To continue to enhance enterprise value, digitization is an indispensable part. Digitization copies the real world into the digital world for analysis and simulation to obtain relevant useful information and then feed back to the real world. The speed of virtual reality of business ideas is rapidly increasing. Therefore, the key to digital is to continually focus on optimizing and improving, however, the key to optimization and improvement is Big Data analysis.
What is “Big Data”?
Big data refers to a collection of data that the scales beyond the capabilities of traditional database software tools in terms of acquisition, storage, management and analysis (TechAmerica Foundation’s Federal Big Data Commission, 2012). It is a high growth and diverse information asset (Gartner IT Glossary,n.d). By the new and efficient mode processing, big data can demonstrate the greater capabilities of decision making, insight and process optimization. In addition, the role of big data is to extract meaningful content from the huge collection of data to create new value, and then collect the results in data form and apply it to specific operations. Fox example, enterprise use big data to analysis for understanding the consumer trend of customer to develop marketing strategies and define products.
The feature of Big data
Volume
The size of the data determines the value and potential information of the data being considered (Domingos and Hulten, 2000). With the development of various portable devices, the Internet and cloud computing and storage technologies, all traces of people and things can be recorded, so the data is mass produced. People is the marker of big data. SMS, social media, photos, videos are all data products. In addition, data enable comes from countless automated sensors, automated recording facilities and inspection equipment. The channels of generating data are also relevant to human activities, such as credit card spending, ATMs. Parking toll collection systems, Internet clicks and various registration processes. Therefore, a large amount of automatically or manually produced data is aggregated to a specific location through the Internet to form a collection of data, including telecommunications carriers, Internet operators, governments, banks and shopping malls (Birney,2012).
Variety
Big data has variety of data types. In the era of big data, data formats have become more diverse. Including text. Audio, pictures, video and analog signals. The sources of data are also increasingly diverse. It is not only in all aspects of the internal operations of the organization but also from outside the organization (Chen et al., 2012, Kwon et al., 2014). A various source of data is the embodiment of big data. For example, big data contain common data from different fields, enterprise can analyse the data to find valuable business information in relevant industries.
Velocity
Velocity refers to the speed of data collection and data analysis. In the business world, the importance of fast has been permeated throughout every aspect of business operations, management and decision making. Velocity is the biggest difference between big data processing technology and traditional data mining technology. In addition, big data is a solution characterized by real-time data processing and real-time results orientation. In other word, the reason why big data has velocity is because the data is depreciated and time-sensitive. Therefore, only the rapid collection and processing of data can reflect the value of the data.
Veracity
The importance of data is the support of enterprise decision making (Diebold, 2012). The size of the data does not determine whether it can help decision making, however, the authenticity of the data is an important factor in the company`s acquisition of ideas. This feature of big data is the most solid foundation for making successful decisions.
The value of Big data
The value of big data is reflected in the following aspects:
- Enterprise is able to use big data for accurate product marketing.
- Small businesses can leverage big data for service transformation.
- Traditional enterprises that must be transformed in the face of Internet pressure can use big data for industrial transformation.
The trends of Big data
Big data resource
Big data will become a limited resource for enterprise to compete for, thus enterprise should develop marketing strategies through big data early.
Combine with the depth of cloud computing
Could computing processing provides flexible and salable infrastructure for big data and is one of the platforms for generating big data.
To sum up, big data has become an important issue for all types of conferences. Most of executives are reluctant to miss this emerging trend. There is no doubt that big data technology will certainly be adopted when enterprise in the future try to analyse existing mass information to drive value-added business.
Reference:
Birney, “The Making of ENCODE: Lessons for Big-Data Projects”, Nature, vol. 489, pp. 49-51, 2012.
F.X. Diebold, A personal perspective on the origin(s) and development of “big data”: The phenomenon, the term, and the discipline (Scholarly Paper No. ID 2202843), Social Science Research Network (2012), Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2202843
Gartner IT Glossary (n.d.). Retrieved from http://www.gartner.com/it-glossary/big-data/.
Chen, R.H.L. Chiang, V.C. Storey Business intelligence and analytics: From big data to big impact, MIS Quarterly, 36 (4) (2012), pp. 1165-1188
TechAmerica Foundation’s Federal Big Data Commission.Demystifying big data, (2012): A practical guide to transforming the business of Government, Retrieved from http://www.techamerica.org/Docs/fileManager.cfm?f=techamerica-bigdatareport-final.pdf
Domingos, G. Hulten, “Mining High-Speed Data Streams”, Proc. Sixth ACM SIGKDD Int’l Conf Knowledge Discovery and Data Mining (KDD ’00), pp. 71-80, 2000.