Database, Big Data and Business Intelligence
Database is the technology that holds all the information that any ICT system runs on. The database allows the system to store, retrieve, modify and delete data from it (Trumpy et al. 2015). The big data refers to a very large scale database that is used for revealing patters, conducting analysis and understand trends, especially associated with human behaviors. The information system can be referred to the organized technology that is used by the enterprises for making most use of the information (George, Kumar and Kumar 2015).
The study includes the detailed information of the database, big data and business intelligence. In addition to that, the role of the information system in decision making regarding various organizations has been covered within the study. As the cyber crimes are increasing each year, it is essential to protect the systems. This study covers some aspects of technical security against the cyber attacks.
2.1 Database, Big Data and Business Intelligence:
Database: The database is an organized set of information for allowing the access, manage and update of information (Teixeira et al. 2013). The database allows the developers to store the data into virtualized table that has rows and columns. The columns hold the same type of data and the rows hold the data that refers to one particular entity. Computer databases stores the aggregation of data records. The database has a unique characteristic called ACID property. It allows the database to maintain the integrity and consistency of data. The database also provides the ability to data read/write (Monteiro et al. 2016). The database is so scalable that it can be found in the large mainframe computers as well as small computers.
The evolution of database imitated at 1960. In that year, the network and hierarchal databases were designed and developed. The object oriented database came along in the 1980s. At present, the advanced SQL, NoSQL and cloud databases are into use. There are four types of databases that the organizations make use of such as relational, distributed, cloud database and NoSQL database. The relational database defines the data in such a way that the data can be accessed and recognized through different methods (Rawlings et al. 2014). This database is also called tabular database. Distributed database is developed on the concept of storing the database in different physical locations. In this kind of database, the data processes are replicated in different network points. The cloud database is a virtualized database that is scalable enough to be adjusted as per the user requirements (Teixeira et al. 2013). The data in cloud can be stored in hybrid, private and public cloud. NoSQL is only useful for the large amount of distributed data. The other two databases are NoSQL and object oriented.
Big Data: Big Data is a technology that refers to the structured and unstructured data that overwhelms a business regularly. The significance of big data usage in an enterprise does not depend on the amount of data rather it depends on the purpose of using those data (Swan 2013). The analysis on the bog data can be conducted regarding the enhancement of strategic business move and better decision making. The volume, velocity and variety are three parts of the big data. The volume refers to the amount of data to be stored. The organizations gather data from the various sources like machine-to-machine process, human commuter interaction, social media, input device and many more.
Findings and Analysis
All the information collected from these various stores refers to a massive amount of data (Provost and Fawcett 2013). New technology such as Hadoop has made easy for the enterprise’s to store this kind of huge data with ease. Velocity refers to information streams in at an exceptional speed and should be managed in an auspicious way. RFID labels, sensors and keen metering are driving the need to manage downpours of information in close continuous (Swan 2013). Variety refers that information comes in a wide range of arrangement from organized, numeric information in conventional databases to unstructured content archives, email, video, sound, stock ticker information and monetary exchanges.
One of the basic characteristics of Big Data is the massive amount of data represented by diverse and heterogeneous dimensionalities. The cause of these dimensionalities is the various data receivers make use different schema regarding collecting data and applications of different natures results in different representations of data (Wu et al. 2014). Self-ruling information sources with conveyed and decentralized controls are a primary normal for Big Data applications. Being self-ruling, every information sources can produce and gather data without including any unified control. This is like the World Wide Web setting where each web server gives a specific measure of data and every server can completely function 5 without fundamentally depending on different servers. Then again, the colossal volumes of the information additionally make an application defenseless against assaults or breakdowns, if the entire framework needs to depend on any brought together control unit (Swan 2013).
Business Intelligence: The business intelligence refers to a technology-driven method regarding the analysis of data and providing exploitable information for assisting the corporate employees. In addition to that, the business intelligence provides the opportunity of making more stable business decisions (Trumpy et al. 2013). A broad range of application, tools and mythologi es. The healthcare centre, mentioned in the case study below, has been using the business intelligence since the implementation of MIS and has been successful in making the decisions.
The case study is based on single particular healthcare centre in Finland. The health care organization developed the management information system in 2013. The utilization of data innovation is required and basic regarding both clinical care and administration work because of the data serious nature of the human services. Regardless of developing interests in data innovation, there are as yet numerous challenges in the execution, utilize and ease of use of social insurance data frameworks. Contrasted with different areas, the inner IT abilities in social insurance associations are insufficient and fall behind in the viable advancement of data frameworks to meet the expanding requests for care, quality and effectiveness.
The accentuation in social insurance data frameworks advancement has been on clinical frameworks, particularly electronic patient records as opposed to on creating administration data frameworks. In Finland, the advancement and usage of clinical data frameworks have been accentuated in national strategies and there are various assorted data frameworks. The data gave by these frameworks, in any case, is not adequate for administrative needs. Likewise, the methodologies of Finnish human services associations have indicated out the need create management work (Kivinen and Lammintakanen 2013).
Database
The managers require the information in making the decisions. These decisions are associated with the regular activities of the healthcare centre such as organizing, coordinating, budgeting, planning, staffing and reporting. The employees who are working in various units like human resources, patient ward, financial units and many more creates a set of information for the system to be collected (Tahri, Hakdaoui and Maanan 2015). This information set is the primary requirement of the managers for taking an effective decision. The managers gets the data of the various levels of the organization in one location and this assists them in taking the best decision for the whole organization. Among directors with dominatingly clinical foundations frameworks that are not straightforwardly significant to patient care are less effortlessly acknowledged and these chiefs concentrate more on non-monetary data and lean toward a more intuitive style of utilizing administration data frameworks than supervisors with foundation in organization, who utilize MIS more for financial basic leadership (Kivinen and Lammintakanen 2013).
The role of the management information system in the decision-making is inevitable. The management information system provides the managers of the healthcare industry adequate and timely information. Various healthcare organizations have stated that the subsystems of the management information system takes an important part in the decision making process (Pettigrew 2014). The healthcare centre uses the decision-making benefits for improving the operations of the healthcare as well as recognizing and exploiting fresh business opportunities in order to maximize the business profit. After the MIS was established, the management of the healthcare centre implemented a decision making process on the basis of employee and other individuals accountable regarding making decisions. The decision making process in the MIS can be referred to the flow of data to the MIS processes then the output information to the user processes and then decision (Pettigrew 2014). This suggests that before allowing the management to take a decision on the basis of raw data, the system processes the data twice for making it understandable for the management executives.
The Healthcare centre takes five steps toward protecting and safeguarding the database. These steps are as following.
Separating the Database and Web Server: In order to make everything easy, various vendors or developers implement the data into the same server within which the application is installed. This approach is not only easy for the vendors to carry out but also cyber attackers can easily attack the database. The attackers do this by cracking the administrator account regarding one server to get control over everything. Therefore, the vendors of the healthcare centre took the decision of separating the database from the Web Server (Bao, Kojima and Kohany 2015).
Encryption: Encrypting the stored files and backups will surely enhance the safety of the data. The web application and stored file sometimes contains the information regarding the connection to the database. If the hackers somehow get hand to that connection method then database will wide open to the hackers (Deshmukh, Pasha and Qureshi 2013). Through encrypting the files, the organization can prevent the information to be fallen in the wrong hand.
Big Data
Web Application Firewall: The healthcare center, through protecting the Web Server, has protected its database. A good application firewall can prevent attacks like SQL injection along with the website destruction and cross-site scripting. Through the prevention of the SQL injection attack, the organization has avoided the theft of valuable information available in the website (Tekerek, Gemci and Bay 2014).
Installing the Patches Periodically: The website of the healthcare centre uses third-party applications. Therefore, the organization always maintains keeping the patches updated.
Enabling Security Controls: The database administrator of the healthcare centre always checks that the security controls are always enable or not.
3. Conclusion:
The study concludes that the information system, database business intelligence and various other technical aspects are very crucial for any healthcare to implement properly. The database and big data are the interrelated technical term. If the organizations have to deal with tremendous amount of data then the big data solution is used. Otherwise, the normal relational, distributed or cloud database is enough. The business intelligence can be considered as the effect and the data collection by the database as cause. The system collects data from various sources and stores it into the database. These data are processed by the system for making various patterns and recognizing trends. The business intelligence can be considered as the key of perfect decision making in the healthcare industry and all the other industries. The management information system does not provide any insight of the patient related activities. Because of this, the healthcare centre has another system that functions for better services to patients regarding treatments.
4. Recommendation:
Database: Employing a good database administrator who can manage the database activities. While implementing the database into separate server, it is crucial to check that the connection between the database and system is working.
Information System Maintenance: With the change in healthcare processes, the need of changing the MIS will come. The healthcare centre must employ a group of professional who can keep the system adequate enough for the current business practice.
Reference List:
Bao, W., Kojima, K.K. and Kohany, O., 2015. Repbase Update, a database of repetitive elements in eukaryotic genomes. Mobile DNA, 6(1), p.11.
Deshmukh, D., Pasha, A. and Qureshi, D., 2013. Transparent Data Encryption–Solution for Security of Database Contents. arXiv preprint arXiv:1303.0418.
George, J., Kumar, V. and Kumar, S., 2015. Data Warehouse Design Considerations for a Healthcare Business Intelligence System. In World Congress on Engineering.
Kivinen, T. and Lammintakanen, J., 2013. The success of a management information system in health care–A case study from Finland. International Journal of Medical Informatics, 82(2), pp.90-97.
Monteiro, P.T., Pais, P., Costa, C., Manna, S., Sá-Correia, I. and Teixeira, M.C., 2016. The PathoYeastract database: an information system for the analysis of gene and genomic transcription regulation in pathogenic yeasts. Nucleic Acids Research, p.gkw817.
Pettigrew, A.M., 2014. The politics of organizational decision-making. Routledge.
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Swan, M., 2013. The quantified self: Fundamental disruption in big data science and biological discovery. Big Data, 1(2), pp.85-99.
Tahri, M., Hakdaoui, M. and Maanan, M., 2015. The evaluation of solar farm locations applying Geographic Information System and Multi-Criteria Decision-Making methods: Case study in southern Morocco. Renewable and Sustainable Energy Reviews, 51, pp.1354-1362.
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Tekerek, A., Gemci, C. and Bay, O.F., 2014. Development of a hybrid web application firewall to prevent web based attacks. In Application of Information and Communication Technologies (AICT), 2014 IEEE 8th International Conference on (pp. 1-4). IEEE.
Trumpy, E., Bertani, R., Manzella, A. and Sander, M., 2015. The web-oriented framework of the world geothermal production database: a business intelligence platform for wide data distribution and analysis. Renewable Energy, 74, pp.379-389.
Wu, X., Zhu, X., Wu, G.Q. and Ding, W., 2014. Data mining with big data. ieee transactions on knowledge and data engineering, 26(1), pp.97-107.
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