Nearing the end of the semester, it is now time for students to reflect on the knowledge obtained in their course(s) and determine the effectiveness of incorporating real-world experience into our academic curriculum.
Students should;
Be able to apply knowledge and theory gained in their courses of study within current workplace or in their future employment.
Be able demonstrate the application of theory to workplace in written form.
If you are enrolled in two course plus INTR your reflection should be a minimum of 400 words.
If you are only taking one course plus INTR your reflection should be a minimum of 200 words.
If you are enrolled in a DSRT course you will need to reflect on how your courses and internship relate to your dissertation topic.
If any outside content or resources are used, proper APA citations and references are required.
Amanullah, M. A., Habeeb, R. A. A., Nasaruddin, F. H., Gani, A., Ahmed, E., Nainar, A. S. M., … & Imran, M. (2020). Deep learning and big data technologies for IoT security. Computer Communications, 151, 495-517.
Petrenko, S. (2018). Big Data Technologies for Monitoring of Computer Security: A Case Study of the Russian Federation (pp. 1-249). Springer International Publishing.
Question 3:
Importance of Advanced Technologies
Sensors:
Sensors played an important role in the development of data streams. IoT is standing well because of the sensors and sensor-oriented applications. The IoT includes smart cities, healthcare, etc. A strong impact is created by the sensors on global computing. Sensors are mainly added to cloud storage services, networks, and database management (Li, 2017).
Computer Networks:
Computer networks are the major bridge between computers, which are interconnected even though they are far away from each other. Information will be shared between the connected computers; this will help in providing storage space for the big data (Li, 2017).
Data Storage:
Data storage is mainly helpful in providing a proper backup for the stored information. This will try to protect the data from malware and viruses by reducing the risk of destroying it. In big data analytics, data storage will play an important role by storing the data and retrieving them whenever it is necessary (Adam, 2015).
Cluster Computing:
Cluster computing is one of the techniques which is of less cost in unconventional for the mainframe computer solutions. Cluster computing will help in increasing the productivity of the organization, which will intern improve the global economies. Cluster computing will mainly help in high-speed local area networks, which is a combination of proper hardware and software. So, in this way, cluster computing will provide a big boost to the big data while accessing it (Li, 2017).
Cloud Computing:
Cloud computing provides different services for computing and also for storage. Some of the technologies that are dependent on cloud computing are database networking, software analytics, and other servers which are working with the support of the internet. The organizations will be very fast in improving their innovation skills with minimum resources by using cloud computing. This will boost the global economy. Different mechanisms are used by cloud computing in order to store and analyze big data (Li, 2017).
Data Analysis Algorithms:
In business organizations, there will be many benefits to data analytics. Different applications like business intelligence, machine learning, and cloud computing are some of the techniques which will provide a great benefit to the organization. The hidden patterns and the marketing trends can be analyzed in order to support the businesses in data analysis algorithms. Different strategies are developed to improve the business and improve the proper change in global computing (Adam, 2015).
References
Adam, K. (2015). Big Data Analysis and Storage. Retrieved from,
https://www.researchgate.net/publication/313400371_Big_Data_Analysis_and_Storage
Li, T. (2017). Analysis of Computer Network Information Based on “Big
Data”. Retrieved from,
https://iopscience.iop.org/article/10.1088/1755-1315/94/1/012195/pdf