28/05/2024
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Big Data Analytics and Trends

Big data analytics is the detailed process of collecting, storing, and analysing large and complex datasets to gain insights that help organisations make better business-related decisions. Through the application of these techniques, it is possible to extract valuable information from massive amounts of raw data collected in various ways. The term “Big Data” refers to datasets that are incapable of being processed and analysed using traditional database management and analysis methods because of how large and complex they are in nature. Datasets are collected from various sources such as social media, logs, customer transaction history, interviews, questionnaires, and much more. A company has to decide what source of data it considers useful and worthwhile before adding it to its training algorithm.

In the world of Banking and Finance, big data analytics plays a crucial role in fraud detection and prevention. By analysing large volumes of transactional data through the use of machine learning algorithms, financial institutions can detect suspicious activities, identify potentially fraudulent patterns, and take immediate action against them. This minimises financial losses and protects customer assets. When a bank analyses market data, and news, they can optimise better trading and investment strategies. By analysing their customers’ behaviours and preferences, they can personalise their offerings, while enhancing customer experience and retention. Banks can also more easily assess the credit scores of their clients and make well-informed decisions regarding loan approvals and interest rates when they analyse credit history and employment records. 

In the world of Aviation, weather conditions, flight data, and air traffic can all be incorporated into the analytical system playing a crucial role in developing predictive models to prevent accidents. The data may also help in optimising air traffic which can help reduce delays and improve fuel efficiency. From analysing seasonal demand patterns and booking data, revenue management becomes more efficient which can lead to more dynamically adjusted ticket prices. Understanding passenger behaviour can offer personalised services, improve customer satisfaction, and tailor marketing campaigns. The goal is to improve the passenger experience overall.

In Agriculture, big data analytics can be harnessed in Soil Science to enable farmers to collect and analyse data on soil conditions, weather patterns, and crop growth to make very precise decisions when it comes to irrigation and fertilisation. Crop yields can be greatly improved through the detection of early signs of diseases and pest infestations through the use of remote sensing technology. With the addition of customer sentiments and satisfaction with the product, a farmer can better optimise their supply chains and know where to directly transport and store their produce to meet the market demand.
When it comes to livestock farming, this technology can help monitor animal health, track feeding patterns, and optimise breeding programs.

In the medical world, mountains of data are generated daily which is extremely crucial for patients, medical institutions, insurance companies, government, and research teams. With strategic analysis of these data pools, medical researchers can be better equipped to devise more targeted and successful treatment plans but also procure medical supplies from all over the world. Patterns of diseases can be identified and risk factors associated with them can be better understood with more effective treatment and medicine created to better combat them. Organ donation can be more predictable and stable ensuring said organs are always in the proximity of patients who are compatible with them. Prediction of a pandemic or epidemic outbreaks can proactively prepare the world for any outbreak of viral diseases.

It cannot be overstated how greatly data analytics would enhance industries around the world. The statistical advantage gained from analysing millions of user and customer records can bring so many benefits to companies and industries. The user experience greatly improves overall. As data analytics becomes more and more fleshed out, it will become apparent just how far-reaching and beneficial these algorithmic tools are.

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