Skip to content

ITECH7406 Business Intelligence and Data Warehousing Assignment

Individual Analytic Report

Executive Summary

Data is an essential asset which helps in creating the competitive advantages over organization. Data Analytics helps organization develops operational efficiency, drive new income, & increase competitive advantage. In this report, how data analytics provides business to users or organizations has been discussed by choosing the SPSS tool. SPSS is termed as Statistical package for the Social Sciences which are use to solve difficult statistical data analysis. SPSS issued by market researchers, health researchers, marketing organizations, & many more for analysing the data. In this report two types of data analytics can be discussed i.e., predictive & prescriptive, Why SPSS tool in data analytics will be chosen & why it is used & the improvements to the data analytics to user or organization by using SPSS tool has been further discussed in assignment. For improving the business growth of any organization, it needs to collect related information. 

Research Question

How can data analytics provide (business) value to users &/or organisations? 


The report includes the details about the data analytics done in the business. The report includes the detail about the importance of the data analytics to the users & the organisation. The software used in this report for the data analytics is the SPSS solutions. The SPSS solutions are the software package that is used for the interactive statistical analysis that is done in the business or organisation. The current name of the SPSS tool is the IBM SPSS Statics. This tool is used by the large number of the organisation for the statistical analysis in social science. The SPSS statistics focuses on simplifying the programming by including the internal file structure, data processing, data type etc. this tools used by the various researchers in making the statistical analysis of the data. The programs offered by the SPSS tool are statistics programme, modeller programme, visualisation designer & text analytics for survey programs.

Importance of data analytics

Data analytics is important to the business & the users. Data analytics is needed in the business to consumer applications (Devi et. al., 2013). The organisation collects the data from the consumers & then this data is gathered & categorised after this the analysis is done.  The data analytics will help the business to grow. Therefore, it can be said that there is certain factor that can define the importance of data analytics in the business such as:

Analysis of business value chain

The data analytics helps the business to analyse the ways in which the existing information can be used to help the business in finding the way to the success.

Industry knowledge

The data analytics helps the business to gain the knowledge about the industry. In this the business can get the knowledge about the ways they can adopt to succeed in future (Chen et. al., 2012). It also helps to analyse the economy that is avail bale with the business.

Seeing the opportunities

The data analytics helps the business in analysing the data that can help in creating the opportunities for the business. It is said to be the way of unlocking the various options for the business.

It benefits the users as they can get the collected data in the systematic form that can help them in making the decision easily. Therefore, it can have said that the data analytics benefits both the users & the organisations & provides various facilities to them.


Executives of chosen data Set- Predictive & Prescriptive

Predictive analytics

Predictive analytics help to link data to successful action by representation dependable conclusions about current events & situations (Arkkelin, 2014).  This helps in organization to practical in cutting cost, reducing risk & increasing profitability, optimizing their business & driving latest form of business. 

The SPSS predictive analytics software used for:

  • Transform data into predictive approaching to direct frontline choices & interactions.
  • Predict what consumers want & will do further to enhance profitability & retention (Ayhan, et. al., 2013).  
  • Increases efficiency of the individual, process & resources.
  • Identify & avoid threats & frauds before they influence the association.
  • Determine social media effect of the products, services & marketing campaign.
  • Execute statistical analysis as well as regression analysis, cluster analysis & correlation analysis (Agudo-Peregrina, et. al., 2014). 

(Source: IBM, 2019)

Prescriptive analytics

(Source: DSC, 2019)

Prescriptive analysis can used to find out the best solution or results with all choices, given the recognized parameters (Vajjhala, et. al., 2015). When combined the predictive analytics, the prescriptive analytics can recommend result option for how to take benefit of future prospect or moderate upcoming risks. This analytics gives vast value to planners & decision makers .The main reason of the prescriptive analytics is not still widely used in difficult planning processes is that frequently these processes are exceptional to the organization. The accessible SPSS tools that previously offer superior planning together with prescriptive analytics don’t manage well among these business particulars (Keahey, 2013). It improves operations, reduces risk & mange resources efficiently.

Fig: Afghanistan Marital Status for men and women

Why it is used & why it is chosen or laid out in fashion 

SPSS was chosen due to its ubiquity within equally scholarly & business circles, building it the most generally used collection of its type. SPSS is similarly flexible packages that permit a wide variety of kinds of investigation, information change, & types of give up in short; it will further than satisfactorily fill their requirements (Sun, et. al., 2014). SPSS tool is utilized for both subjective & quantitative investigation can be examined by the product along these lines making the specialists work simpler. In this way, why SPSS is significant in information examination can’t be undermined since it has altered the information investigation process.

To condense what they have canvassed in this section, they will advance throughout accompanying strides as you make & execute a SPSS program: 

  • Access SPSS for Windows from PC hard drive or from system (LAN) 
  • Create an information record in SPSS Data Editor or SPSS Syntax Editor 
  • Save information record utilizing suitable document expansion (.SAV or .SPS) 
  • Specify an investigation to be kept running on information document (e.g., Frequencies) 
  • View consequences of an examination in SPSS Viewer Window 
  • Save yield record in this Viewer Window utilizing the SPO document amplification (Schoenherr & Speier‐Pero, 2015). 

Practical Approach

Improve the operations 

The CEO wants to improve the operations, the use of the tool SPSS solutions can help to improve or enhance the sale & operations of the company. The CEO should use the predictive analysis of the tool so that can help in predicting the outcomes, make smarter decisions & getting the better results for the company. The improvement can be made by the company by saving the money through the predictive analysis. Therefore, it can be said that the predictive analysis can help the business in saving the money (Duan & Xiong, 2015). The operation can be improved by avoiding the costly problems that can occur in the operations. This can be done as the SPSS tool can help in predicting the operating characteristics of the business cost effectively & accurately that can help in analysing the factors that can generate the downtime or the benefits to the business. Another through which the operations can be improved by the CEO using this software, as the predictive analysis can impact the profitability & the competitiveness of the organisation. The predictive analysis through this tool can help the business in to turn the vast amount of structured & unstructured data into actionable one. Therefore, through this it can be seen that there are various ways that can be used by the business to improve the operations & increase the sales of the business through the use of the SPSS solution tool.


Through this report it can be concluded that the tool that has been used for the data analytics is the SPSS solutions. It is the best tool as it can help to improve or enhance the sale & operations of the company. Data analytics is important to the business & the users. The data analytics helps the business to analyse the ways in which the existing information can be used to help the business in finding the way to the success. The report includes the details about the data analytics done in the business. The report includes the detail about the importance of the data analytics to the users & the organisation.

  • Agudo-Peregrina, Á. F., Iglesias-Pradas, S., Conde-González, M. Á., & Hernández-García, Á. (2014). Can we predict success from log data in VLEs? Classification of interactions for learning analytics and their relation with performance in VLE-supported F2F and online learning. Computers in human behavior31, 542550. Retrieved from:
  • Arkkelin, D. (2014). Using SPSS to understand research and data analysis. Retrieved from:
  • Ayhan, S., Pesce, J., Comitz, P., Sweet, D., Bliesner, S., & Gerberick, G. (2013, April). Predictive analytics with aviation big data. In 2013 Integrated Communications, Navigation and Surveillance Conference (ICNS) (pp.113). IEEE. Retrieved from:
  • Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS quarterly36(4). Retrieved from:
  • Devi, B., Rao, K., Setty, S., & Rao, M. (2013). Disaster prediction system using IBM SPSS data mining tool. International Journal of Engineering Trends and Technology (IJETT)4, 33523357. Retrieved from: content/uploads/2019/03/Disaster-Prediction-System-Using-IBM-SPSS.pdf
  • Digitalvidya, (2019). About us. [Online] Digitalvidya. Available at: . [Accessed: 17 September 2019].
  • DSC, (2019).Welcome to data science central. [Online] DSC. Available at:[Accessed: 17 September 2019].
  • Duan, L., & Xiong, Y. (2015). Big data analytics and business analytics. Journal of Management Analytics2(1), 1-21. Retrieved from:
  • IBM, (2019).About us. [Online] IBM. Available at: capabilities%2Fentry%2Fpredictive_analytics_with_ibm_spss_basic_q_as&psig=AOvVaw3kjIHcJcM0v5ZMt9I6yyWh&ust=1568809598168726. [Accessed: 17 September 2019].
  • Keahey, T. A. (2013). Using visualization to understand big data. IBM Business Analytics Advanced Visualisation. Retrieved from:
  • Schoenherr, T., & Speier‐Pero, C. (2015). Data science, predictive analytics, and big data in supply chain management: Current state and future potential. Journal of Business Logistics36(1), 120132. Retrieved from:
  • Sun, N., Morris, J. G., Xu, J., Zhu, X., & Xie, M. (2014). iCARE: A framework for big data-based banking customer analytics. IBM Journal of Research and Development58(5/6), 4-1. Retrieved from:
  • Vajjhala, N. R., Strang, K. D., & Sun, Z. (2015, August). Statistical modeling and visualizing open big data using a terrorism case study. In 2015 3rd International Conference on Future Internet of Things and Cloud (pp.489496). IEEE. Retrieved from: