Big data is a field of AI that introduces ways to analyze, systematically acquire information from, or otherwise manipulate data sets that are too large or complex to be dealt with by traditional data-processing application software. Big data includes datasets with huge sizes exceeding traditional programs’ capacity to handle appropriate time and value (Wikipedia, 2020). The characteristics of Big Data are (Kitchin, 2014):
- Enormous volume, consisting of terabytes or petabytes of data.
- High velocity, being created in or near real-time;
- variety, being structured and unstructured in nature.
- Exhaustive in scope, striving to capture entire populations or systems.
- Fine-grained resolution and uniquely indexical in identification.
- Relation in nature, containing common fields that enable the conjoining of different data sets.
- Flexible, holding the traits of extensionality and scalability.
2. Applications of Big Data
Big data is a sign that everything is changing. Every portfolio is affected: finance, transport, housing, food, environment, industry, health, welfare, defence, education, science, and more (Johnson, Big data: big data, digitization, and social change, 2017). Here some of the applications in big data (Wikipedia, 2020):
The use and modification of big data inside governmental applications allow getting the benefit, especially in terms of cost, productivity, and innovation.
Providing personalized medication, clinical risk intervention, and medical prediction systems using big data analysis has improved healthcare very well.
The industry moves away from the traditional approach of using specific media such as newspapers, magazines, or television shows. Instead, it taps into consumers with technologies that reach targeted people at optimal times in optimal locations.
Health insurance providers gather data on social “determinants of health” such as food and TV consumption, clothing size, marital status and purchase habits. This information can be used to make predictions on health costs in order to spot health issues in their clients.
- Internet of Things (IoT)
The IoT devices provide information that is used to make a mapping of device interconnectivity. The media industry, special companies, and governments have been using these mappings in order to reach their audience more effectively and increase the efficiency of their media.
- Information technology (IT)
Big data has been used as a helpful tool for employees in their work, making “big data” significant within business operations. Big data helpful application in IT made the collection and distribution of information technology (IT) more efficient. Applying big data processes with Machine learning and deep learning makes IT departments more powerful in predicting potential issues and providing solutions before the problems even happen.
3. Benefits of Big Data
The impact of big data, open data, and data infrastructures can be seen clearly in science, business, government, and civil society (Huberman, 2017). Here some of the benefits of Big data:
- Businesses can analyze customer traffic to calculate precisely how many employees they will need each hour of the day. The goal is to spend as little money as possible (Arslan, 2016).
- Geographical coverage: global sources delivered sizable and comparable data for all countries, no matter their size (Wikipedia, 2020).
- Level of detail: providing fine-grained data with many interrelated variables and new concepts, such as network connections (Wikipedia, 2020).
- Timeliness and time series: graphs can be produced within days of being collected (Wikipedia, 2020).
4. Big Data Challenges
Big Data challenge is not a technical problem of transferring the maximum number of bits in the minimum amount of time, but also the scientific challenge of formulating approaches to perform the complex and twisted systems that must design and manage to run the modern world (Johnson, Big data: big data, digitization, and social change, 2017).
Another challenge is coping with its abundance and exhaustivity (including sizeable amounts of data with low utility and value), timeliness and dynamism, messiness and uncertainty, semi-structured or unstructured nature, and the fact that much of big data is generated with no specific question in mind or is a by-product of another activity. The tools for linking diverse datasets together and analyzing big data were poorly developed until recently because they have been too computationally challenging to implement (Huberman, 2017), (Useche, 2019).
5. Ethics of AI, Data science and big data
Millions of people use the web for their social, informational, and consumer needs. During that, they publish their information through all social networks (Huberman, 2017).
The problem is that with real-world data, there is often information in there that you did not intend to be in there, but it is captured because of the bias in the data collection process. Human beings can have very diverse motives for why they make something. We need to put checks and control in place like any technology that it has utilized to benefit us (Askell, 2020).
Big commercial companies gather troves of private data claiming no interest in personal details, while in reality selling, exchanging, or misusing such data (Johnson, Big Data: Big Data or Big Brother, 2018).
Arslan, F. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, by Cathy O’Neil. Journal of Information Privacy and Security, pp. 157-159.
Askell, A. (2020, 12, 1). Ethics & AI: Privacy & the Future of Work. Retrieved from youtube: https://www.youtube.com/watch?v=zNxw5gJtHLc&list=PLzdnOPI1iJNeehd1RXhnVMBFi1WhWLx_Y&index=7
Huberman, B. (2017, 12). Big Data and the Attention Economy. ACM Digital Library, pp. 1-7.
Johnson, J. (2017, 12). Big data: big data, digitization, and social change. Ubiquity, an ACM publication.
Johnson, J. (2018, 8). Big Data: Big Data or Big Brothe. Ubiquity, pp. 2-10.
Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society.
Useche, D. O. (2019, 4). Challenges of Interpreting Big Data. Retrieved from “Big Ideas”: AI to the Cloud: https://blogs.commons.georgetown.edu/cctp-607-spring2019/category/week-11/
Wikipedia. (2020). Big data. Retrieved from Wikipedia: https://en.wikipedia.org/wiki/Big_data