Table of Contents
This paper speaks about the agile smart data that incorporates methods, algorithms and heuristics for data usage and for supporting executive needs. This data comprises certain business rules that strings along imperatively. We also observe the implementation of these rules in cases like apache and giant forest. The paper further questions whether a design diagram is required round the business events described in the IT Capital Budgeting and MWDSS case studies.
INTRODUCTION
Smart data is the digital information which is formatted for further data analytics and consolidation. Smart data is often related to IOT and data produced by smart sensors. It does not require a centralized system for the decision making process. Business analysts, IT managers, data scientists, etc., are looking and experimenting for ways of increasing revenue, solving problems, improving efficiency and decision making by using smart data. It is closely related to the concepts distributed computing such as openness. Some of the applications of smart data are financial services, manufacturing, healthcare, public sector, etc. Capital budgeting is the process by which an organization evaluates and ranks its investments and expenditures. IT capital budgeting problem can be modelled and solved by the knapsack optimization problem and two different simulated annealing heuristic solutions. The Med Watch Decision Support System (MWDSS) is a medical informatics technology that is mainly used for tracking disease trends and patient movements in the military.
RESULT
Capital Budgeting is undertaking and selecting set of capital expenditures for resources. They are two different Simulated Annealing heuristic models to solve the information technology capital budgeting. Inputs would be given and results are compared in the both models. When the output was compared Simulated Annealing, heuristic had high values. Smart data is very important for decision making process. By using the smart data and Simulated Annealing model the results were more high level. Smart data is helpful to provide cost effective support and strategy. Web Based Med Watch Decision Support System is an application which is used to improve decision making. Med Watch Decision Support System helps to improve the performance and also integrates internal process and external process, surveillance is also improved. When inputs were given to the software it would analyse and provide feedback as output. It was so easy to understand and has common operations. Med Watch Decision Support System provides high impact results and also improves data resource management. Smart data helps in increase in optimization, lower cost, and increase in strategy. In increasing daily objectives and challenges these tools are used to improve decision making.
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CONCLUSION
From the result we see the ways by which smart data can be used in IT capital budgeting and Med Watch Decision Support System. The main aim of smart data is to produce valuable data that can be used by governments and other enterprises for the various purposes like planning, monitoring, decision making, etc. It is the data that has been engineered to have superior characteristics. It optimizes enterprise performance making it more efficient, effective in terms of cost, strategy, planning and decision making. Some of the characteristics of smart data are adaptability, high response to change making it timelier and responsive, lower cost, continuous optimization and performance enhancement of the enterprise. One of the concerns of smart data in an enterprise is that the smart data strategy is not clear and understandable by all levels of users. This gap must be removed in order to maximize efficiency and effectiveness.
