TRANSFORMASI DIGITAL DALAM PENGEMBANGAN PRODUK MANUFAKTUR : KEUNGGULAN DATA LAKEHOUSE SEBAGAI SOLUSI TERINTEGRASI
Abstract
Transformasi digital telah mengubah cara perusahaan manufaktur mengelola data dan mengembangkan produk mereka. Data Lakehouse, sebagai solusi arsitektur data yang inovatif, menggabungkan keunggulan Data Lake dan Data Warehouse untuk mengatasi tantangan pengelolaan data yang terstruktur dan tidak terstruktur. Penelitian ini mengeksplorasi dampak implementasi Data Lakehouse dalam mengoptimalkan pengembangan produk dan kolaborasi antar departemen di industri manufaktur, dengan studi kasus dari Procter & Gamble (P&G), Shell, Comcast, dan ABB. Hasil penelitian menunjukkan pengurangan siklus pengembangan produk hingga 40% dan peningkatan efisiensi kolaborasi lintas tim sebesar 60%. Penelitian ini menyimpulkan bahwa Data Lakehouse merupakan solusi yang kuat untuk mempercepat pengembangan produk dalam industri yang semakin terdisrupsi oleh teknologi digital.
References
Acker, Thomas, et al. Data Management and Analytics for Industry 4.0: Challenges and Opportunities. Springer, 2018. “ABB Reduces Costs with IoT and Azure Databricks.” Microsoft Azure, 2024, www.azure.microsoft.com/en-us/case-studies/abb/.
Choi, Sungjin, and Hyunjeong Hwang. “Cybersecurity Challenges in Data Integration for Industry 4.0.” Journal of Information Security and Applications, vol. 56, 2021, pp. 1-12.
Comcast Enhances Customer Retention with Lakehouse Analytics. Databricks, 2023, www.databricks.com/customers/comcast.
Deloitte. The Transformation of Data and Analytics in Manufacturing. Deloitte Insights, 2022, www.deloitte.com/global/en/insights/manufacturing-data-transformation.
Forrester Research. Data Management Trends in the Digital Transformation Era. Forrester, 2021.
Gartner. The Financial Impact of Data Integration Platforms in Manufacturing. Gartner Research, 2023.
Henschen, Doug. “Data Lakehouse: An Emerging Data Architecture for Analytics.” InformationWeek, 2021, www.informationweek.com/data-lakehouse-architecture.
Hu, Ling, et al. “Accelerating Product Development Through Data Integration.” Journal of Manufacturing Systems, vol. 61, 2022, pp. 205-217.
IBM Security. The Cost of Data Breach Report. IBM, 2023, www.ibm.com/security/data-breach.
IDC. Data Lakehouse in the Future of Manufacturing. IDC Insights, 2023.
Inmon, Bill, and Linstedt, Dan. Building the Data Lakehouse: A Complete Guide to Data Warehousing and Data Lake Integration. Morgan Kaufmann, 2015.
Jarke, Matthias, et al. Data Management for Modern Manufacturing. Wiley, 2020.
Khan, Yusuf, et al. “Overcoming Data Fragmentation Challenges with Data Lakehouse.” International Journal of Data Engineering, vol. 37, no. 4, 2021, pp. 301-312.
Kim, Jihoon, and Minseok Kim. “Collaborative Data Management in Manufacturing.” Journal of Industrial Information Integration, vol. 17, 2020, pp. 100-107.
Kumar, Anil, et al. “Digital Transformation and Data Management in Manufacturing.” McKinsey & Company Insights, 2022, www.mckinsey.com/industries/manufacturing.
“Microsoft Azure’s Shell Digital Transformation with Azure Databricks.” Microsoft Azure, 2023, www.azure.microsoft.com/en-us/case-studies/shell.
Mohan, Ravi, et al. “Optimizing Team Collaboration with Integrated Data Platforms.” Technology Innovation Management Review, vol. 12, no. 2, 2022, pp. 45-58.
Morgan, Alice, et al. Collaborative Data Integration: A New Era in Manufacturing. MIT Press, 2021.
“Procter & Gamble Boosts Decision Speed with Lakehouse Platform.” Databricks, 2023, www.databricks.com/customers/procter-gamble.
PwC. Industry 4.0: The Digital Revolution in Manufacturing. PwC Insights, 2022, www.pwc.com/industry-4.0.
Rosenberg, Alex. Data Analytics for Accelerated Product Development. Routledge, 2021.
Sharma, Ravi, and Praveen Kumar. “Handling Big Data in IoT and Automation for Manufacturing.” International Journal of Advanced Manufacturing Technology, vol. 123, 2023, pp. 205-217.
Siemens. Data Integration and Management in Manufacturing: A Practical Guide. Siemens, 2023.
Sullivan, James, and Robert James. Technical Training for Data Management in Industry. Routledge, 2021.
Thornton, Lewis, et al. “Case Studies on Reducing Development Cycles through Data Integration.” Manufacturing Science Journal, vol. 30, no. 1, 2022, pp. 60-75.
Wang, Ling, and Jie Sun. “Collaborative Data Analysis in Manufacturing.” International Journal of Industrial Engineering and Management, vol. 56, 2023, pp. 123-145.
Warden, Kevin. Data Lakes and Warehouses: Integration and Best Practices. Springer, 2020.
Wells, Aaron, et al. “Cost Optimization with Data Lakehouse Implementation.” Journal of Manufacturing and Technology Management, vol. 34, 2023, pp. 90-102.
Zorica, Milos, et al. “Real-Time Analytics in Product Development.” Journal of Data Science and Engineering, vol. 8, 2023, pp. 25-39.
Zulkarnaen, W., Fitriani, I., & Yuningsih, N. (2020). Pengembangan Supply Chain Management Dalam Pengelolaan Distribusi Logistik Pemilu Yang Lebih Tepat Jenis, Tepat Jumlah Dan Tepat Waktu Berbasis Human Resources Competency Development Di KPU Jawa Barat. Jurnal Ilmiah MEA (Manajemen, Ekonomi, & Akuntansi), 4(2), 222-243. https://doi.org/10.31955/mea.vol4.iss2.pp222-243.
Choi, Sungjin, and Hyunjeong Hwang. “Cybersecurity Challenges in Data Integration for Industry 4.0.” Journal of Information Security and Applications, vol. 56, 2021, pp. 1-12.
Comcast Enhances Customer Retention with Lakehouse Analytics. Databricks, 2023, www.databricks.com/customers/comcast.
Deloitte. The Transformation of Data and Analytics in Manufacturing. Deloitte Insights, 2022, www.deloitte.com/global/en/insights/manufacturing-data-transformation.
Forrester Research. Data Management Trends in the Digital Transformation Era. Forrester, 2021.
Gartner. The Financial Impact of Data Integration Platforms in Manufacturing. Gartner Research, 2023.
Henschen, Doug. “Data Lakehouse: An Emerging Data Architecture for Analytics.” InformationWeek, 2021, www.informationweek.com/data-lakehouse-architecture.
Hu, Ling, et al. “Accelerating Product Development Through Data Integration.” Journal of Manufacturing Systems, vol. 61, 2022, pp. 205-217.
IBM Security. The Cost of Data Breach Report. IBM, 2023, www.ibm.com/security/data-breach.
IDC. Data Lakehouse in the Future of Manufacturing. IDC Insights, 2023.
Inmon, Bill, and Linstedt, Dan. Building the Data Lakehouse: A Complete Guide to Data Warehousing and Data Lake Integration. Morgan Kaufmann, 2015.
Jarke, Matthias, et al. Data Management for Modern Manufacturing. Wiley, 2020.
Khan, Yusuf, et al. “Overcoming Data Fragmentation Challenges with Data Lakehouse.” International Journal of Data Engineering, vol. 37, no. 4, 2021, pp. 301-312.
Kim, Jihoon, and Minseok Kim. “Collaborative Data Management in Manufacturing.” Journal of Industrial Information Integration, vol. 17, 2020, pp. 100-107.
Kumar, Anil, et al. “Digital Transformation and Data Management in Manufacturing.” McKinsey & Company Insights, 2022, www.mckinsey.com/industries/manufacturing.
“Microsoft Azure’s Shell Digital Transformation with Azure Databricks.” Microsoft Azure, 2023, www.azure.microsoft.com/en-us/case-studies/shell.
Mohan, Ravi, et al. “Optimizing Team Collaboration with Integrated Data Platforms.” Technology Innovation Management Review, vol. 12, no. 2, 2022, pp. 45-58.
Morgan, Alice, et al. Collaborative Data Integration: A New Era in Manufacturing. MIT Press, 2021.
“Procter & Gamble Boosts Decision Speed with Lakehouse Platform.” Databricks, 2023, www.databricks.com/customers/procter-gamble.
PwC. Industry 4.0: The Digital Revolution in Manufacturing. PwC Insights, 2022, www.pwc.com/industry-4.0.
Rosenberg, Alex. Data Analytics for Accelerated Product Development. Routledge, 2021.
Sharma, Ravi, and Praveen Kumar. “Handling Big Data in IoT and Automation for Manufacturing.” International Journal of Advanced Manufacturing Technology, vol. 123, 2023, pp. 205-217.
Siemens. Data Integration and Management in Manufacturing: A Practical Guide. Siemens, 2023.
Sullivan, James, and Robert James. Technical Training for Data Management in Industry. Routledge, 2021.
Thornton, Lewis, et al. “Case Studies on Reducing Development Cycles through Data Integration.” Manufacturing Science Journal, vol. 30, no. 1, 2022, pp. 60-75.
Wang, Ling, and Jie Sun. “Collaborative Data Analysis in Manufacturing.” International Journal of Industrial Engineering and Management, vol. 56, 2023, pp. 123-145.
Warden, Kevin. Data Lakes and Warehouses: Integration and Best Practices. Springer, 2020.
Wells, Aaron, et al. “Cost Optimization with Data Lakehouse Implementation.” Journal of Manufacturing and Technology Management, vol. 34, 2023, pp. 90-102.
Zorica, Milos, et al. “Real-Time Analytics in Product Development.” Journal of Data Science and Engineering, vol. 8, 2023, pp. 25-39.
Zulkarnaen, W., Fitriani, I., & Yuningsih, N. (2020). Pengembangan Supply Chain Management Dalam Pengelolaan Distribusi Logistik Pemilu Yang Lebih Tepat Jenis, Tepat Jumlah Dan Tepat Waktu Berbasis Human Resources Competency Development Di KPU Jawa Barat. Jurnal Ilmiah MEA (Manajemen, Ekonomi, & Akuntansi), 4(2), 222-243. https://doi.org/10.31955/mea.vol4.iss2.pp222-243.
Published
2024-12-31
How to Cite
Rumanto, Y., Susilawati, Y., Maslahah, U., Yusuf, Y., & Achsan, H. (2024). TRANSFORMASI DIGITAL DALAM PENGEMBANGAN PRODUK MANUFAKTUR : KEUNGGULAN DATA LAKEHOUSE SEBAGAI SOLUSI TERINTEGRASI. Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA), 8(3), 3084-3098. https://doi.org/10.31955/mea.v8i3.4829
Section
Articles
Copyright (c) 2024 Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
