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The term “Big Data” refers to the volume, velocity, and variety of data generated over time by healthcare providers and containing information pertinent to a patient’s care, such as demographics, diagnoses, medical procedures, medications, vital signs, immunizations, laboratory results, and radiology images. Figure 1.1 depicts above mentioned healthcare entities.

Figure 1.1 Big data in healthcare.

Figure 1.2 Five vs of big data.

According to Thota et al. [1], electronic health sources such as sensor devices, streaming machines, and high-throughput instruments are accumulating more data as medical data collection advances. This big data in healthcare is used for a variety of purposes, including diagnosis, drug discovery, precision medicine, and disease prediction. Big data has been critical in a variety of fields, including healthcare, scientific research, industry, social networking, and government administration [1]. The five Vs of big data are as follows as shown in the Figure 1.2 for better understanding:

1 1. Variety: Without a doubt, the variety of data represents big data. For instance, among the various data formats are database, excel, and CSV, all of which can be stored in a plain text file. Additionally, structured, unstructured, and semi-structured health data exist. Clinical data is an example of structured information; however, unstructured or semi-structured data includes doctor notes, paper prescriptions, office medical records, images, and radio-graph films.

2 2. Veracity: This data’s legitimacy in the form of veracity can be challenged only if it is inaccurate. It is not about the accuracy of the data; it is about the capacity to process and interpretation of data. In healthcare, the trustworthiness function gives details on correct diagnosis, treatment, appropriate prescriptions, or otherwise established health outcomes.

3 3. Volume: Without a doubt, the large volume represents large amounts of data. To process massive amounts of data such as text, audio, video, and large-format images, existing data processing platforms and techniques must be strengthened. Personal information, radiology images, personal medical records, genomics, and biometric sensor readings, among other things, are gradually integrated into a healthcare database. All of this information adds significantly to the database’s size and complexity.

4 4. Velocity: Big data is completely represented by the amount of information produced every second is considered as velocity. The information burst of social media has brought about a wide range of new and interesting data. Data on overall health condition and growth of the plant size and food bacteria are stored on paper, as well as various X-ray images and written reports, is up dramatically.

5 5. Value: Big data truly embodies the value of data. When it comes to big data analytics, the benefits and costs of analyzing and collecting big data are more important. In healthcare, the creation of value for patients should dictate how all other actors in the system are compensated. The primary goal of healthcare delivery must be to maximize value for patients.