Company Analysis: Luminoso Technologies

In an IT-driven environment, the importance of corporate information systems is undeniable. However, for some types of organizations, they are critical, ensuring the seamless functioning of an enterprise. This statement can be applied to the companies working in the IT industry, such as Luminoso Technologies. Moreover, the roles played by them, as well as their application to the particular tasks, define the efficiency and competitiveness of any firm on the market. The following work focuses on the analysis of the role of information systems in the activity of Luminoso, as well as the assessment of the effect of solutions provided by the company on the basis of a case study.

General Information and History

Luminoso Technologies, Inc. is an American company that specializes in the development of software for text analysis. It is providing its clientele with an opportunity to analyze consumer feedbacks and, therefore, maximize their satisfaction and loyalty of customers. The organization takes its roots into 1999, spawning on the basis of the Massachusetts Institute of Technology (MIT) under the Undergraduate Research Opportunities Program (UROP). The project was focused on machine learning, resulting in the creation of the analytical tool. The latter used cloud services and databases to correct and store the data from the Internet, namely the definitions of various words and the relations between verbal constructions. Initially, the goal of the program was the creation of an analytics engine equipped with a graphic interface. However, it eventually evolved into a successful software for text analysis. After the completion of the research in 2010, the MIT Media Labs established Luminoso using the specialists involved in the study and the information obtained in its course (Matheson, 2013).

The Roles of Information Systems

The information systems play a wide array of roles in the activities of Luminoso. This fact is not surprising, considering the company’s focus on analytics based on the artificial intelligence. The most important of them is the provision of the necessary conditions for the development of new products and the improvement of existing ones. As it has been mentioned before, the solutions by Luminoso help other firms to analyze the feedback from consumers. Given the fact that it can be retrieved through various communication channels, including news sites, blogs, online forums, and social media, one can assume that the products of Luminoso have to process a considerable amount of data. As a result, the specialists of the company implement natural language processing (NLP) in the solutions they offer (“Illuminating Your Data with Artificial Intelligence,” 2016). NLP enables computers to read and understand the text. However, the primary difficulty of this process is the fact that, as a rule, artificial intelligence (AI) requires some input to be made in a specialized language. It must be clear and well structured; and all rules must be strictly adhered to. On the other hand, the linguistic structure of the natural language is significantly difficult as it presents many changing parameters on a constant basis. The context for the conversation determines the meaning of a phrase. It means that the particular verbal construction should be understood in a unique way. Additionally, regional dialects, slang, and non-standard phrases may impede the recognition even more. As a result, the AI has to be taught the ways of recognizing and processing text, namely through the use of the so-called big data that can be provided by the systems of Luminoso.

In turn, one of the roles is related to retrieving the information that can be applied in the course of the process of machine learning from such sources as clouds. These ones are the convenient mediums for storing and processing the required data, combining hardware, licensed software, communication channels, and the technical support to users. The work in the cloud is aimed at the reduction of costs and improvement of efficiency of enterprises. Moreover, big data are an integral part of this technology, providing the unprecedented opportunities for both the traditional structured information from databases and business intelligence of social networks, as well as much less structured multimedia data (Bidgoli, 2016). Moreover, given the fact that the company’s products (Luminoso Analytics and Luminoso Compass) also utilize standalone cloud solutions (“Who We Are,” 2016), it is possible to say the following fact. The system also plays a supportive function when it comes to the provision of services.

At the same time, the information systems of Luminoso act as storages. Given the fact that the processes of machine learning and deep analysis often rely on big data, it is possible to point out the following problems stemming from its use. First of all, the volume of data grows on a constant basis. It requires the presence of innovative devices and algorithms to store them efficiently. Without a fast processing, its usefulness is minimal, but the concept of speed is quite relative being different for various types of information. Additionally, such heterogeneity requires different storage formats, as well as increased security. It means that no information should be lost; and an unauthorized access to it is undesirable. Finally, the internal data of the company, including its financial, research, and other records, is also to be stored and managed properly (Bidgoli, 2016). Thus, the organizational role of the system is also not to be underestimated.

Additionally, the information systems provide protection both to the company and its clients. As it has been mentioned before, cloud technologies and corresponding solutions have many advantages. However, during their introduction and implementation, the problem of data safety is not the one to be ignored. The lack of a physical access to servers in the cloud makes security issues even more important. In the case of an emergency it will be impossible to shut the system down to prevent leakage and theft of the sensitive data (Bidgoli, 2016). When it comes to standalone clouds used by such products as Luminoso Analytics and Luminoso Compass, data safety can be ensured with relative ease (“Who We Are,” 2016). However, in public clouds used by the organization, the creation of new client accounts and servers requires only a few minutes of time and a valid credit card. The experience shows that businesses often cannot prevent the situations where their staff becomes involved in machinations through the use of cloud services. As a result, the actual number of servers that stores sensitive corporate data can significantly exceed the quantity that is under the control of responsible specialists (Bidgoli, 2016). Therefore, the protection of private data, including the ones belonging to users of the company’s products, is a necessity for Luminoso.

The Application of Information Systems

The described roles form a basis that allows applying the information systems to them. It is providing the conditions for an efficient solution of problems and challenges encountered by Luminoso. At the same time, the firm does not disclose such information. However, by using the data provided above, as well as relying on the current trends and developments in the IT industry, it is possible to make several assumptions related to the application of information systems in Luminoso.

First of all, when it comes to the management of big data, the enterprise is likely to utilize an approach based on the use of both hardware and software complexes. Such ones provide the pre-configured solutions for processing of such information, namely Aster or Oracle. They are usually supplied as telecommunication cabinets being ready for the installation in already existing data centers and containing a cluster of servers and management software for the massively-parallel processing (Bidgoli, 2016). Given the fact that Luminoso has been formed on the basis of MIT, possessing some of resources of the facility, such course of actions is feasible. Hardware solutions for analytical processing, such as hardware-software complexes by Hana and Exalytics, can also be used in the process of work with big data. It occurs despite the fact that their work is not originally based on a massively-parallel principle; and their RAM host volumes are limited to several terabytes. Moreover, the company may implement the systems based on the traditional relational database management such as Exadata. These are capable of efficiently processing terabytes of the structured information while solving tasks related to the quick search and analysis of massive amounts of structured data (Bidgoli, 2016). In any case, Luminoso has to rely on one of these solutions when it comes to the work with a large volume of information being required for the processes of machine learning and NLP.

As it has been mentioned before, the firm also utilizes standalone clouds to provide services to its customers. Therefore, the application of information systems to maintenance and provision of software is likely to be based on the software-as-a-service (SaaS) approach. In general, this model focuses on the principle of availability of applications that are fully maintained by the provider. The latter one manages them, providing customers with an access to client devices, typically through mobile devices or Web browsers. The primary advantage of the SaaS model for consumer services lies in the costs associated with the installation, upgrade, and support of equipment, as well as the operating software. The primary reasons for that are as follows. First of all, the applications adapted for remote use, with one application being used by multiple clients. The consumers are charged for its use either in a form of a monthly subscription fee or on the basis of the volume of operations. The cost of technical support also is included in payment. Finally, the modernization and updating of the application are carried out promptly and transparently for the clientele (Hemann & Burbary, 2013).

As in all forms of cloud computing, the customers pay not for owning the software per se, but rather for its rent (i.e. the use through a mobile application or web interface). Thus, unlike a classical scheme of software licensing, they have relatively small, periodic expenses. Such ones are being without a need to invest in the acquisition and implementation of the software platform and hardware required for its deployment, and then maintain it in the working conditions. The periodic payment scheme assumes that in the case of temporary absence or unavailability of the product, a customer may suspend its use and freeze payments to a developer. From the perspective of the latter one, some proprietary software distributed under the SaaS model allows combating the counterfeit products with a high degree of efficiency. The reason is that software as such is not transferred to end users. Furthermore, the concept of SaaS often reduces the cost of deployment and implementation of technical and advisory support of the product, although it does not exclude it completely (Hemann & Burbary, 2013). As a result, the goods offered by Luminoso are attractive for a wide range of consumers that are interested in text and intent analysis for marketing purposes.

When it comes to data storage and management, the organization is likely to rely on the solutions that are common in the IT industry, namely the use of the client-server database management systems (DBMS). The DBMS provides the client and server with an opportunity to exchange the minimum necessary amount of information. The latter one carries a main computational burden while the former one can perform the functions of pretreatment before sending information to the server. However, most of its tasks are related to the organization of access to organize the access. In most cases, the client-server DBMS is much less demanding for the computer network bandwidth than the file-server one, especially when running a search operation based on user-specified parameters in the database. In particular, there is no need to transfer the entire data array to the clients as the latter sends the query to the server to conduct a search at the local level. The results, which are typically several orders of magnitude less than the entire volume of the information amount, are returned to the client. It provides a way to display the result to the users (Bidgoli, 2016).

Finally, as it has been mentioned before, data security is of utmost importance for Luminoso, with its products relying on cloud services (“Who We Are,” 2016). Thus, the application of information systems of the firm to this issue is likely to be carried out in the following ways. First of all, there may be separate internal and external confirmations of access rights, which can be accomplished on the basis of personal servers of the enterprise or through the use of specialized business solutions. The employers use their internal passwords to log on the server. Therefore, after a check, they are granted the right of access to the cloud. Therefore, when accessing the external resources they can use their personal domain passwords without a threat to the security of the firm. This option is especially attractive for the Windows environment. The reason is that from the point of view of users, domain passwords are suitable for authorization on cloud servers. However, the external clouds do not have an access to Active Directory. means that they may not be included in the domain. The periodic change of passwords is also much easier (and, in some cases, becomes possible) since internal and external authorization processes are separated (Bidgoli, 2016).

Another method is based on the use of the information system for the monitoring of log data created by cloud servers. These can be an important source of data for the conduct of technical examinations, especially for dynamic cloud servers that do not function in a continuous mode. When a need for such expertise arises, for example, in the case of any attack, this information is often an only hook since the appropriate cloud servers can be decommissioned. Therefore, saving the important log entries (users’ login/logout time, the integrity of the system, and its updates) for the entire lifetime of the cloud server is an important and necessary measure. Only the collection, consolidation and output of data to external storages, for example, a Syslog server, the platform for validating security logs or the security information and event management system, will provide the conditions for its subsequent analysis. The attack on a group of cloud servers can go unnoticed in the case it is performed sporadically. However, after the retrieval of log entries and executing their systematization, one can detect the source of the attack and take the necessary measures (Bidgoli, 2016). Given the efficiency of these two methods, it is possible to assume that Luminoso uses both of them to ensure the security of its private information.

Competition and Consumer Experience

The rapid development of the IT industry, as well as the growing popularity of business solutions it offers, provides for fierce competition in all of its branches, including the ones related to machine learning and analysis of data. In the case of Luminoso, the range of its major competitors includes the enterprises developing and offering products related to deep analytics based on the use of AI. As a result, it is possible to identify such organizations as Sysomos and Crimson Hexagon as the primary competitors of Luminoso. They are both focusing on the intent analysis (Hemann & Burbary, 2013).

Still, even under such conditions, the analytical solutions proposed by Luminoso provide its clients with a better understanding of their customers. ensures the loyalty of the clientele in a long-term perspective and improves the competitiveness. In this regard, it is possible to provide an example of Intel Corporation as a major developer of central processing units that collaborates with such well-known brands as Dell, Samsung, and Microsoft. The problem of the enterprise lies in the fact that it does not contact directly with end consumers of its products. It means that it lacks some understanding of the feelings of the latter one on the technology it uses. In other words, the complaints or words of approval do not reach the company, making it difficult to maintain the competitiveness on the high level. However, Intel still has an opportunity to receive a feedback from its users by utilizing online reviews of its partners’ products that are posted on retail websites. These ones contain the data that ranges from feature descriptions to pain points (Luminoso, 2016). However, it still has to be analyzed to be of any value for the enterprise.

As a result, the Intel’s Consumer Insights and Analytics team has collaborated with Luminoso to transform this information into the insights that can be used to improve the current the new product strategy. Moreover, the firm intended to reveal the drivers of customer sentiments to adjust the performance of its products and discover the new marketing opportunities. By using Luminoso Analytics, Intel has managed to identify the core themes in the intents of consumers including the features of interest, applications, and add-ons, as well as connect them to specific stock keeping units. Moreover, the firm was able to analyze the major product categories to determine the root causes for the reaction of clients and identify trends in the behavior of the latter ones (Luminoso, 2016). As a result, the findings made with the help of Luminoso Analytics have provided the basis for the development of the strategies focused on partner engagement, improvement of products, and marketing campaigns based on customer feedback. has improved the competitive power of the enterprise. Moreover, Intel has started sharing critical insights with its partners, demonstrating the commitment to shared success and contributing to its positive reputation (Luminoso, 2016). Thus, its experience of the use of the products by Luminoso was successful.

Conclusion

The organizations that work in the IT industry heavily rely on the information systems in their everyday work. Therefore, Luminoso is not an exception. With its products and solutions focusing on the application of the AI, deep analysis, and NLP, the presence of the system that can address the problems arising in the course of the firm’s activity is a necessity. The analysis of the enterprise has demonstrated that the information system of Luminoso performs several core functions, including the ones related to security, data storage, software development, and the provision of services. Despite the fact that the firm did not disclose the information on the application, the trends in the IT industry have allowed making certain assumptions on this matter. By taking into account the outcomes of the collaboration of Luminoso with such well-known brands as Intel, it is possible to state the following fact. Its information system is quite efficient as it allows the company to operate in a highly competitive environment while offering high-quality products to its customers.