Discuss about the Systems and IT Professional Practice for Data Acquisition.
A SCADA (Supervisory Control and Data Acquisition) system is a system of hardware and software elements installed in industries to manage and supervise their systems (Boyer 2014). This is a system that ensures that the industry or factory can control and manage all parts of the larger system as it is being used (Boyer 2014). For example, a SCADA system installed in oil and gas facility can be configured to use electronic sensors installed in the tanks or storage facilities to control different aspects of the oil and gas facility. For instance, temperature and pressure sensors installed in the tanks send data to the SCADA system where processing takes place. It means that this is a system that has inputs, processing, and outputs. The system also has feedback control system where correction takes place (Boyer 2014).
In the example of the oil and gas SCADA system noted above, the inputs can include temperature readings, pressure gauge data, humidity, and electrical data. All this data is fed into the SCADA system as the inputs for processing. In the processing stages, the temperature and pressure data can be checked whether it exceeds the set limits. The feedback loop provides corrective action after the acquired data has been processed (Boyer 2014). If it temperature data exceeds the limits, it means that there is excessive heating and the feedback loop needs to correct this since it could lead to accidents or incidents. Corrective action by the SCADA system could include increased cooling to lower temperature or vice versa (Boyer 2014). If pressure is high, the feedback loop in the SCADA system can reduce it by transferring some oil to other tanks (Boyer 2014).
The SCADA system has several characteristics. In terms of the inputs, readings from electronic devices are the main inputs. If the SCADA system is installed in the oil and gas factory, inputs may include readings from equipment about, temperature, pressure, tank levels, humidity, wind conditions, and pH levels (Bagri, Richa and Jhaveri 2014). All these inputs are collected by hardware elements or electronic readers and fed into the SCADA software. The SCADA software proceeds with the necessary transformations to ensure that the data can be processed (Bagri, Richa and Jhaveri 2014). For instance, temperature data can be changed to Fahrenheit for processing. Once processing takes place, the outputs can be transformed into formats that are human-readable. The transformations can also involve showing visualizations on the computer screens (Bagri, Richa and Jhaveri 2014).
The boundary for the system is the set limits for the readings. For instance, the set limits for temperature and pressure are already in the system and then it compares these to the readings collected in the field (Bagri, Richa and Jhaveri 2014). Once the system completes the comparisons or analysis, corrective action can be provided and implemented. The environment means that settings or surrounding within which the operation takes place. This is a general surrounding where there are outside elements that can affect operations. For example, exposure of the sensors to bad weather can damage them. In this operating environment, chances of outside influences affecting the SCADA system are minimal. Even for tanks and other assets located outdoors, the sensors are safe since they are located inside the facilities. It means that the environment can rarely affect the system except in cases of natural disasters.
When the SCADA system for oil and gas has completed processing of inputs, it provides outputs used for corrective action (Boyer 2002). For instance, if the temperature is above the set limits, the output of the system is a warning and the new temperature required for the system. For instance, if temperature was at 88F and the recommended is 60F, the system output is an action for cooling temperature until 60F. This is the output to be used in the feedback loop (Boyer 2002). If is communicated to the heating and cooling system so that they reduce temperature to such a level. The feedback affects the operations of the system by increasing or decreasing the readings in the facility as recommended by the system (Boyer 2002). For example, if the pressure inputs suggested that the tank pressure is too high, the feedback affects the operations since the SCADA outputs reduce the temperature. The feedback may also affect operations by stopping or starting some operations. For instance, if SCADA system notes a high temperature, it can affect operations by halting all transfer or processing operations for oil and gas products. Workers may be required to stop operations until the pressure and temperature are returned to the required levels. In such a case, the effect on the operations could be positive or negative. For instance, if temperature was too high and operations are halted, it can negatively affect operations. If the readings are good and SCADA system recommends operations to continue, this is a positive impact since it upholds safety in the facility (Boyer 2002).
One of the major advantages that can flow into the firm because of outsourcing its information systems is a reduction in costs. Outsourcing ensures that the firm reduces its costs of running an information system (Gonzalez, Jose and Llopis 2010). The firms that offer outsourced information systems are able to run the systems at a lower cost compared to the client. Since it is there core business, they can lower costs by developing such systems in-house instead of buying the systems. They can also lower their totals costs by offering such a system to many companies. It means that the firm can pay less for the outsourced system compared to buying and installing the system. The costs are also lowered because of reduced maintenance and support needs. Costs are also lowered because of reduced hiring and training costs (Gonzalez, Jose and Llopis 2010). This is an advantage since it lowers the overall expenses of the firm and this can increase profitability.
The other advantage is due to increased efficiency and effectiveness of the system. Since the outsourcing firms are experts in developing and running the information systems, they have expert knowledge and skills with such systems (Gonzalez, Jose and Llopis 2010). It means that they can make such systems work well and increase productivity. The experts in the outsourcing firms have better experience and skills meaning that they can fix errors and problems quickly leading to increased effectiveness of the system. The third advantage of outsourcing is increased productivity for the firm. Outsourcing IT systems allows the firm to concentrate on their core/main business instead of spending more time on dealing with IT issues. For instance, if the firm manufactures cosmetics, outsourcing IT systems allows the firm to concentrate on the core business of selling more products to collect more revenue (Gonzalez, Jose and Llopis 2010). If the firm doesn’t outsource, employees could waste a lot of time fixing IT issues instead of selling more products. By focusing on the main business, the workers in the firm can remain more focused on the right tasks leading to better productivity (Gonzalez, Jose and Llopis 2010).
One main disadvantage of outsourcing is lack of control over the information system. When a firm outsources the information system, the responsibility for implementing the system is in the hands of the outsourcing firm (Gonzalez, Jose and Llopis 2010). If such a firm fails to act professionally, issues of lateness, inaccuracy, and poor quality could result. It means that since the IT system is in the hands of the other firm, the client could face problems because they do not have direct control of the system. Lack of control can mean inability to meet strict deadlines and other customer requirements. The second disadvantage of outsourcing is knowledge management (Gonzalez, Jose and Llopis 2010). Once the system has been outsourced, all the work is completed by the service provider. It means that internal workers will gain little knowledge of the system. Where this is the case, it means that workers do not understand the system well. If the outsourcing agreement is cancelled, returning to an internally implemented system could be very difficult since workers know little of the system. It means that a change of the strategy to implement the system internally could negatively affect the business. Since workers have little knowledge, the transition could negatively impact the transition leading to negative outcomes. The third disadvantage of outsourcing is because of the risk of exposing confidential data (Gonzalez, Jose and Llopis 2010). For instance, if the organization outsources the human resource and finance systems, there is confidential data that is put at risk. In terms of finance, data about sales, revenues, and profitability can be exposed to third-parties. Human resource data such as salaries, wages, and other important elements of employee contracts can be exposed. If such data is misused by the service provider, it can affect the firm negatively.
One information system that can be outsourced by this firm is the accounting and finance information system. In the firm, there are thousands of transactions that our every hour meaning that the information system handles many transactions (Tayauova 2012). The information system handles a lot of data and it takes many employees to run and man this function. For instance, there has to be data entry employees to enter data about offline transactions. IT exerts have to be employed to develop, implement, and maintain the system (Tayauova 2012). It means that there is a dedicated team of workers needed to ensure that the information system is operational. Outsourcing is justifiable to reduce the size of the operation. It is important to reduce the size of the team and the number of activities taking place in this system. If the current situation continues, the size of the operation may become larger as the firm grows. Such an outcome may increase expenses and complexity in running the system. As the operation grows errors, omissions, and other mistakes can increase (Tayauova 2012). This may call for more training and education of workers and this only increases costs. Therefore, it is justifiable to outsource this information system to an expert or firm with the required knowledge and experience in this area. It is justifiable since reducing errors and keeping the operation small can increase productivity (Tayauova 2012).
Analytics is a relatively new branch of computer science that deals with generating useful insights or trends from a collection or set of data (Runkler 2016). Learning analytics means that the students may be required to learn all the processes, tools, and concepts that involve gathering data sets and extracting useful insight from data (Cushing and Campbell 2015). Learning analytics could greatly benefit students especially because of improved decision making abilities or approaches (Gandomi and Haider 2015). After learning analytics, the students can learn that they need to use data to make decisions. Instead of making decisions based on unfounded assumptions, students learn that they need to consider available data and analyse it to make decisions (Hwang and Chen 2017). The benefits will accrue to students since they will gain additional skills after leaning analytics. These skills are very useful when they join careers. Since today’s firms generate a lot of data, students gain immensely from this knowledge. The students who start small businesses in future also gain from this knowledge since they will now start to use the science to make smart decisions. The benefits would accrue to the students since they understand the concepts and tools used in analytics (Geng 2017). The benefits also accrue to students since they learn the gain some experience in analytics. They can build on this knowledge and use it as a starting point once they graduate (Rahm 2016).
There are several advantages that could arise in a university after learning analytics. First, the decision-making approach can be improved and errors & inaccuracies can be eliminated since analytics uses data in decision-making (Guller 2011). It is also advantageous since it improves knowledge in the university and skills as well as experiences. Another benefit of learning analytics is that it allows the university to make use of data that lies within their systems. From learning analytics, many benefits could accrue to the students. If the entire institution learns analytics, the students gain since they now learn a new branch of computer science that they can apply after graduation (Kambatla and Kolias 2014). The benefits accrue to students since they have the opportunity to learn the tools, practices, and approaches used in analytics (LaValle, et al. 2013). These can be learnt in class or through interaction with people using analytics in the university. Publications such as books, journals, and internet articles published in the university can also benefit students so that they can learn more about analytics. Conferences and talks about the topic can also benefit students and prepare them well to use analytics in future.
While learning analytics is important and advantageous for students, there are several negative outcomes that can result. Since this is a complex area of computer science, the students can suffer from increased complexity and lack of comprehension (Guller 2011). Students can also start to complicate decisions by using data and spend more time indulging in analytics. It could also arouse some negative behaviors such as stealing data and unauthorized access to practice analytics. From the discussion of analytics, it appears an interesting yet complex discipline in computer science (Guller 2011). If students are not ready for this subject, they can fail to comprehend it if it is too complex for them. It means that students can take an increasing amount of time to learn analytics. It means that they can spend time dedicated for other subjects just to learn analytics (Nagaraj and Duggirala 2015). The complexity can also arouse the interest of students and make them spend more time on it reading and experimenting. Since the university has a lot of data stored in the information systems, students with increasing knowledge of analytics can attempt to gain access to data for experimentation. There is also a disadvantage that students who learn analytics and use data to make decision can overcomplicate decisions. It means that students may fail to understand the situations that require analytics and those that do not. The negative behaviors such as stealing data and unauthorized access could change or multiply in future leading to more serious information security offences.
Today, many institutions are involved in the collection and analysis of student-related data. I think this is ethical. When institutions collect and analyze student data, they can use the insights developed to improve services within the institution. Normally, when the data is collected, various elements are gathered. For instance, the data can include names, email addresses, postal address, physical address, age, gender, culture, subjects, grades, club affiliations, and co-curricular activities (Nagaraj and Duggirala 2015). There are many elements of student data that can be collected by the institution for various reasons. The collection of this data is ethical since the institution needs to have the details about the students that they admit. Institutions have a legal right to collect data about students and store it as details of the students attending college.
The analysis of this data is also ethical since it can allow the institution make better decisions. For instance, the institution can analyze performance data to understand the students who fit in leadership positions or serve other purposes (Guller 2011). As seen in the previous sections, analytics helps one make informed decisions from data collected. Analytics helps one develop trends and insights that are helpful in making decisions. It means that the student-relating data can be ethically used to make good decisions that can help students and the institution (Wong 2016). If the data and insights gathered from it are used for the right reasons, then the collection and analysis of such data is ethical. It would be more difficult to run an institution without the necessary data.
Once such data is collected by the institution, it should be stored in a strong and secure system where it cannot be compromised by attackers. As noted in the above sections, some negative behaviors can result from the use of analytics. Stealing data, manipulation, and illegal access can result in extreme circumstances (Qiu and Antonik 2017). It means that the institution needs to guard against these issues to ensure that the data is collected and analyzed in the correct manner. If this is done, the collection and analysis of student data is both ethical and beneficial to the institution.
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