COIS13013 Business Intelligence and Development of Venture

Answer 1: Knowledge management is the process of creating, using, sharing and managing knowledge and information in an organization therefore it is the effective approach for achievement of organization objectives by best use of knowledge. Knowledge management plays significant role in an organization. The main object of knowledge management is to create and improve knowledge stores and resources. It helps in development of knowledge environment (Collison & Parcell, 2007).

Significant of knowledge management are as follows:

• Knowledge management improves the organization ability for solving problems and conflicts.
• It is the process of using and sharing information and knowledge in such way it promotes innovation and cultural changes for changing business requirements.
• Knowledge management helps in improving the quality of employees and speed of decision making thus it plays vital role in decision making process.
• It increases customer satisfaction by using of information, knowledge and cross collaborations in organization.
• It helps in reducing tendency of repeated work and increases efficiency and productivity of employees.

Knowledge management technologies are discussed as below.

• Groupware: It helps in teamwork and coordination by sharing information in groups therefore it provides a framework for threaded discussion and sharing information.
• Workflow: This techniquepermit the version of processes related with the creation, use and safeguarding of organization knowledge. It is important tool for development of venture portals.
• Content/Document management: It provides a tool for content and document management.
• Enterprise portals: Websites provide information to organization as well as groups.
• Elearning: It provides framework for creating modified training and education software thus it includes lesson plans, progress monitoring and online programs.
• Planning and scheduling: It provides tool for planning, maintenance and scheduling.
• Telepresence: It includes face to face meetings without gathering at one site. Videoconferencing is important example of telepresence (Maier, 2007).

Answer 2: Data analytics: Data analytics refers to quantitative and qualitative techniques and tools which are used in improvement of productivity and business gain thus data is divided in two parts such as, data and patterns for recognition and analysis of behavior (Bivand, Pebesma, Gomez-Rubio, and Pebesma, 2008).

Text analytics: It refers to text data mining and it is same as data analytics therefore it is the process of deriving valuable and important information from text. Valuable information is very difficult in deriving through devising of patterns and trends (Widdowson, 2008).

Differences between data analysis and text analysis:

There are four types of data analysis which is using by many companies in business, they are such as prescriptive, predictive, Diagnostics and descriptive. For example, in healthcare industry the patient’s population can be easily managed by using of prescriptive data analysis and it can help to measure number of patients who are diagnosed with obesity. The another example of data analysis is social media marketing campaign where descriptive data analysis can be used for evaluation of number of posts, followers, fans, mentions and pins etc. Companies can use data analysis tools for sales leading scores and it can evaluate financial performance of customers. So it can be said that data analysis is very useful for organization. It helps in constructing the findings from different source of data and it breaks macro level problems into micro level problems.

Answer 3: Knowledge based decision support system: Knowledge based decision support system is also known as intelligent decision support system. It helps managers for taking strategic and critical decisions by providing useful information and interpretations for various alternatives. Knowledge based support system provides support and cooperation for solving problems and conflicts because it is based on excellent knowledge. Artificial intelligence technique used by knowledge based decision support system. It provides flexibility to organization for solving problems effectively (Berner, 2007)

Decision support system: Decision support system is an effective organism which provides support to organization and business for taking effective decisions thus it is a tool for operation, management and planning for developing an organization. It is a computer based information system which provides assistance for decision making process. Inputs, outputs, decisions and use of knowledge and expertise are the main components of decision support system. There are three types of DSS, they are such as data driven DSS, Model- driven DSS and knowledge driven decision support system therefore they all provide excellent framework to organization (Turban, Sharda and Delen, 2011).

For example, it provides expert assistance and advice in specific problems like define computer procedures, run decision models and presenting reports. But decision support system is not provided such kind of information. Another side a knowledge based decision support system helps in defines decision models and provides intelligent support for decision analysis. It also provides guidelines while using decision support system.

Another example of knowledge based decision support system is clinical decision support system which is used for medical diagnosis of patient data. Finance center is also example of knowledge based decision support system because it provides support to take decision for financial institutions to increase the revenue and profits.

It helps in learning good strategies for using tools and techniques and discovers knowledge from huge record.

Answer 4: There are three service models of service oriented decision support system in the organization. They are discussed as below (Dmantley 2013)

• Optimization/Simulation model:It refers to the finding alternatives and functions for cost effective and achievement of highest performance under the certain constraints with the help of maximizing desired factors and minimizing undesired factors. In optimization, maximizing refers to attainment of higher results and minimizing refers to reducing cost and expenses for the desired outcomes. Optimization model is restricted by the lack of full information and time to assess the information is available in the organization.

Another side simulation can be used to demonstrate final genuine effects for alternative conditions and course of action. Simulation can be used for educational purpose; training and military personal and it identify the risk and control on the risk factors. For example, simulation games represents as a simulation environment compare to the other video and computer games. Theme park rides also example of simulation model.

2) Deterministic model: It is the system in which there is no uncertainties involve in the development of future states of the organization. A deterministic model usually produces the similar output for the given initial conditions and primary state. For examples, deterministic model represents the physical laws which are described by different equation. Another example, The Schrödinger equation in quantum mechanics which are explained the constant time development of a system thus it seems as deterministic model (Chankong and Haimes, 2008).

3) Operation, management and planning model: Operation management is a district area of management who controls and designs the process of productions and business operation. It involves the responsibilities which ensure that production process is very efficient in terms of using wealth and in terms of customer requirements. It controls and manages whole production system which converts inputs of materials into output of materials. Operation management covers banking sectors, companies, hospital, suppliers and technologies.

Refernces

Berner, E.S., 2007. Clinical decision support systems (Vol. 233). New York: Springer Science+ Business Media, LLC.

Bivand, R.S., Pebesma, E.J., Gomez-Rubio, V. and Pebesma, E.J., 2008. Applied spatial data analysis with R (Vol. 747248717). New York: Springer.

Chankong, V. and Haimes, Y.Y., 2008. Multiobjective decision making: theory and methodology. Courier Dover Publications.

Collison, C. and Parcell, G., 2007. Learning to fly: Practical knowledge management from leading and learning organization (With CD). John Wiley & Sons.

Dmantley, 2013, Decision Support System (DSS), viewed 21 July 2017, from https://dmantley.wordpress.com/2013/05/27/decision-support-systems-dss/

Maier, R., 2007. Knowledge management systems: Information and communication technologies for knowledge management. Springer Science & Business Media.

Turban, E., Sharda, R. and Delen, D., 2011. Decision support and business intelligence systems. Pearson Education India.

Widdowson, H.G., 2008. text, context, Pretext: critical Isssues in discourse Analysis (Vol. 12). John Wiley & Sons.