBM, discussed the latest trends in AI & Data Science and the challenges in Data Science.
He said:“Data Science consists of Artificial Intelligence (AI) and Machine Learning among others. In the field of AI, there is also a wide spectrum of capabilities, features, technologies and algorithms and Machine Learning is a very dominant domain today which is an area having a lot of discussions and investments to get much more value out of it.”
Data science is the domain of study that deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions. It uses complex machine learning algorithms to build predictive models. A data scientist analyses business data to extract meaningful insights and solves business problems by gathering data from multiple sources and processing raw data and converting it into a format suitable for analysis.
Ali said:“Within Machine Learning, we have multiple techniques which can be used to get results and insights. It includes supervised learning which is supervision by the author or data scientist and unsupervised learning where the computer trains itself when provided with algorithms. There is also reinforcement learning used in self-driving cars (like Tesla) and deep learning which uses more complex techniques to achieve the solutions”.
He went on to shed light on the current popular trends in Data Science such as Internet of Behavior (IoB), NLP (Natural Language Processing) and conversational analytics, augmented analytics, augmented data management, graph analytics, explainable AI, wearables & IOT, and Auto AI.
Ali added that these applications have received significant amount of attention and investment from the academia and the industry.
During the event, Ali also discussed the operational challenges in Data Science.“Firstly, understanding the problem which is complex and has boundaries around it. Secondly, data handling that is choice of the right data, the right data sampling, preparation, and assumptions. Thirdly, lack of relevant skills of technology, the business domain or the mathematical model underneath,” he added.
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