Data science is a scientific field that deals with collection, preparation, processing, analysis and visualisation of data. It is difficult to estimate the exponential increase in the popularity of this subject. However, we can easily conclude that the rise of data science has enabled effective data management as well as precise data analysis.
Since data science is a relatively new course, it is yet to be integrated into the curriculum of our engineering disciplines. However, the paradox is that the industrial sector is in need of thousands of data scientists who can help in navigating a business in a market dominated by data. It is in this context that professionals are pursuing data scientist courses in Bangalore, Delhi and other places of the country aiming to take advantage of data science positions in various companies.
Essential components of data science
Data science is an interdisciplinary subject that borrows strongly from mathematics. Statistical models, probability and other computational methods are critical components of data science. Data science also relies on information theory and knowledge discovery models. Machine learning techniques, deep learning techniques, artificial neural networks and other generative networks fall under its domain.
The scope of data science also includes dimensionality reduction, feature selection, feature extraction and large scale optimization.
Role of data science in knowledge discovery
Data science plays a great role in collection, processing and analysis of data. Data transforms into knowledge through a hierarchical process that we call the DIKW pyramid. The base of the pyramid is the widest and is represented by data. Data when processed becomes information. After further processing, we obtain knowledge from information. Information transforms into wisdom that represents the peak of the pyramid.
Data science also helps us in processing unstructured data and converting it into a structured form. In this way, data science helps domains like semantics, analytics, modelling as well as visualization.
When we say that data science helps in knowledge discovery, we refer to the aggregate of all the processes in the life cycle of data science that convert data into precious information and knowledge.
Data as a service
In the present times, cloud computing has revolutionized the entire ecosystem of computational services. Cloud based environments provide services like infrastructure as a service, software as a service, and platform as a service. However, the integration of data science with the cloud computing environment has led to the arrival of data as a service. This gives glimpses of the importance of data, its valuation as well as its importance to various businesses that have their base on the cloud.
Footnotes
It needs to be noted at this point in time that data as a service can become successful only when we provide security and trust in data-based services while simultaneously reducing the risks associated with the same. In one word, the sensitivity of data needs to be given utmost concern if data-based services have to flourish.
