Enabling Intelligent Decision Making and Optimization in Enterprises through Data Pipelines

Enabling Intelligent Decision Making and Optimization in Enterprises through Data Pipelines

Authors

  • Chunhe Ni Computer Science, University of Texas at Dallas, Richardson, TX, USA
  • Chenwei Zhang Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
  • Wenran Lu Electrical Engineering, University of Texas at Austin, Austin, TX, USA
  • Hongbo Wang Computer Science, University of Southern California, Los Angeles, CA, USA
  • Jiang Wu Computer Science, University of Southern California, Los Angeles, CA, USA

DOI:

https://doi.org/10.53469/wjimt.2024.07(02).13

Keywords:

Data pipelines, Intelligent decision-making, Data cleaning, Data analysis

Abstract

This article explores the pivotal role of data pipelines in driving intelligent decision-making and optimization within manufacturing enterprises. It delves into the transformative potential of technologies such as the Internet of Things (IoT), big data analytics, and artificial intelligence (AI) in revolutionizing operations. By seamlessly integrating diverse data sources through intricate pipeline networks, enterprises can gain invaluable insights into market dynamics, consumer preferences, and operational efficiencies. Real-time data processing capabilities empower enterprises to dynamically adjust production processes, anticipate demand fluctuations, and optimize resource allocation, leading to significant improvements in efficiency, quality, and competitiveness. The article emphasizes the importance of establishing a sound data infrastructure, cultivating data analysis talents, developing data governance policies, promoting a data-driven decision-making culture, and continuously optimizing data application scenarios. Through methodologies like data cleaning, improving accuracy, ensuring consistency, and enhancing efficiency, enterprises can harness the full potential of data to achieve sustainable growth and competitive advantage in today's digital age.

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Published

2024-04-15
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