Analyzing this data to extract sensible and meaningful insights is a big challenging task; integrating and optimizing this data, storing, organizing and analyzing is a challenge. The Big Data must be captured, stored, organized and analyzed to influence the decision making in any enterprise or business
To conquer big data, organizations must learn to embrace it. Factors impeding the efforts to build analytical organization The three parameters any organization needs to address to maximize the value of big data are: 1. Institutional inertia: Big data helps the organization to understand the current market, competitions, and strategies etc. which transform them. This kind of sudden change creates unease and resistance at different levels.
Gaining critical business insights by querying and analyzing such a very big amounts of data is suitable need of the hour and become a challenge to the standard data taking out approach. This data comes from a broad range of sources such as logs, social communication, sensors etc. The organizations are facing new challenges to analyze vast amounts of information. The different aspects of the big data make it difficult to manage. Big data requires speed for its processing.
INTRO → BIG DATA AFFECT PUBLIC EXPENDITURE AND QUALITY OF THE SERVICE The usage of big data in the healthcare sector can have significant consequences on the productivity of the healthcare system, improving the quality of care and treatment, enhancing patients’ experience, boosting industry competitiveness, and creating a range of fresh business models and services. For example, McKinsey has estimated that US healthcare could capture more than $300 billion in value every year. Interesting to see is that $200 billion out of those $300 billion derive from savings on national healthcare spending, that is of around 8 percent of the total national healthcare expenditure. It is necessary to go deeply into the repercussions of using big data on public
The biggest disadvantage of Big Data is the lack of privacy, specifically on trusted medical records. To be effective and get the entire picture of a patient, Big Data must have access to everything. Technology minimizes individual privacy, according to Big Data experts. Moreover, Big Data allows doctors to observer a patient’s health from everywhere. Furthermore, there are some people that they see the ability of forsee future medical problems as positive, but Big Data can be seen as replacing doctors.
The main aim of big data analytics to have better decision power. The decision support system is being a tool for managing complex supply chain. The research paper presents a multi-agent-based supply chain management system that incorporates big data analytics which can enable better corrective control actions. The paper discusses the applications of the multi agent supply chain management. The author has presented the use of multi agent based supply chain system could enhance the supply chain agility inspite of increased complexity of global supply chains.
Due to such large size of data it becomes very difficult to achieve effective analysis using existing traditional techniques. Since Big data is new upcoming technology in the market which can bring the huge benefits to the business organizations,
With the existence of big data, people can gain advantage especially for companies or organizations. However, to derive the real value of Big Data, tools are needed to store and organize those data, which comes from a variety of sources in order to analyze the data effectively. Besides that, the issues and challenges of Big Data must also be known to understand and avoid from making
I. INTRODUCTION Healthcare organizations today are capable of generating and collecting a large amounts of data. This increase in volume of data requires automatic way for these data to be extracted when needed. With the use of data mining techniques it is possible to extract interesting and useful knowledge and regularities. Knowledge acquired in this manner, can be used in appropriate area to improve work efficiency and enhance quality of decision making process.
You can take data from any source and analyze it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smart decision making. When you combine big data with high-powered analytics, you can accomplish business-related tasks such as: • Determining root causes of failures, issues and defects in near-real time. • Generating coupons at the point of sale based on the customer’s buying habits. • Recalculating entire risk portfolios in minutes. • Detecting fraudulent behavior before it affects your