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Optimizing Data Pipeline Design for Pharmaceutical Manufacturing Analytics in Power BI

Author(s) Srikanth Reddy Katta
Country United States
Abstract In the production of drugs, analytics is critical as it enhances the quality, compliance and operation of the drug manufacturing processes to the best standards worthy of being consumed by patients. Power BI is a great tool to work with while putting the focus on visualizing the data and performing the deep data analysis, however, it's also pivotal to organize the process of the data pipeline correctly for the better performance of the values. This paper aims to review several strategies to best plan for a data-structured pipeline to support the data format structure used in the pharmaceutical manufacturing process; this includes the integration, transformation and performance. These are the factors such as the real-time and batch processing of big data sets, the regulatory requirement, for instance, Food and Drug Administration (FDA) 21 CFR part 11, among others, sophisticated analysis for predictive upkeep of machinery/equipment, and enhancing production rates, among others. I will explain techniques to work with ETL processes DAX and improve the performance of Power BI, including integration with data lakes and Microsoft Azure Synapse Analytics. In addition, we also explain the use of AI-based anomaly detection as well as the use of automated data validation. The descriptions given in the case studies reveal practical applications of the theory wherein optimising pipelines boosts reporting precision, shortens reporting delays, and increases decision-making effectiveness in pharmaceutical businesses. Consequently, by employing the above strategies, it would be possible for organizations to achieve the full potential of using Power BI in the manufacturing of pharmaceutical products, as well as enhance compliance with the legislation to foster innovation.
Keywords Pharmaceutical manufacturing, Data pipeline optimization, Power BI, ETL, Data analytics, Regulatory compliance, FDA 21 CFR Part 11, Data lakes
Field Medical / Pharmacy
Published In Volume 6, Issue 3, March 2025
Published On 2025-03-20
Cite This Optimizing Data Pipeline Design for Pharmaceutical Manufacturing Analytics in Power BI - Srikanth Reddy Katta - IJLRP Volume 6, Issue 3, March 2025. DOI 10.5281/zenodo.15125103
DOI https://doi.org/10.5281/zenodo.15125103
Short DOI https://doi.org/g9bnmg
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