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Business Analytics in Software and Information Technology Industry Report

Industry Description: Software and IT as the Current Area of Continuous Innovation

The technological breakthrough that has been taking place on the global scale over the past few decades is worth paying closer attention to as one of the most prolific and promising areas for business development. The specified realm incorporates the concept of communication, the active use of innovative technology and the idea of innovation as a business tool, in general, and the active promotion of business connections across the globe (Adhikari, Morris, & Pan, 2017). The Software and IT Industry (SITI) has experienced a massive development recently and is still evolving, taking new shapes with every discovery in the IT environment. Because of the continuous progress that can be witnessed in the specified domain, it can be defined as worthy of further exploration as the area where significant changes are bound to occur.

The recent trends in the selected area show that the SITI has been experiencing rapid growth. Particularly, the levels of spending on the identified industry have been on the rise since 2010 and are expected to approximate $424 billion in 2019 (“Information technology (IT) spending on enterprise software worldwide, from 2009 to 2019 (in billion U.S. dollars),” 2018). Furthermore, the rising demand for software tools as the means of exploring new opportunities in business, communication, and other domains have led to a significant increase in stock prices within the industry (Adhikari et al., 2017). Therefore, the consistent growth that can be observed in the SITI implies that the industry is going to leave a memorable mark on the global business environment.

Using Business Analytics in the Software and IT Industry: Data Security, Big Data, and Cybercrime

To ensure that the development of the SITI should be uninhibited and fast, one should study the existing opportunities to remove key barriers on its way to progress. A closer look at the subject matter will pin to the issue of data safety as one of the primary reasons for concern in the context of the SITI (Reilly & Jorgensen, 2016).

In addition, the necessity to use the Big Data as the means of obtaining crucial information about changes in demand and consumer behavior, as well as cater to the needs of an increasingly diverse population, should be regarded as one of the essential trends in the SITI. Thus, one will have to apply Business Analysis as the method of improving the performance of the companies operating in the specified setting. The adoption of the business analytical tools will help forecast major changes in the industry, as well as determine the slightest alterations in buyers’ behaviors.

Finally, one must give Business Analytics credit for being an important tool in determining the possibility of a cyberattack and information leaks. The specified issues can be regarded as the primary problems circulating in the realm of SITI. The adoption of Business Analytics tools in turn, while giving a chance to determine primary trends in the specified environment, cannot be deemed as the means of safeguarding the industry form cybercrime entirely. Therefore, more elaborate strategies for business analysis should be introduced into the environment of SITI (Adhikari et al., 2017). Particularly, embracing an array of external factors such as the emergence of new malware, as well as a detailed analysis of internal ones, such as problems in the existing data management design, will have to be viewed as a necessity.

Nevertheless, the adoption of Business Analytics as the method of exploring key business trends in the SIS market performs its function rather well. For instance, opportunities for receiving and processing customer feedback are extended significantly. In addition, the identification of customer-specific needs and, therefore, the design of an intricate marketing satiety becomes a possibility with the active use of the contemporary Business Analytics tools (Adhikari et al., 2017).

Business Analytics Techniques in the Software and IT Industry: Data Science and SAS

At present, the propensity toward using Big Data as the source of corporate decisions can be identified in the SITI industry (Shmueli, Bruce, Yahav, Patel, & Lichtendahl, 2017). The specified trend is linked directly to the concept of the Data Science, which is defined as the endeavor at determining algorithms for data retrieval and its further processing (Shmueli et al., 2017). The concept of data mining has recently emerged in the realm of data science, implying that specific patterns and trends can be identified when analyzing data sets, in general, and the Big Data, in particular (Shmueli et al., 2017). Consequently, the current data science processes are rooted in the assumption that, by arranging information in clusters and subjecting it to a thorough analysis, one may encourage the active data learning (Shmueli et al., 2017). In other words, the consistent data analysis will lead to the emergence of smart technologies that will inform the design of customer-based marketing strategies, production processes, etc., based on the outcomes of the data analysis process. Forecasting customer behavior and detecting market trends at the earliest stages of their development, therefore, are seen as the essential tools in reinforcing the position of SITI organizations in the modern business environment.

The business analysis techniques deployed in the SITI context are similar to the ones that are used in any other environment, yet they need to be especially precise and aimed at determining the opportunities for improving the existing services, designing intelligent application, introducing interactive tools, etc. Therefore, the adoption of the techniques that encourage the active machine learning and the creation of smart applications can be regarded as the primary trends. The changes described above are not only necessary but also inevitable in the environment that can be described as increasingly diverse. Catering to the needs of the representatives of all cultures is imperative, yet identifying every unique property of the said cultures is barely a possibility without smart applications. Implying the unceasing interaction with users, smart business analytics tools gather the data that will be used to model the existing techniques for product design, marketing, and communication.

Dominant Players in the Business Analytics Landscape: From Excel to SAS to Online Tools

Although the realm of the business analysis is a comparatively new area, it has already been filled with an array of devices that lead to an extraordinarily fast and rather efficient processing of the available information. At present, most analytical tools that are represented in the market provide an opportunity to determine the effects of specific variables on the one of interest for target organizations (Yin & Kaynak, 2015). Although most of the market is dominated by the tools that have been created by well-established companies, innovative solutions may finally oust the current champions from the market.

For instance, the companies such as Microsoft became the face of the Business Analytics quite a while ago, yet are still persistent in their endeavor at being at the helm of the target market. The Excel software, although providing rather basic options for an in-depth analysis of selected variables, remains one of the unsurpassed devices for comparing crucial business variables. The SAS software, in turn, offers extensive opportunities for determining key variables and assessing their effects on a particular organization. Consequently, detailed information about the means of retaining the competitive advantage of a selected organization in the setting of the global market can be obtained.

It is remarkable, however, that, even with the advanced opportunities for a business analysis that the specified tools provide, they still do not offer a complete evaluation of the key issues that modern SITI organizations face in the environment of the global market. Particularly, the threat of cybersecurity breach and the following loss of corporate data, as well as a threat to the personal data of customers, still makes SITI companies extraordinarily vulnerable to external threats. Therefore, further improvements must be made to the set of tools used in Business Analytics to ensure safe and secure environment for companies belonging to SITI.

Business Analytics: Three key Players and Their Role in the Contemporary Business Analytics industry


Perhaps, being the most common software for an extensive data analysis, Excel remains the foundational software for determining key trends in a particular industry organization, locating primary tendencies, and providing forecasts. When considering the disadvantage of the specified tool, one must admit that, having been designed quite a while ago, the software may have worn out its welcome as the means of analyzing the consistently changing data. With the introduction of Google Sheets, opportunities for interactive analysis and the observation of changes occurring within the specified environment, the identified software requires auxiliary tools for the supervision of all changes and the identification of essential factors that affect the SITI environment.


SAS is a more recent addition to the existing list of analytical tools that can be used to explore opportunities in market research and the development of a sustainable competitive advantage in the SITI environment. It should be noted, however, that the application of SAS implies addressing a rather narrow set of goals. Particularly, the device allows primarily for a comparison between the existing options and the location of tendencies in a specific environment. Although the said steps are also crucial for the successful management of corporate needs in the realm of the global economy, they are not enough for a SITI organization to succeed. Therefore, the tools such as Plutora Release Manager, which provide tools for not only detecting specific trends but also planning and arrangement of the available resources will have to be utilized (“Plutora Release Management Software features,” 2017).

The specified devices should be given credit for the options for bridging the gap between business and the IT environment. Their adoption is necessitated by the need to coordinate the R&D processes conducted in the SITI realm with the promotion strategies used to build a competitive advantage. In contrast to the SAS tools, which typically offer massive opportunities for a business analysis yet do not provide the foundation for planning, the identified devices serve as the means of planning further steps in the SITI market and building a sustainable marketing approach.


Finally, one needs to address the options that Tableau as a Business Analytics tool provides as the possible source of analytical techniques that can be adopted in the SIS environment. The identified software can be utilized for tracking down and reporting the alterations that occur in the context of the SITI environment. Although the specified step might seem as barely necessary, it, in fact, supplies the data that can be used to identify dents in the current strategy for preventing data leaks and addressing cybersecurity issues. Given the increasing threat of malware and cybercrime, it is essential to locate the loopholes in SITI companies’ security and address these dents in the firms’ safety strategy as efficiently as possible. A reporting tool, in turn, will shed light on even minor concerns, thus, leading to a steep rise in the security levels within the industry.

Major Trends and Forces Shaping the Software and IT Industry: Advanced Machine Learning

Although the issue of cyberattacks remains a massive problem for the contemporary SITI environment, it is not the only trend that can be identified in the given area. Positive tendencies are also noticeable and worth paying closer attention to; for example, the propensity toward more efficient data management deserve to be mentioned. In the ever-changing realm of the global economy, the mere input of essential data is not enough to ensure the successful processing and the further provision of reliable information, particularly, regarding industry forecasts. Instead, one should consider creating the tools that allow building a system of knowledge. Put differently, the focus on machine learning as one of the most prolific areas and the most intriguing prospects in the context of the SITI must be addressed (Pillay, Qu, Srinivasan, Hammer, & Sorensen, 2018).

The concept of the machine learning is currently affecting the SITI to a considerable degree since it creates the platform for customizing users’ experiences and locating the solutions that will meet the needs of all customers base on their background and unique characteristics (Chen & Asch, 2017). The specified process is linked directly to the use and management of the BIG Data. Defined by Volume, Velocity, and Variety, the Big Data provides a vast range of information about target populations’ preferences, thus, allowing organizations to build a comprehensive model for catering to the needs of the target demographics. The use of machine learning, in turn, will help make the analysis of the big Data more intricate and careful; thus, the information obtained from the choices made by buyers will inform organizations in the SITI context about the changes that they will have to make to their products.

Other Issues Worth Discussing: Cybersecurity as the Area for Concern

One must also keep in mind that the contemporary area of SITI is filled with numerous challenges associated with the issue of cybersecurity. Being a growing industry, SITI contains an increasingly large number of threats to the safety of its users’ personal and corporate data due to the presence of numerous tools for illegal information retrieval (Adhikari et al., 2017). Malware designed to steal the personal information of the Internet users is becoming increasingly more intricate and difficult to detect, which means that the specified area requires close scrutiny (Adhikari et al., 2017).

The problem is complicated severely by the fact that the adoption of cybersecurity tools and software is unlikely to have any effect of required magnitude unless changes in people’s behavior are observed in the specified domain. Because of the lack of awareness among users and the failure to enhance security-based behaviors in the identified domain, the propensity toward failing to detect malware remains a disturbing trend (Adhikari et al., 2017). Therefore, it is imperative to encourage employees in the specified companies to alter their behaviors in the environment of the SITI (Adhikari et al., 2017).

Furthermore, a heavy emphasis must be placed on the issue of R&D. the specified area must be funded extensively to ensure the development of new tools for enhancing the security of data and its careful analysis. Restructuring the budget may be viewed as a necessity to keep in pace with the challenges to which the SITI exposes its agents. The specified step includes designing the software that meets the demands of particular organization. For instance, the tools for carrying out an analysis of marketing opportunities for a SITI organization within the context of a new market should be created. In addition, the devices that allow for a multifactor analysis and the provision of a careful assessment of emergent opportunities and threats will have to be deemed as a necessity. Inventory optimization must also be regarded as an important step toward enhancing the overall efficacy of a firm operating in the setting of the SITI (Adhikari et al., 2017). Thus, a company will be able to cater to the needs of a diverse population and prevent the instances of data loss.

Conclusion and Recommendations: Business Analytics in the Software and IT Industry

The adoption of Business Analytics tools must be regarded as a necessity of any company operating in the global market. However, the specified step is especially important for the companies that work in the realm of the SITI, which is experiencing drastic changes at present. It is important to ensure that the latest trends are identified and taken into account when developing tools for enhancing the competitive advantage of organizations. However, the issue of data security and its efficient management are, perhaps, the most essential issues that organizations in the SITI context will have to focus on when considering their current choice of business strategies. Because of the increasingly fast pace of technological development and the necessity to use the BIG Data for modelling customer-based strategies, companies must secure their data. Otherwise, organizations in the SITI realm may face the danger of leaving the information of their customers exposed. Thus, devices for enhancing information management strategies and especially information security must be deemed as the primary focus of contemporary SITI firms.

In addition, the need to cater to the demands of an increasingly diverse population have to be brought up as the areas that modern SITI organizations must address with the help of Business Analytics tools. Although the current devices, especially the time-tested tools such as SAS, provide large opportunities for determining key tendencies in the market and testing the available solutions, one must also mention the importance of combining them with the devices that allow locating the tools for selecting the optimum strategies in other realms of a business’s functioning. For instance, it is crucial to build a link between the current information management issues and the choice of an appropriate R&D strategy, the proper marketing device, and the appropriate means of carrying out a financial analysis. Giving vast opportunities for receiving the data that will shape the specified decisions, the use of traditional and innovative Business Analytics tools will have to be deemed as a necessity.


Chen, J. H., & Asch, S. M. (2017). Machine learning and prediction in medicine-beyond the peak of inflated expectations. The New England Journal of Medicine, 76(26), 2507-2509.

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Pillay, N., Qu, R., Srinivasan, D., Hammer, B., & Sorensen, K. (2018). Automated design of machine learning and search algorithms [guest editorial]. IEEE Computational Intelligence Magazine, 13(2), 16-17.

Plutora Release Management Software features. (2017). Web.

Reilly, G., & Jorgensen, J. (2016, January). Classification considerations for cyber safety and security in the smart ship era. In Proceedings from the International smart ships technology conference (pp. 26-27). New York, NY: ISSTC.

Shmueli, G., Bruce, P. C., Yahav, I., Patel, N. R., & Lichtendahl Jr, K. C. (2017). Data mining for business analytics: Concepts, techniques, and applications in R. New York, NY: John Wiley & Sons.

Yin, S., & Kaynak, O. (2015). Big data for modern industry: challenges and trends [point of view. Proceedings of the IEEE, 103(2), 143-146.

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