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Decisions With Big Impact On Data Analytic - MyAssignmenthelp.com
Question: Discuss about the Decisions With Big Impact On Data Analytic. Answer: Introduction General Electric is a digital industrial company which was found in New Jersey USA in 1878.The Companys business is divided into four themes i.e. building, curing, moving and powering. General electric builds appliances, lightning, power systems and many other products for domestic and business applications. It also provides medical technologies like CT, MRI, Digital Mammography, PET/CT, Ultrasound and patient monitoring devices. Apart from this, GE builds navigational and transport safety and productivity systems.GE is also involved in developing and producing nuclear and wind turbine technologies. As, General Electric has a wide business and all of them are distributed so to provide connectivity with all the themes it released a project named as Industrial Internet. This project is a combination of machines, data and the Internet. This report will utilise an Enterprise Information Architecture-Reference Architecture (EI RA) approach to analyse and design an Information Centric implementation of Industrial Internet with respect to the four themes of General Electric. EIA RA is a template approach to Enterprise Information Architecture. It not only works through a systematic process of design but it assumes that there are tried and true methods and design patterns which form the building blocks of information systems. Yet it allows for changing and evolving technologies. The systematic EIA RA approach to Industrial Internet design will include its Conceptual Architecture, Logical Architecture, Component Modelling and Operational Modelling. One of GEs latest projects is an Industrial Internet which is the convergence of industrial machines, data and the Internet. The potential is to provide connectivity for all product applications with the use of four themes. It also includes real-time monitoring and analytics of remote systems such as pipelines and power generation equipment. This very dynamic company require enterprise systems that can adapt and not only remain effective in the harshest of conditions but also operate in the most secure and data sensitive environments such as hospitals. Conceptual Architecture The aim of Industrial Internet Enterprise System (EIS) is to provide a flexible, connected information system that enables connectivity for all the product applications of General Electric .It should also include real-time monitoring and analytics on remote systems and remain effective even in adverse conditions. Capabilities required for the system should include: Industrial Internet must operate for all the four enterprises, Provide real time monitoring on power generation equipments, Enable the sensors on gas turbines and other machines to get connected to the cloud, Enable the machines to operate in adverse situations These four requirements of Industrial Internal is not an exhaustive list and only pertain to the four themes of General Electric i.e. Building, Curing, Moving and Powering, the building blocks of which are portrayed in Figure 1. This figure shows a system as a single enterprise but comprises all the four themes. A conceptual architecture diagram represents the system architecture and here it describes how the executive business people gets the information updated on Industrial Internet. Figure 1: Conceptual diagram The real time monitoring all the themes is controlled by the cloud and then analysed in respect to security. These building blocks are the basis of an Architecture Overview Diagram (AOD) which translates non-technical operational requirements into a conceptual model(Godinez, 2010) as described in the given figure. The AOD in the figure displayed below shows how the various concepts required in an Information Architecture connect and interoperate to deliver a flexible Industrial Internet to the executive business people. Data Domains of all the themes comprises into a single enterprise approach of Industrial Internet which is managed by Master Data services, Metadata Services, Data Services, Content Services and Analytical Services. Although these systems will be geographically dispersed, they will be designed to give accurate information and good performance to the cloud and all the four themes as well as the end users. Industrial internet provides functionalities of accessing big data. These systems and services are used by the cloud as well as the executive business people with their respective presentation services and delivery channels. The Connectivity and Interoperability service provides the data communication channels between all these systems and services. The service is integrated into cloud services and security along with privacy. The metadata services for exchange of information based systems on the basis of metadata. The Master Data services provide quality and authoring services. The analytical services will let the cloud optimize the business performance. The content services take care of the data which is unstructured like images, presentations and gives measure to manage that data. Logical Architecture The logical architecture starts to set out the technical functionality required to deliver the business view oriented conceptual architecture (Godinez, 2010). Figure 3 Logical View Diagram shows how functional services are logically located in relation to each other. This starts at the base where Cloud hosting services host and support Integration and Information services which provide services to the Application Services which are presented to different themes and areas and constituents in the Presentation Layer. These all communicate via the Connectivity and Interoperability Services. Non-functional services dealing with Compliance, Availability, Retention, Security, Capacity and Quality of Service(Godinez, 2010) are also shown in relation to the services they support. These include Business Process Orchestration and collaboration service, Information Security and Information Privacy and IT Service Compliance and Management Services. Figure 3: Logical Architecture Diagram The Business Process Orchestration and Collaboration layer gives end-to-end business process orchestration. They also provide abilities in such a way that all the users of an enterprise collaborate easily. The Connectivity and Interoperability determines interoperability between the services. It also supports transport and communication protocol and interoperability functions. Information Security and Information Privacy is required for security and data assurance policies. These services are necessary because they reduce risk and make the system cost effective. Component Model The Component Model sets out the actual parts or components that will deliver the functionality shown in the Logical model. A Component can be described as a logically grouped set of specific capabilities or software applications that will deliver specific functionality (Godinez, 2010). The model sets it out in three parts; Component Relationship Diagram, Component Descriptions and Component Interaction Diagrams. Component Relationship Diagram The Component Relationship Diagram depicts the components, interfaces and their relationships(Godinez, 2010). The given figure shows a depiction of the Logical Model Diagram turned on its side and populated with the Components which will deliver the logical functions. These Components are then described as part of the Component Model. Figure 4: Component Relationship Diagram Component Descriptions Component Descriptions describe each component in terms of it services, interfaces and functional and non-functional requirements. Depending on the needs of the project these descriptions include an ID for Identification, a Name, High-level description, Service description and a list of Interfaces (Godinez, 2010). For the purpose of this report only the Mash up Hub component differ from the Enterprise Information Architecture Reference Architecture model and are therefore described. Name Mash up Hub High-level description- This component combines the four themes of General Electric with Industrial Internet .It also relates the cloud with the executive business people and works as an interaction gateway between people and the Enterprise Information Enterprise. This portal will constitute all the four themes on a single cloud enabling the Industrial Internet to get mash-up with the themes. In terms of security and moderation services, this Collaboration Hub relies on Presentation Services access to the Directory / Security Services component for authentication and authorisation and relies on collaboration services to monitor and moderate individual collaboration instances. With the help of this hub, it will be easy to analyse and examine all the themes and let the system operate easily. This component relies on Presentation Services to secure the communication and authorise and authenticate the constituent on a single-sign in basis (one sign in gives access to all authorised portals). Interfaces on the external presentation side, multiple themes are presented simultaneously and are presented to the executive business people. The presentation layer also presents multiple collaboration interactions of executive business people on a dashboard type web or mobile app page. On the internal interface side is a gateway which acts as a connection between building, curing, moving and powering. This Mash up hub also enables a business to quickly build web-based applications at low costs. They also allow non-technical users to create new value from the information by mashing together information from various sources. Component Interaction Diagram Component Interaction Diagrams depict the dynamic interaction between components in a particular use case scenario. It is a way of high level interaction testing to verify component configuration and inclusion. The given figure represents the access to the Mash up- Hub interaction scenario. It shows how the themes must be included in the cloud first and then be passed onto the Presentation Services for examination. Figure 5: Component Interaction Diagram Operational Model An operating model is the operational design which is responsible for the delivery of the business strategy. The ideas of operating model improvements make many changes in the business strategy and hence the business grows. The operating models also describe how the organization delivers the abilities and the outcomes of finance which are necessary for the strategy. Processes and activities the work that needs to be done Organization and people the people doing the work and how they are organized Locations, buildings and other assets the places where the work is done and the equipment in those places needed to support the work Information the software applications and databases needed to support the work Sourcing and partners those outside the organization supporting the work Management system the planning and performance management of the work Figure 6: Operational Model The Operational Model takes the components from the Component Model and distributes them onto geographically distributed nodes (Godinez, 2010). Data flow connections between nodes are specified between geographically dispersed Locations. Nodes are location specific and physical platforms on which software executes. Each node consists of one or more components known as Deployment Units(Godinez, 2010). A Component Model will be broken down into many distinct functional and non-functional Operational Models. The EIA RA has templates for many standard components such as those portrayed in Figures 6 and 7. The Content Resource Manager Service availability portrays an industry standard method of maintaining high availability for unstructured data. Likewise the Continuous Availability and Resiliency Operational Pattern portrays a standard design to maintain the data security and operations even in adverse situations. Conclusion General Electric requires a big data and analytics system known as Industrial Internet. Hence, Industrial Internet has been designed using industry standard Enterprise Information Architecture Reference Architecture templates which are business executive centric. Having outlined five specific capabilities, a system Building Block diagram and an Architecture Overview Diagram were drawn to provide a conceptual technical view of the Industrial Internet enterprise information system. From this diagram a Logical Diagram was drawn to translate the concepts into an information system which was then broken down into components which could be described and logic tested in the Component Model. Once all the components were set out they could be further broken down into many Operational Models describing geographically located nodes and their data connections. During each step of the design process, reference has been made to the required big data and analytics capabilities for which the Enterpr ise Information System is designed. Industrial Internet identifies ways to improve productivity and reliability. References Aitchison, M. (2016). Design Research in Architecture: An Overview.The Journal of Architecture, 21(2), pp.308-312. Diesner, J. (2015). Small decisions with big impact on data analytics.Big Data Society, 2(2), pp.205395171561718. Eliot, G. (2016).The mill on the Floss. New York: Open Road Integrated Media. General Electric (2018).About us. [online] Available at: https://www.ge.com/au/ [Accessed 11 Jan. 2018]. Hudson, W. (2003). Enterprise information architecture.interactions, 10(6), p.53. LaWell, M. (2015).Building the Industrial Internet With GE. [online] Available at: https://www.industryweek.com/manufacturing-leader-week/building-industrial-internet-ge [Accessed 11 Jan. 2018]. Matter, V. (2015).The Industrial Internet: An Underestimated Game Changer?. [online] Available at: https://www.maisonneuvega.com/uploads/6/3/4/5/63456323/the_industrial_internet_-_an_underestimated_game_changer_-_mga_011215.1.pdf [Accessed 11 Jan. 2018]. Marks, O. (2008).GE's Enterprise Collaboration Backbone | ZDNet. [online] ZDNet. Available at: https://www.zdnet.com/article/ges-enterprise-collaboration-backbone/ [Accessed 11 Jan. 2018]. Wining, L. (2016).GEs Big Bet on Data and Analytics. [online] Available at: https://sloanreview.mit.edu/case- study/ge-big-bet-on-data-and-analytics/ [Accessed 11 Jan. 2018].
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