Data Wrangling and Visualization for Credibility and Usability

In recent times of data driven world, where data is all around us, the difficulty is how to make meaning out of this huge and growing data .Irrespective of improvements in technologies to work with data, data analysts still spend allot of time analyzing data quality related issues and how to make data credible and usable for effective decision making. Nonetheless the process of ‘data wrangling’ is often very cumbersome, time-consuming and requires a lot of resource. Data Wrangling encompasses just modifying and cleaning data to provide user an interactive and efficient data, but is a method which has data identification, extracting, cleaning and integrating data for a dataset which would be analyzed as needed. This article, seeks to look at the challenges and opportunities related with how data credibility can be achieved through new interactive systems that integrate data verification, transformation and visualization with the aim of maximizing the quality of data. The under listed research questions have been captured, including how appropriate visualization can facilitate the apprehension of missing data, inconsistent data and uncertainty; how interactive visualizations might facilitate data transformed specification; finally, how documented and social interaction can enable wider reuse, verification, and modification of data transformations.