Big data is the most evolving term in a massive amount of people since the 1990s till this modern era of digitization. The merge of artificial intelligence with big data is enormously affecting our everyday lives. Artificial intelligence was discovered in 1956 during the Dartmouth Summer Research Project. Several bumps and hurdles were faced by artificial intelligence during the time period of technological advancements and development.
Undoubtedly, artificial intelligence is reshaping the landscape of the modern era of automation. Also, a prominent transition can be seen in this world where artificial intelligence is entering into reality from theory. In this era where our lives are accommodated with the Internet of Things, companies are also acquiring mastered artificial intelligence and big data technologies that will become the wave of the time.
The concept of big data is not something that is unfamiliar to people. The term is evolving in this world since the 1990s. But the concept of big data with the merge of artificial intelligence is again becoming the topic of discussion in these years. At the EMC World conference in May 2011, the concept of big data was discarded on the theme of Cloud Meets Big Data. A report was published by McKinsey in the same year in May and after that, the concept of big data become hot again.
So the question arises that “what is big data?” Big data is expanding in different directions which also possesses a wide range of technologies. Because of the versatility of big data, different people can have contrasting perspectives. For example, complex data analysis, massive data collection, etc. Thus big data can have various different characteristics.
The combination of artificial intelligence and machine learning is providing us with opportunities to incorporate various different use-cases of big data in a wide range of organizations such as health sectors, financial infrastructures, media, and communications, education sectors, manufacturing sectors, insurance sectors, energy, and sports sector.
One question could be summarized after the collection of customer data, and that is “now what?” answering that question, broadly speaking, instead of having a deep insight into data using manual efforts, artificial intelligence, and machine learning is providing different ways of data analysis. Data analysis is becoming less labor-intensive, more accurate, and efficient with the help of AI-powered big data. New capabilities of artificial intelligence are enhancing the analytics of this world where data-driven decisions take place.
Satellite data is utilized in 29 studies which proved to be the most significant use of big data. For example, a study in Haiti aimed to access whether CDR could predict the early statistical evolution of the pandemic of cholera.
Fortunately, Big data has the potential to help the detection of the outbreak considering the exponential growth in the number of coronavirus cases. Big data can be used in health sectors to analyze health records and keep track of the contact history of the patient which helps the identification of patterns of the spread of the virus. The evolution in the utilization of big data is resulting in the evolution of the legal posed challenges and ethical concerns. Ethical issues include lack of personal autonomy, compromised privacy, and the demand of the public to have a fair and transparent relationship between end-user and organizations.
During this era of digitization, big data and artificial intelligence are the most evolving branches of computer science that are playing a very crucial role in our everyday lives. Different technologies based on artificial intelligence and big data are acquired by numerous sectors and financial infrastructures and it is predicted that expansion in these fields will never stop.
Big data has a promising and hopeful future in the health sector despite all of the expected privacy challenges. Thanks to big data for deterring expected and unexpected customer risks during the process of data collection. Sectors would need to invest in the mandatory technologies for the enhancement of staff training and computing infrastructure. It would be interesting to see if methodologies based on big data results in predicting the future outbreak of COVID-19.