Implementing a new information system in a large organization poses challenges that should necessarily be met before the system’s installation can be called successful. First of all, among many different options, a businessperson must find the system that would suit his or her company in terms of its working capacity, the availability of the needed services, and the costs the organization will have to incur when installing and maintaining this system. Unless a businessperson has exertional IT skills, he or she will have to find an IT company that will be able to install the option needed as well as maintain it through its life cycle.
Secondly, the installation of a new information system may face resistance on the part of employees, who are used to a particular method of work and are averse to changes. The older generation may be fearful that the system will ultimately rob them of their workplaces, while younger people may dislike the particular variant chosen. So, a businessperson faces the challenge of persuading the staff to embrace changes wholeheartedly and transfer smoothly to a new system. The difficulties and costs of organizing training courses for the staff will have to be considered.
Lastly, the system will have to be tested before it can be fully implemented in the work of the company. Testing may present challenges since it may be time-consuming and keep the staff from using the system’s full potential. The desire to use a new system and the consideration of the money paid may blind the businessperson to its obvious drawbacks, and instead of trying to fix some issues, he or she may urge the staff to use the system in its unattuned version.
The generic systems development approach that considers the Systems Development Life Cycle should be used to meet the challenges effectively. Breaking the implementation of the new system into several stages allows for addressing each challenge effectively at its level. Thus, costs and time considerations should be addressed at the planning stage so that no additional costs and time expenses creep into the project. Determining the necessary functions, capacity, and characteristics of a new system will have to be considered at the feasibility or requirements of the analysis and design, and prototyping stages. At the stage of implementation and integration, training courses will have to be provided for the staff to fight the possible opposition to a new system.
Cloud services, or “clouds,” are a network of powerful computer servers that allow customers to use their resources over the Internet: store files and share them and do calculations.
In a narrow sense, cloud services are online programs that help to organize remote work and solve business problems. Clouds can be considered a utility as they allow employees to get access to a shared database from anywhere in the world and manage projects. Each employee sees the result in real time, can make comments, edit and perform personal or joint tasks. An example of a cloud service is Google Docs.
Nowadays, more and more organizations adopt a data-driven approach in their strategies. However, this approach poses some challenges for the organizations involved. First of all, not all the data are accurate. While it is sometimes easier for an organization to use data from outside sources instead of collecting its data, it should be remembered that these data may not be updated in time and thus should be verified. Secondly, the use of big data may create confusion since employees sometimes feel lost and overwhelmed by the number of digital data they have access to. The challenge is to filter them and single out those necessary to perform the given tasks. Indeed, employees run the risk of falling into the trap of their bias as they may use data from the sources they like and disregard those that run counter to their vision. Such an approach will ultimately lead to the adoption of decisions that may be harmful to business. Finally, without proper structuring, data will present a maze of unrelated numbers useless for the organization. The challenge of structuring data and drawing correlations between different sets should be met at all levels of the organization.
The first example of big data usage in business is the collection of data related to age, hobbies, income, and preferences of customers by large consumer networks. Based on these data, they create personalized ads sent via emails or applications to attract customers to the goods sold. The second example is the use of big data analytics which allows managers to make the right decision for the company and mitigate the risks the organization faces.
Before conducting digital surveillance, Russel needs to consider what kind of information he wants to get as the choice of surveillance tools will depend on it. Once this is determined, Russel will have to determine whether he needs the analysis of the information he receives from newer IoT technologies and analytics software or if he can draw inferences himself. There are video analytics systems that can notify him of suspicious activities and motions within the organization. Finally, to determine whether his agents send some information to a rival bank, Russel should consider using tracking applications that disclose what kind of information has been sent.
Phishing can be described as a type of internet fraud used to obtain user identification data. It is used to steal passwords, card numbers, bank accounts, and other confidential information. As a rule, a phishing attack starts from fake websites that imitate the Internet pages of popular companies: social networks, online stores, and streaming services. Hackers expect that the user will not notice the forgery and will indicate personal data on the page: card details, log-in and password, and phone number. If a person does this, the scammers will get his or her data.
Denial of Service attacks can be described as network congestion with parasitic traffic when a large number of fake requests are sent to the attacked resource, which completely “clogs” all server channels or the entire bandwidth of the input router. At the same time, it becomes impossible to transfer legitimate traffic to the server. There may be so many requests that the server does not have time to process them and goes into “denial of service” mode. An example of a Dos attack was the fall of electronic postal services in Estonia in 2007 when the system was stalled for several days due to a large number of fake requests. The difficulties enforcement agencies experience in stopping computer crime stem from the fact that these crimes are anonymous and can be committed from any part of the globe. The high level of anonymity on the Internet provides modern hackers with great opportunities for cyber attacks, and the tense relations between countries make such criminals practically inaccessible to the authorities, making it difficult to investigate these crimes.