scholarly journals VISUALISASI DATA INTERAKTIF DATA TERBUKA PEMERINTAH PROVINSI DKI JAKARTA: TOPIK EKONOMI DAN KEUANGAN DAERAH

2016 ◽  
Vol 12 (2) ◽  
pp. 82
Author(s):  
Nadiar Ahmad Syaripul ◽  
Adam Mukharil Bachtiar
Keyword(s):  
Data Analysis ◽  
Data Visualization ◽  
Human Visual System ◽  
Exploratory Data Analysis ◽  
Mobile Platforms ◽  
Personal Lives ◽  
Abstract Data ◽  
Exploratory Data ◽  
Open Datasets ◽  
The Given

Based on statistics from data.id, in the first quarter of 2016, there are 1,137 datasets distributed at 32 institutions and 18 groups in Indonesia. DKI Jakarta Province contributes to these data at the most, i.e. 714 datasets. A lot of accessible open datasets have an impact on the availability of valuable information that can be extracted to good use, for businesses, governments, and personal lives. To get the desired information, an exploratory data analysis is needed to make data more alive. The goal of this research is to provide a proper visualization of the given data. Data visualization is a way (perhaps a solution) to communicate abstract data, to aid in data understanding by leveraging human visual system. The result of this visualization is effective and engaging charts appropriates to the given data and can be run on mobile platforms.

Hyperbolic Space for Interactive Visualization

2011 ◽  
pp. 575-581
Author(s):  
Jörg Andreas Walter
Keyword(s):  
Pattern Recognition ◽  
Data Analysis ◽  
Hyperbolic Space ◽  
Exploratory Data Analysis ◽  
Strong Support ◽  
Interactive Visualization ◽  
User Interaction ◽  
Efficient Integration ◽  
Exploratory Data ◽  
The Given

For many tasks of exploratory data analysis, visualization plays an important role. It is a key for efficient integration of human expertise — not only to include his background knowledge, intuition and creativity, but also his powerful pattern recognition and processing capabilities. The design goals for an optimal user interaction strongly depend on the given visualization task, but they certainly include an easy and intuitive navigation with strong support for the user’s orientation.

The Steaming Mug

2018 ◽  
pp. 1-14
Author(s):  
Kavitha Ranganathan
Keyword(s):  
Data Analysis ◽  
Business School ◽  
Exploratory Data Analysis ◽  
Introductory Course ◽  
Hands On ◽  
Exploratory Data ◽  
And Performance ◽  
Correct Path ◽  
The Given ◽  
Basic Philosophy

The case is meant to be used in an introductory course on Data Visualization or Analytics in either a business school or any other context where students have had some exposure to management topics. This case primarily focuses on introducing students to the basic philosophy and techniques of exploratory data analysis (EDA). The Steaming Mug, a US based hot beverage chain is provided as a context for engaging in a hands-on exploratory data analysis exercise to understand the strengths and weaknesses of the company's operations and performance. The learning from exploring this case will help students understand that many different insights can be drawn from the given data. The students will understand that there is no “one correct path” for this analysis. The values of getting multiple groups to present their findings is that students realise that there are many other angles that could have been explored, than the path they had gone down.

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Exploratory Data

Covid-19 Cases in India: A Visual Exploratory Data Analysis Model (Preprint)

2020 ◽  
Author(s):  
Jayesh S
Keyword(s):  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Case Fatality ◽  
Public Health Emergency ◽  
Virus Spread ◽  
Analysis Model ◽  
Case Fatality Ratio ◽  
First Case ◽  
Exploratory Data ◽  
The Government

UNSTRUCTURED Covid-19 outbreak was first reported in Wuhan, China. The deadly virus spread not just the disease, but fear around the globe. On January 2020, WHO declared COVID-19 as a Public Health Emergency of International Concern (PHEIC). First case of Covid-19 in India was reported on January 30, 2020. By the time, India was prepared in fighting against the virus. India has taken various measures to tackle the situation. In this paper, an exploratory data analysis of Covid-19 cases in India is carried out. Data namely number of cases, testing done, Case Fatality ratio, Number of deaths, change in visits stringency index and measures taken by the government is used for modelling and visual exploratory data analysis.

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