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Data analysis, visualization, data quality, anomaly detection 1. INTRODUCTION Data sets regularly contain missing, extreme, duplicate or er-roneous values that can undermine the results of analysis. These anomalies come from various sources, including human data entry error, inconsistencies between integrated data sets, and sensor inter-ference. The Missing V’s in Big Data: Viability and Value. The era of Big Data is not “coming soon.”. It’s here today and it has brought both painful changes and unprecedented opportunity to ... Data/ink ratio is a concept introduced and advocated by the influential data visualization expert Edward Turfe. 1 It reflects a minimalist design of data visualization. Although not everyone may favor the principle, it helps ensure that the visualization remains uncluttered to make important information prominent.I have a data set which has incidents resolved w.r.t date. I would like to look at the trends of number of incidents resolved over the past 45 days only on a Clustered column chart.. I couldn't see entries for specific dates (because the number of incidents resolved was zero on that day).8. Data visualization and descriptive analysis Ziqian Zheng From this lab session, we start to analyze real datasets. Today, our focus is how to approach a new dataset to get an intuitive understanding. South Africa Heart Disease The data are a subset of the Coronary Risk-Factor Study (CORIS) baseline survey, carried out in three rural areas of the Western Cape, South Africa in 1983.Visualizing Missing Data Being able to plot missing values is a great way to quickly understand how much of your data is missing. It can also help highlight when variables are missing in a pattern something that will need to be handled with care lest your model be biased.