Leveraging FME for Modernizing Legacy Batch Jobs Handling Spatial Data
Abstract: Legacy batch jobs handling spatial data often rely on outdated technologies and inefficiencies. Modernization efforts require robust tools that can seamlessly integrate with existing workflows while offering advanced spatial data processing capabilities. This article explores how FME (Feature Manipulation Engine) can be leveraged to effectively modernize legacy batch jobs involving spatial data. We delve into FME's core functionalities, highlighting its strengths in data format translation, spatial transformations, and data quality checks. By incorporating FME into the modernization process, organizations can streamline spatial data workflows, enhance data quality, and achieve greater operational efficiency.
Keywords: Spatial data, legacy batch jobs, Feature Manipulation Engine, FME, data format translation, spatial transformations, data quality checks, workflow automation, geospatial data processing, data integration, data validation, spatial data analysis, geospatial analytics, coordinate system reprojection, data filtering, feature selection, geometric calculations, feature generalization, data standardization, data harmonization, visual programming, batch processing, parallel processing
How to Cite?: Vijayasekhar Duvvur, "Leveraging FME for Modernizing Legacy Batch Jobs Handling Spatial Data", Volume 8 Issue 2, February 2019, International Journal of Science and Research (IJSR), Pages: 2359-2360, https://www.ijsr.net/getabstract.php?paperid=SR24517174146, DOI: https://dx.doi.org/10.21275/SR24517174146