Business Information Systems

BUS105 – Business Information Systems

Task1.

Summary of each stage of the data cycle

Data Generation: under this step, essential data is generated so that the usable outcomes can be received by the researcher.

Data Collection: It is defined as the second step under the data cycling in which data is being collected that has been gathered from the reliable and trustworthy resources so that highest possible quality can be ensured in the data collection (Abbasi et al., 2016).

Data Storage: This is the third step of the data cycle in which data is stored after collecting it from the different resources.

Data Visualization: It is the graphical representation of the data in which different visual elements such as charts, graphs, and maps, etc are included. With the help of this, the treads can be understood easily.

Data Analysis: After visualizing the data, it is essential to analyze the data for getting effective outcomes (Sun et al., 2017).

Data Actions: It is the last stage, in which appropriate actions are needed to be taken so that important tasks can be accomplished.

Introduce the business problem

While concerning about this case, it is found that the main issue, in this case, is to investigate the trends in popular names and it is essential to investigate earlier so that enough stock can be bought without the worry of that stock not selling.

Task2.

Write a paragraph on storage options for a large group of files

In respect of the gift shop, it is identified that there are several options that can be adopted by the owner in order to store the data related to its inventory such as mugs, hats, and t-shirts with the popular names in trends (Chang, 2016).

In this manner, cloud storage can be more beneficial for the shop as under this, digital data is stored under logical pools. With the help of this data storage option, the data can be kept available and accessible at any time for the users.

Task3.

Determine the changes in the two visualizations

Name: MARY
YearAmount (Frequency)Position
19459221
195510222
19657338
197519105
198513136
19959180
20054314
20159172

As per this table, the name ‘Mary’ peaked in popularity during the 1950s as it has been positioned at no. 22 in 1955 with 102 occurrences and it lost a lot of its popularity during the 1990’s and 2000s as it was positioned at 180 and 314 in the year 1995 and 2005 respectively.

Name: ISABELLA
YearAmount (Frequency)Position
19553274
19651674
19752448
19851671
19954143
20051007
20151828

On the basis of above table, it is found that the name ‘ISABELLA’ lost its popularity mainly in 1960s and 1980s as it positioned 674 and 671 with 1 occurrence but at the same time, this name gained more popularity during 2000s as this name was positioned at 7 positions with 100 occurrences.

Task4.

Determine the changes in name of boys and girls

1. Name: Joan
YearAmount (Frequency)Position
19455832
195514114
19658206
19751675
19851671
199500
200500
201500

 

2. Name: Joy
YearAmount (Frequency)Position
19451677
195516100
19654323
19752448
198500
199500
200500
20152543

 

3. Name: Beth
YearAmount (Frequency)Position
19455163
19555209
19651674
19756227
19854315
19952466
20053388
20152543

 

4. Name: Judith
YearAmount (Frequency)Position
19451843
19551708
19654255
19759178
19853381
19951712
200500
20152543

 

1. Name: Roslyn
YearAmount (Frequency)Position
19451677
19553464
19652191
19755258
19851671
199500
20051775
20152543

 

2. Name: Veronica
YearAmount (Frequency)Position
19451395
195516100
196515125
197514126
19854315
19954311
20052517
20154327

 

3. Name: Gwenda
YearAmount (Frequency)Position
194510111
19556187
196500
197500
198500
199500
200500
201500

 

4Name: Nancy
YearAmount (Frequency)Position
19451974
19555209
19653377
19754298
19853381
19952466
20051775
20151828

 

Suggest two other analyses

In respect to analyze the data, there are several ways that are available for the businesses so that they can efficiently analyze the data (Paul et al., 2018). In this manner, these two analysis ways are as follows:

  • Qualitative Analysis
  • Quantitative Analysis

Task5.

In concern of more stock, the recommendations should be more effective and these should be related with the business products as the business owner recently purchased the t-shirts so there is need to suggest that what names should go on them (Pearlson et al., 2016). In this manner, some recommendations are as follows:

  1. Gift shop owner needs to use ‘Isabella’ name on the t-shirts that have been purchased.
  2. It can also be suggested to gift shop owner that it should adopt the quantitative data analysis so that it can analyze its numeric data effectively.
  3. The owner needs to collect the data from social media sites so that the customer’s preferences can be identified effectively. It is helpful to identify the demand for mug and t-shirts.

Task6.

Suggest three other sources of customer data

In the manner of the gift shop, there are many options that are generally used to collect the customer data.  By using these sources, the business owner can identify the key preferences of the customers. In this way, three sources are defined below:

Websites: Business websites are a great source of information. In this, with the help of an analytical tool for analyzing what action the visitors takes, business owners can find a better understanding of what kind of products or services are looked by their customers (Bichler et al., 2016).

Social Media: It is the most important tool that is considered as the wealth of answers for the businesses which to understand their customers like people. With the help of this source, businesses can more easily be connected with the customers because it is quite an easy option that can be accessed by any person (Peltier, 2016).

Feedback: It is also an important source of customer data as under this, customers are asked to provide their valuable feedback in regards to the products of the business.

References

Abbasi, A., Sarker, S. and Chiang, R.H., 2016. Big data research in information systems: Toward an inclusive research agenda. Journal of the Association for Information Systems17(2), p.I.

Bichler, M., Frank, U., Avison, D., Malaurent, J., Fettke, P., Hovorka, D., Krämer, J., Schnurr, D., Müller, B., Suhl, L. and Thalheim, B., 2016. Theories in business and information systems engineering. Business & Information Systems Engineering58(4), pp.291-319.

Chang, J.F., 2016. Business process management systems: strategy and implementation. Florida: Auerbach Publications.

Paul, P., Bhuimali, A., Aithal, P.S. and Bhowmick, S., 2018. Business Information Sciences emphasizing Digital Marketing as an emerging field of Business & IT: A Study of Indian Private Universities. IRA International Journal of Management & Social Sciences,(ISSN 2455-2267)10(2), pp.63-73.

Pearlson, K.E., Saunders, C.S. and Galletta, D.F., 2016. Managing and using information systems, binder ready version: a strategic approach. US: John Wiley & Sons.

Peltier, T.R., 2016. Information Security Policies, Procedures, and Standards: guidelines for effective information security management. Florida: Auerbach Publications.

Sun, Z., Strang, K. and Firmin, S., 2017. Business analytics-based enterprise information systems. Journal of Computer Information Systems57(2), pp.169-178.

 

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