Enabling Interactive Visualizations in Industrial Big Data
Aguinaldo Bezerra, Vitor Greati, Vinícius Campos, Ivanovitch Silva, Luiz Affonso Guedes, Gustavo Bezerra Paz Leitão, Diego Augusto Santos Silva
Abstract
Industries are considered data rich but information poor environments. Mainly due to systems design restrictions, to the lack of adequate processing power and to a sector culture notably focused on collecting, selecting, storing and preserving historical series in on-demand access repositories, massive data generated in industrial operations is traditionally neglected (or simply took aside). This huge amount of unprocessed data resting in these repositories is a latent and rich source of information that could be used to improve industrial processes. This work then proposes an approach in which an elastic processing engine is designed to be plugged-in to currently installed industrial information infrastructure to provide it with the ability of performing visual analytics on massive industrial data. A case study where an interactive visualization application is made possible in real-world industrial data scenario of over 100 million records is presented to attest the effectiveness and potential of the proposed approach in enabling interactive visualizations to Industrial Big Data.