Unlocking Intelligence Through Data Pipeline Re-Optimization With DataOps Approach: A Case Study in Vanderlande Project Execution

Amri, Syifa Alina (2024) Unlocking Intelligence Through Data Pipeline Re-Optimization With DataOps Approach: A Case Study in Vanderlande Project Execution. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

In the rapidly evolving landscape of data management, the adoption of DataOps principles has emerged as a transformative approach to optimizing workflows and driving intelligent decision-making processes. This thesis explores the re-optimization of data pipelines using DataOps within the Project Management Office (PMO) of Vanderlande’s APS CC EMEA-LATAM. Vanderlande, a global leader in logistic process automation, faces challenges in effectively managing and harnessing data due to a hybrid environment of legacy systems, manual processes, and emerging data-driven initiatives. The research aims to design an optimized data pipeline to enhance the accuracy and efficiency of project execution KPIs. The study assesses current data management practices, explores the applicability of DataOps principles, and develops technical deliverables to the Proof-of-Concept stage. A mixed-method approach, guided by the Development Oriented Triangulation (DOT) Framework, is employed to address the research questions. Methods include document analysis, interviews, workshops, and prototyping. Key findings indicate that current data practices are fragmented and manually intensive, leading to inefficiencies and data inconsistencies. The implementation of a centralized SQL Server database, integrated with automated data flows and a user-friendly interface, addresses these issues. The adoption of DataOps principles—automation, agility, centrality, and well-defined roles—enhances data integrity, reporting efficiency, and overall project execution. This thesis contributes to the field by demonstrating how DataOps-driven solutions can optimize data pipelines, facilitating a more intelligent and data-driven project execution environment. The results underscore the importance of continuous improvement and stakeholder collaboration in achieving effective data management.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	DataOps, Data Pipeline Optimization, Project Execution
Subjects:	T Technology > T Technology (General) > T57.5 Data Processing
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis
Depositing User:	Syifa Alina Amri
Date Deposited:	28 Aug 2024 05:49
Last Modified:	28 Aug 2024 05:49
URI:	http://repository.its.ac.id/id/eprint/114870

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