Challenges of Big Data Management for Organization and the Possible Solutions
introduction
Having a rapid development in the sector of Internet technology, the demand for data collection in various industries has increased significantly, and the generation of big data arises at the historic moment. Big data can be looked to as the collection of massive data collected through various resources, involving the environment, medical records, sensors, intelligent electronic devices, laboratory research data, and management data (Emmanuel，2016). Big data change people’s way of thinking and have a profound impact on all aspects of organizations. Big data can be used in five fields: global manufacturing, personal life field, retail, medical and government field. Various studies have also found that big data can be conducive towards the development of the global economy as it helps in improving medical and public management (Chen and Zhang, 2014). Because of the importance of big data, it has been widely considered that During this period, the huge amount of data brought the most significant challenges to the scientific field, such as biology, astronomy, and meteorology. due to the increase of data volume, as the calculation often limits scientists
（Chen，Li，2013）.
These challenges mainly include the risk of information and data leakage, the lack of talents, and the lack of innovation ability are also among the risks. This essay demonstrates several typical challenges of big data management in terms of security risks, lack of high-quality talent, and insufficient Innovation technology. Besides, some corresponding measures are suggested, including improving regulation, improving the technical level, and improving independent innovation to help in tackling the problems.
Challenges and solution of Big Data Management
Information leakage risks and security risks can be improved by coming up with regulation and making laws as solutions. In other industries, the risk of data leakage in insurance is high. A large number of sensitive data that is worth is collected and stored in the underwriting area alone. Privacy is another problem that is reflected in the fact that customer groups benefit from sharing data, but some feel uneasy about losing control of their data（Salka, 2015). So, if there’s a data breach, the shortage of security systems is seemingly the only factor to be found. Private parties seek legal redress for damage caused by cyber intrusions and, at the same time, demand for better cybersecurity measures. For instance, different consumers can bring class audition lawsuits as the shareholders bring class auctions on security fraud and derivative suits (Hershkoff andMarcus，2018).
The gap in technical capabilities is a big issue. Business leaders and hiring managers have long believed that they face a shortage of high-quality talent. However, economists often question the lack of skills as the reasons for the slow growth of employment. ( Career Builder and Harris Interactive) conducted a survey of more than 2000 human resource managers and recruitment managers in the United States in 2012, and found that nearly 40% of employers could not find qualified job candidates, and 80% of employers start to get worried about the “emerging skills gap”（ Ferguson，Hitt and Tambe，2013).
Because of the above situation, protecting cloud security gets done by technical experts from different platforms like Google, Amazon, the U.S. National Security Agency, and the Department of defence. Through better procurement policies and technologies, cloud security is improving every minute. Cloud computing makes sense both financially and commercially. For instance, the ability to have an identity management system that helps in the physical access of privileges helps in reducing risks and improving security (Marcus, 2018). As a result, the Security cloud can allow us to move the physical security applications (including its identification, its access control, and primarily video). According to Marcus (2018), the use of cloud has become more effective than the formulation of legal policies, as improvement time has become targeted. Few high-quality talents are another challenge of big data management. I propose improving the employment level of big data majors and strengthening the training of schools and enterprises as effective solutions.
Governments can build some policies or laws that could help protect data privacy and safety. In Canada’s case, private sector privacy is dictated by the Personal Information about the Protection and Electronic Documents Act (P.I.P.E.D.A.). Schedule of P.I.P.E.D.A. lists the ten regulations that must be followed when an organization collects, processes, or discloses personal information. The regulations include a mandate where there is the protection of personal information using the security safeguards that are significant towards the sensitivity of the information needed（ Hoffman,2016). Therefore, it believed that policies and laws are among the most important factors to regulate security networks. For instance, a case where the rules show positive prevention of the data leakages and information on the implementation of different roles is believed to have the factors. But this approach is less effective when it comes to unintentional leaks, for instance, when having inadequate technical capabilities. Besides, laws and policies are a practical process that needs to be perfected through continuous practice. Due to the design of the platform, cloud computing has security.
Different methods have been used to employ graduates’ competitiveness were carrying out college engineering education certification has been one of them. There has been active online recruitment and also a one on one career. The live online recruitment has given a hand in finding out correct positioning in different industries (Falola, 2014). Promote the employment rate corresponding to major and position to above 90%, and form a good talent training mode and base in the field of big data （Zhu and Deng，2020).
There has been a focus on the application of cloud computing technology by Guangdong Open University. Therefore, the university will strengthen the mutual penetration of big data major and related industries, and the high integration of data science and industry-related knowledge. In the process of practice, we should pay attention to the cultivation of talents with a solid foundation, a wide range of knowledge, and good practical ability （Zhu and Deng，2020）. Secondly, a suggestion on schools or enterprises can be conducted by technical training for students or employees.
For example, in 2015, because of the gap between the huge demand for big data talents and education talents, Guangdong Open University added the development plan for applying big data technology to the major of computer application technology. It began to recruit students within the province in the spring of 2016. Next, there was an application for the major of “big data technology and application” in 2018, aiming to cultivate practical and skilled big data talents (Zheng,2019).
Talent is an important factor in the big data field. Progress can be made in terms of talent through the above ways, although the process is a long one. The short-term implementation will be difficult because the learning of technology needs a certain amount of time. So, short term implementations the part that needs to be worked on.
Conclusion
The challenges include short of innovative technology in data management, and they can be dealt with by the proportion of the improvement of the capacity of scientific research and innovation. About 50000 new breast cancer cases are diagnosed in the U.K. each year, and 40-60% of them undergo implantation-based reconstruction. With the progress gotten from science and technology, there is the production of new meshes and implants. The new meshes and implants come into the market after they have obtained certification that doesn’t have any evidence of a randomized trial that is very high, different audits, and long term follow-ups on data. Recognition of the importance of innovation is essential because of the low-cost innovation that is seen to be important in all the regions of the world (Vidya and Green, 2018).
Hence, I recommend that all the industries improve their innovation ability with the help of big data. For instance, we see that the delivery of documents and express services has become a great library innovation service in the big data period (Bakti and Sumaedi, 2013). Besides, when electronic resources cannot meet the needs of some readers, such as disabled readers, these resources can be delivered to these readers by express delivery. With the help of these innovative services, the application of big data in the library is smoother and very efficient (Lu，Dou，and Wang，2017）. Generally, I think innovative technologies or forms can bring benefits and vitality to the application of big data. However, innovation is still an efficient process that requires constant practice and accumulation to find the right solution.
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