COLLABORATIVE BIG DATA ANALYTICS AND VISUALIZATION
A LITERATURE REVIEW
Abdulazeez Adejumo
Department of Computer Systems Technology
North Carolina Agricultural & Technical State University aadejumo@aggies.ncat.edu MARCH 2015 Abstract
This paper discusses collaboration using big data analytics and visualization. It tries to bring to fore the advantages of collaborative analysis using visualization tools. How information visualization can enhance effective collaborative decision making process. It reviewed applicable and related literatures and it put forward propositions about definition of key terms, their relationships and applications.
It hashed out the relationship between understanding big data through
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Now that we have figured out how to harvest the free and ubiquitous big data, the next huge challenge is to figure out how to analyze and display the information in a useful and meaningful way. The big question today is how you present big data in a way that human beings can quickly understand and make decision. Most big corporations and government entities are drowning in a pool of their own data, because they lack the corresponding manpower to understand the data and extract meaningful knowledge out of it (Bizer, Boncz, Brodie, & Erling, 2012).
This paper focuses on reviewing the accessible literatures on big data analytics and big data visualization in a collaborative environment. Consequently, methodologies and technologies used in these fields are described. The challenges facing collaborative visualization was highlighted but they were not discussed in details.
The literatures reviewed were selected among the enormous papers out there based on their uniqueness in the way this topic was treated with focus on the purpose of my research. The year of publication of these articles range from 2010 to 2014. This is because collaborative visualization of big data gained its prominence during these years.
Therefore, the consecutive sections discussed the definition of big data, tools for analyzing big data, data mining, knowledge discovery, visualization and collaborative
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
Brown, B., Chiu, M., Manyika, J. (2011), Are you ready for the era of big data? Retrieved
Since the 1970’s databases and report generators have been used to aid business decisions. In the 1990’s technology in this area improved. Now technology such as Hadoop has gone another step with the ability to store and process the data within the same system which sparked new buzz about “big data”. Big Data is roughly the collection of large amounts of data – sourced internally or externally - applied as a tool – stored, managed, and analyzed - for an organization to set or meet certain goals.
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
Meanwhile, data sharing is a large part of Boston’s efforts to improve the quality of life for their residents. And the City of Boston eagers to improve BAR from a data collection effort to a citywide performance management system accessible in real-time from any device. Big data provides an unprecedented opportunity to deliver improved services. It is a good chance to analyze large data sets, find the value of data and tell the story of the City of Boston in new way.
New organizations can leverage Big Data in such a way that it provides benefits that can prove valuable especially to an organization seeking to establish itself and grow. One of these benefits is faster and better decision making. Particularly with the analytics of Big Data, organizations have access to real-time data
Visualization in data mining is a new methodology for exploring and analyzing a huge data sets, data visualization techniques and joining traditional data mining strategies. It is used for large amounts of data sets and information. Visualization of model-fitting, data and results play a very important role, but vast data sets are distinctive and new techniques of a data display needed for managing and dealing with large data sets. With the help of this paper to learn the importance of visualization techniques, approaches and methods used in data mining . The strategy used to achieve this objective is writing an literature review of many books, journal articles and conference proceeding which are written by experts.
Big Data is an outgrowth of the proliferation of databases and massive data sets. The insights needed to more intelligently manage an organization can be found in the myriad of data sets that comprise a Big Data platform. The greatest challenge of Big Data is contextual intelligence supported by integration to legacy, 3rd party and homegrown application systems located throughout an enterprise (Jacobs, 2009). To get ot his level of proficiency in analyzing Big Data sets and databases, enterprises need Business Intelligence (BI) and analytics tools that can parse through terabytes quickly, finding patterns and analyzing massive amounts of data, then distilling it down to key
With the growing data explosion, understanding of data is faster and easier through data visualization, providing an individual highly valuable insight of data at minimum effort and time. This helps the user to come up with new hypothesis and models from complex large scale data. Furthermore, new technologies are emerging in the frontier of data graphics and hardware to enable the rapid progress in the field [1] . The visualization tools such as graph, chart, and glyphs not only fasten the exploration process but also help to understand the characteristics of the multidimensional, complex data and communicate it.
Today, data is a growing asset that various businesses are having difficulty converting into a powerful strategic tool. Companies need help turning this data into valuable insight, which can diminish risk and enhance returns on investments. Companies are struggling to make sense and obtain value from their big data. Superior and reliable
It is that time of year again, to sit back, and reflect on everything that has happened in the past year and to make predictions of what will happen in the years to come. The new job that is starting to move out of the woodworks is ‘Big Data.’ These large volumes of data are being used in ways no one could have imagined years ago. Data analysts are using this newly found information to improve the world around us, from helping companies make a more efficient profit, research the climate changes, or improve how people live their daily lives.
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’ is the application of specialized techniques and technologies to process very large sets of data. These data sets are often so large and complex that it becomes difficult to process using on-hand database management tools. There are several techniques which are widely used in implementation of Big Data.