Data integration is becoming a standard practice in all businesses. Protected, controlled, converted, useful, and agile data are all requirements. The technique of collaborating with people, processes, suppliers, and technologies to gather, reconcile, and make better use of data from various sources for decision support is known as big data integration. Volume, velocity, veracity, variability, value, and visualization are all features of big data. Any Big Data project must include a stage called Big Data Integration. However, there are a few things to consider. Big Data Integration, in general, is the process of combining data from a range of diverse sources and software formats, and then providing users with a translated and unified picture of the resulting data. For all of the data collected, big data integration and processing are critical. Data must have value in order to support the final outcome of its use.
Title : Pharmacogenomics: current status and future directions
Matthias Schwab, University of Tübingen, Germany
Title : Monitoring Folds Localization in ultra-thin Transition Metal Dichalcogenides using Optical Harmonic Generation
Ahmed Raza Khan, Australian National University, Australia