Information Visualization And Data Mining

The analysis of big data is the process of organizing, collection, analyze and examining the large volume of data to find patterns, market trends and useful information. This analysis helps organizations to better understanding about the information within data, and helps analyst to make better

The concepts are the significant advancement in examination and access to quality information. The new aspect of big data that is essential for its application is the variety formats it receive data. The data streams in different format of structured and unstructured (Groves et al., 2016).The data comes in numeric database, videos, audios and email. The data also comes from multiple sources. It is therefore ease to detect the trend and nature of the information in the system. Data management is one of the key aspect of data mining. It involves examination of data and identification based on source and quality (Crockett, & Eliason, 2016). These elements create utility of the information in the system. The health care will therefore get quality information for improving its

The research proposal can be developed from the topic of big data to match up the demands of enormous data flow in the dynamic world. Data visualization tools at significant cost can help up in analytics of big data and can form an innovative research proposal for analysis and extensive research. The real time data and the use of techniques of big data in this domain can form an excellent topic of research calling for formulating methodologies and strategies to tap the untapped potential of this field and to experiment more in the field of research.

Big Data is an expansive phrase for data sets so called big, large or complex that they are very difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. In common usage, the term big data has largely come to refer simply to the use of predictive analytics. Big data is a set of techniques and technologies that need or require new forms of integration to expose large invisible values from large datasets that are diverse, complex, and of a massive scale. When big data is effectively and efficiently captured, processed, and analyzed, companies

The author points out that although there are existing algorithms and tools available to handle Big Data, they are not sufficient as the volume of data is exponentially increasing every day. To show the usefulness of Big Data mining, the author highlighted the work done by United Nations. In order to further enhance the reader’s perspective, the author provided research work of various professionals to educate its readers about the most recent updates in Big Data mining field. The author further describes the controversies surrounding Big Data. The author has first provided the context and exigence by elaborating on why we need new algorithm and tools to explore the Big Data. The author used the strategy of highlighting the logos by mentioning the research work of different industry professionals, workshops conducted on Big Data and was able to appeal to connect to the reader’s ethos. The author also used pathos by urging the budding Big Data researchers to further dig deep into the topic and explore this area

Visual representation is a powerful and very effective way to present information. Each method used including some methods not provided on here have a massive role in telling different stories of how the world is set up. Matching the data/ information collected is a very important aspect. Using visual representation of data can help make complicated form of information example research, data, facts, statistics and patterns relevantly very easy and basic to understand.

Data mining is the procedure of identifying new hidden, insights and unexpected patterns in large data. Analyzing and exploring the huge volume of data sets and information becomes increasingly very difficult. Visualization of data mining helps to deal with a flood of data and information. As a volume of a large set of data stored and collected in databases develops, there is a developing need to provide a data summarization through visualization. The benefit of visual information investigation is that the client directly involves in the process of

In a fast paced, business ordinated technological world the overall welfare of a company is tied to the success or failure to make the tough decisions. On one instance a company’s CEO might be able to make the choices based on experience, advice, or simple gut instinct. However, this is not the only skill one needs. There is a great deal of information to be found in being able to see investments in data and analytics. These decisions are based off of big data. Big data is a catch-phrase, used to describe a massive volume of both structured and unstructured data that is too large to process using traditional database and software techniques. The volume of data is in most cases is too big, moves too fast or it exceed the processing capacity the company has. Despite these potential drawbacks, big data contains the potential to help companies by improving operations and making faster, more intelligent decisions. This can be broken into three key parts, knowledge, data, and information.

Part 1: To focus on the field of information visualization introduction, definitions, conceptualizing data types within the field, the advantages and disadvantages of representing information in 2D and 3D, 2D and 3D information visualization presentation techniques, 2D and 3D information visualization in the Web environment, and an introduction to the Scalable Vector Graphics (SVG) and extensible 3D (X3D) standards.

Datawatch Visual Data Discovery is an interactive tool that can find correlations, clusters and patterns within your data. It features reporting capabilities that allow you to gain more detailed results, discover trends, and get rid of irrelevant data easily to identify underlying data patterns.

In general, the term “Visualization” is defined as the development of a visual image in the human mind. However that is more than simply a graphical representation of data or concepts, as visualization can work as a cognitive tool, and becomes a powerful strategy in the construction of knowledge using human percipient and cognitive capacities. This definition is based on the work of Stuart Card (Card 1999); he defines “Visualization” as being the use of visual representations of abstract data, supported by computers and in order to extend the cognition, in an interactive mode (Dulclerci & Joao, 2010).

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

Big data analytics methods and techniques (which is the application of predictive methods, pattern recognition techniques, cluster analysis, and other quantitative and qualitative methods in big data sets) can

The amount of digital data has been exploding during the past decade, while the number of scientists, engineers and analysts available to analyze the data has been static. To bridge this gap requires the solutions of fundamentally new research problems, which can be grouped into the following broad challenges: (a) developing algorithms and system to mine large, massive and high dimensional datasets, (b) developing algorithms and system to mine new types of data, (c) developing algorithms, protocols and other infrastructure to mine distributed data, (d) improving the ease of use of data mining systems, and (e) developing appropriate privacy and security models for data mining. In order to respond to these challenges, we require applied, multidisciplinary and interdisciplinary research in data mining and knowledge discovery (Soman et al., 2008).

Abstract— Big Data is a new term used to describe a massive volume of both structured and unstructured data that is so large that it is difficult to process using traditional database and software techniques. Big Data mining is the capability of extracting useful information from these large datasets or streams of data, that due to its volume, variability, and velocity, it was not possible before to do it. The Big Data challenge is becoming one of the most exciting opportunities for the next years. We present in this issue, a broad overview of the topic, its current status, and forecast to the future. We also introduce some articles, written by influential scientists in the field, covering the most interesting and state-of-the-art topics on Big Data mining.