Big data visualization: Tools and challenges

Ali, Syed Mohd; Gupta, Neelesh; Nayak, Gopal Krishna; Lenka, Rakesh Kumar

doi:10.1109/ic3i.2016.7918044

Cited by 101 publications

(47 citation statements)

References 5 publications

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“…Ali et al [2] conducted thorough research and reviews of visualization tools. However, it must be acknowledged it was conducted with Big Data, unstructured data as the focus, whereas, the focus of this paper is concerned with structured data.…”

Section: Related Workmentioning

confidence: 99%

Visualization of Online Datasets

Downie¹,

Peng²

2018

IJNDC

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As computing technology advances, computers are being used to orchestrate and advance wide spectrums of commercial and personal life, information visualization becomes even more significant as we immerse ourselves into the era of big data, leading to an economy heavily reliant on data mining and precise, meaningful visualizations. However, accuracy of information visualization techniques is heavily dependent on the knowledge and capabilities of users, leaving novices in many fields at a disadvantage. This is a challenging problem that has been inadequately addressed regardless of the influx in visualization tools. Therefore, this paper proposes a novel approach with a focus on online datasets, allowing users to automatically and accurately visualize datasets. Experiment results show that using a browser extension and specially created HTML tables containing custom attributes-stating the data attribute type-the approach is able to detect and present the most suitable visualizations at the click of a mouse. This proposed approach provides a means for novices to quickly and accurately visualize online datasets.

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Section: Related Workmentioning

confidence: 99%

Visualization of Online Datasets

Downie¹,

Peng²

2018

IJNDC

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“…We have demonstrated some of the queries in this paper, the user can also perform other queries in diverse ways as per requirement. Since visualization is an important aid to find out insights of your data, we used Tableau to visualize our data and its results [7]. Since we are dealing with big data, we connected tableau with Hive to take advantage of working in distributed environment [26,27,28].…”

Section: Hybrid Model For Faculty Retrievalmentioning

confidence: 99%

“…There exist some special visualization tools that are designed especially for handling big data like Tableau, Microsoft PowerBI, Gephie etc. in our model we used Tableau for visualization to do in-depth analysis [7].…”

Section: Big Data Visualizationmentioning

confidence: 99%

Fair: A Hadoop-based Hybrid Model for Faculty Information Retrieval System

Gupta¹,

Lenka²,

Barik³

et al. 2017

Preprint

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Abstract:In era of ever-expanding data and knowledge, we lack a centralized system that maps all the faculties to their research works. This problem has not been addressed in the past and it becomes challenging for students to connect with the right faculty of their domain. Since we have so many colleges and faculties this lies in the category of big data problem. In this paper, we present a model which works on the distributed computing environment to tackle big data. The proposed model uses apache spark as an execution engine and hive as database. The results are visualized with the help of Tableau that is connected to Apache Hive to achieve distributed computing.

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“…Especially, using those conventional methods, practitioners are required to have considerable visualization expertise and they must have a deep understanding of the inter-relation among data to properly select attributes to be visualized. Choosing the right number of data attributes is a critical task as an appropriate reduction of dimensions would help to highlight the key pattern and can reduce processing time and the density of the image without losing interesting patterns (Ali 2016). Since identifying the semantic relationship between data objects is the first step of dimension selection (Khan and Khan 2011), automated determination of related variables is required to help highway practitioners overcome the obstacle when working on large and complex data sets.…”

Section: Introductionmentioning

confidence: 99%

“…Visualized data allows professionals to quickly see patterns and evaluate the correlation between data attributes. However, deriving meaningful information from large data sets using traditional visualization techniques is challenging due to the increasing degree of the complexity and the volume of data (Ali et al, 2016).…”

Section: Introductionmentioning

confidence: 99%