Abstract
The ever-increasing flow of information in organizations has posed challenges to business for years and this has led to the development of the phenomena of big data. Following the adoption of the term “big data”, velocity, volume, veracity, velocity, and variety are the five elements that scholars have used to describe big data. For years, companies such as insurance firms have correlated data sets using the five elements. This has helped limit confusion attributable to the collection, storage and dissemination of complex data. The correlation is necessary due to the difficulty in managing huge volumes of data sets.
What is Big Data
Big data refer to huge volumes of multifaceted data sets stored in database for many uses depending on the nature of the operations of an organization. The common type of information stored in the data sets includes structured and unstructured information on companies, people’s profile, and research findings among other information. In large organizations, the correlation of the data sets is essential in minimizing the complexities attributable to the difficulties in collection, storage and dissemination of huge volumes of information from different sources. According to Mayer-SchöNberger & Cukier (2013, p. 3), the correlations in sets minimize the confusion in management of data. In particular, the extent of the size of the data makes it difficult for businesses to utilize traditional management tools in processing the data.
The five V’s of Big Data
Volume is one of the five vs of big data. It describes the enormous amounts of data produced per second. The measurement for the quantities of data is in bytes. The other two vs of the five vs are velocity, variety. The last two are veracity and value. For velocity, the pace of creation of new data defines big data. From the definition of volume, data is rapidly expanding and as such, organizations will face difficulties in managing volumes of data in years to come. This will increase the speed of production of data. As a v of data, velocity influences the capacity of storage of data in databases. Another v that is variety facilitates analysis on the capacity of individuals to generate data. Variety describes the uniqueness of data in terms of structure. As noted, huge volumes of data transmitted in different parts of the globe are unstructured (Ohlhorst, 2013, p.6). For veracity, it is the accuracy of data described. The last v is value. This refers to the usefulness of data. The estimation of value is dependent on the significance of data.
History of Big Data
The exact origin of the use of the term “big data” is difficult to establish, however, it is evident that the growth of internet technology has contributed significantly to the growth of big data. In the year, 2012, it was when the growth of big data became evident as people were seeking solution to the limitations in data expansion and usage. Organizations and individuals at the time were searching for effective tools for capturing, processing and dissemination of huge volumes of data leading to the development of the phenomena of relating data sets (Mayer-SchöNberger & Cukier, 2013, p.7). The objective of was to deal with additional increase in information flow.
Opportunities for Big Data to improve insurance
Insurance have the capacity to reduce their expenses in using big data in managing data for its clients. Through customization of services, small insurance companies have the opportunity to use big data of large companies to design packages that suit the needs of different clients of insurance companies (Mayer-SchöNberger & Cukier, 2013, p.11). Small companies can also alter data sets to enable the management asses the situation in the market place prior to designing premiums that reduces wastes. For instance, insurers in small firms will liaise with actuaries from big firm when pricing their policies to facilitate customization of premiums.
Challenges to use Big Data for insurance
It is difficult to validate big data since they are stored in sub sets obtained from correlated sets. The ownership of big data is also unknown and this makes it difficult for organizations to process big data in real time in situations where the source of the data is unverifiable. Subsequently, managing big data requires huge investments and this poses challenge for small organizations that lack the capacity to extract important data from huge volumes of data.
Benefits for insurance to use Big Data
Big data facilitates analyses that help in the identification of the major causes of problems in organizations at early stages thus preventing the possibility of huge damages in future. The real time assessment of data encourages customization of products to suit the needs of different customers. This saves insurers costs incurred in researching the marketplace during calculations for risks (Ohlhorst, 2013, p.21). Consequently, the real-time analysis aids in identification of new opportunities in the marketplace. For instance, small companies can seek customer information using mobile phones thereafter use the data in pricing packages in line with the suggestions of the customers.
Operations needed to get and analyze Big Data from insurance
The use of effective technologies in the collection of data is a critical step in ensuring retrieval of useful data. Proper timing is also necessary to prevent data from spinning. The speed of collection has to secure the back-up systems. The confidentiality of customer’s information is also mandatory (Mayer-SchöNberger & Cukier, 2013, p.5). Consideration of the above factors aids in leveraging data based on variety, velocity, and volume among the other Vs of big data. Operations in data analysis should ensure contextualization of big data from diverse perspective to facilitate integrative sampling in order to enable small organizations use data of large organizations in making deductions.
Recommendation sections
It is advisable for insurance companies to invest in big data in planning their administrative duties to limit wastage of resources that result from the use of inappropriate strategy in meeting the needs of customers. Big data is essential because it unearths opportunities besides encouraging collaborative work in assessing the situation in the marketplace. Users of big data should be caution in their actions to avoid challenges such as security risks and bias in the collection of data. Insurers should also scrutinize the data in details to minimize the possibility of incurring losses from using wrong data in making decisions.
Conclusion
The use of big data is a new phenomenon in the business world, hence the increase in its usage despite some of the data creating problems for users. One of the benefits of big data use that has increased its usage is its efficiency in facilitating analysis. Effective harnessing of big data also reduces wastages, saves on time and enhances effective decision-making. On the contrary, users of big data face challenge in designing effective database management systems for huge volumes of data.
List of references
Mayer-SchöNberger, V., & Cukier, K, 2013, Big data: a revolution that will transform how we
live, work and think. London, Murray.
Mayer-SchöNberger, V., & Cukier, K. 2013, Big data a revolution that will transform how we
live, work, and think. Boston, Houghton Mifflin Harcourt. http://oclc-marc.ebrary.com/Doc?id=10659211.
Ohlhorst, F. 2013, Big data analytics: turning big data into big money. Hoboken, N.J., Wiley.
