Global Journal of Computer Science and Technology, C: Software & Data Engineering, Volume 22 Issue 2

f) Deployment The satisfactory results from the pilot of credit card campaigns allow the Big Data environment to be deployed to other initiatives of the transformation plan, reason for this, committees are formed between the Project Management and Engineering area for developing the projects according to the profitability, complexity and impact will be realized in the Big Data environment. The work from the Solution Architects becomes relevant when they design a document with the architectural solution model for the different use cases, this global guideline helps in the elaboration from the technical and functional designs and the own ingest implementations in the Data Lake. These solutions involve all the layers of a software development such as services or the front end, so these solution architects rely on data architects to suggest specific solution alternatives in the Data Lake or outside of it. The architecture, data scientist and engineering communities are made available with the aim of sharing experience with other countries where the financial institution also operates. This communication reinforces the good practices established and the recommendations for initiatives. g) Reliability and Research Once the big data environment is performed, more projects and more users progressively consume it, which contributes to the formalization of a platform support front is crucial for the stability of a continuous work environment and the reliability of a platform (Nachiappan et al. , 2017). This support team was initially centralized for Latin America where the infrastructure of all the countries is located, but soon after, it was decentralized to the different regions providing the Engineering teams autonomy to provide access to files in sandboxes, user registrations, creation of development environments for developers, and creation of sandboxes; This autonomy improved the perception from the quality of internal services by Architecture and Engineering because the scaling of capacities is better in a distributed environment like in the case of Big Data, unlike current systems where Engineering was always an obstacle, for example increased storage. As time goes by, new pieces come to join the Big Data environment and others to replace, in the case of Nexus by JFrog Artifactory (as a repository from configuration artifacts) or new libraries for data ingestion in the Data Lake or for measuring the quality from data in the same Data Lake; For this, Arquitectura de Datos continues with its component validation work, ensuring the correct use of each piece of the Big Data environment that comes from Spain. The productive batch will grow while the projects and initiatives will increase, for this, the reliability of Engineering area ensures the reliability from the meshes in Control M, considering direct communication with us, the architecture team and the infrastructure commissions in Mexico. Finally, the Big Data environment is constantly monitored locally and globally through strategic KPIs, which involves resource consumption (cpus, memory and disk), user accesses, incidence analysis and monitoring of governed objects. Figure 8: Example of Monitoring of the Environment Integration of the Big Data Environment in a Financial Sector Entity to Optimize Products, Services and Decision-Making Global Journal of Computer Science and Technology Volume XXII Issue II Version I 47 Year 2022 ( ) C © 2022 Global Journals For obtaining this data, we support on tools for continuous monitoring of cores, users, memory, etc., of our Big Data environment which is in continuous evolution.