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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.

Be able to identify the benefits of incorporating real-world experience into an academic program.

Requirement for the Reflection:

Students will reflect on the connection between knowledge concepts for courses they are enrolled for the current semester and how those have been, or could be, applied in the workplace.

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.

Question 2:

Big data describes existing large data that the existing systems cannot process. Daily a large amount of data is generated, constituting big data to overcome the storage issue technologies that store large amounts of data are cooperate (Amanullah et al.,2020). Sensors capture relevant information in a particular task when collecting data from different sources. Sensors are then connected through computer networks that transmit the collected data to the database and share the data stored in the database with other people within the same network or the internet. Data collected from different sources are stored in data storage made of magnetic disk technology to reduce the cost of storing data that could have been backed up manually either in files.

Due to the daily increased data, cluster computer systems with high processing power and large storage space are incorporated to ensure that every network is connected to a local area network equipped with high speed. Cluster computers provide high technological powers to arrange, analyze, respond to claims about data from different uses, and store large data sets (Petrenko, 2018). With time as there is an increase in data sets, cluster computers then fail to rent storage space and are therefore forced to rent space from a cloud computing facility. An organization should not bother investing in equipping a large database; rather, it should upload its files to the cloud. When data anonymously increase frequently, there is a need to invest in data analysis algorithms to automate or sub-automate data to detect their pattern flow and analyze how to cooperate with new technologies.

Reference

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

  
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