The 6 Best Data Science Research and Thesis Topic Ideas


Companies all over the world are looking for skilled and talented data experts that can use significant insights generated from data to improve business productivity and assist achieve company goals. Data science has recently become a profitable professional option.

Various data science and big data courses are now available at colleges and institutes to equip students for success in the digital industry. Participating in or taking on several data science projects is the best way to increase the robustness of a CV.

In this article, we’ve compiled a list of six research and thesis subject suggestions for data science projects in 2022.

  • In a distributed cloud, how to handle practical video analytics: Sharing videos has become a way of data and information exchange as people’s reliance on the internet has grown. The Internet of Things (IoT), telecom infrastructure, and operators all play a significant role in creating insights from video analytics. Several questions must be answered in this context, including the efficiency of existing analytics systems, the changes that will occur if real-time analytics are incorporated, and others.

  • Big data analytics in smart healthcare systems: big data analytics can help make healthcare more efficient, accessible, and cost-effective. By offering real-time analytics, big data analytics improves the operational efficiency of smart healthcare providers. It improves the capabilities of intelligent systems by utilising short-term data-driven insights, however there are still significant obstacles in this field that must be addressed.

  • Using real-time analytics to spot bogus news: In today’s world, the spread of fake news has become a major concern. The information acquired via social media networks may appear to be reliable, but that is not always the case. The data comes from unauthenticated sources the majority of the time, making it a critical issue to handle.

  • federated learning with real-world applications that is secure: Federated learning is a strategy that uses many decentralised edge devices and servers to train an algorithm. This technique can be used to develop models locally, but it’s unclear whether it can be used at scale, across many platforms, with high-level security.

  • The impact of big data analytics on marketing strategy: Data science and big data analytics have completely transformed the marketing sector. It has aided businesses by providing crucial information on their current and future clients. However, some challenges such as the existence of surplus data, the integration of complicated data into customers’ journeys, and total data privacy are still unexplored and require rapid attention.

  • Big data’s influence on business decision-making: According to current research, big data has changed the way managers and business leaders make key decisions about the company’s growth and development. It enables them to acquire objective data and analyse market situations, allowing businesses to adapt and make decisions more quickly. Students will have a better understanding of the current market and business situations as well as the ability to analyse new solutions by working on this topic.

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