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Robotics Process Automation and Data Analytics: Unlocking Insights Through Automation

EasyChair Preprint no. 11257

7 pagesDate: November 6, 2023


In today's rapidly evolving business landscape, organizations are constantly seeking innovative ways to gain a competitive edge. Two powerful tools that have emerged in recent years are Robotic Process Automation (RPA) and Data Analytics. RPA offers the ability to automate repetitive, rule-based tasks, while Data Analytics harnesses the power of data to extract valuable insights. When combined, these two technologies can unlock a wealth of opportunities for organizations. This paper explores the synergies between RPA and Data Analytics, highlighting how the automation of routine tasks can streamline data collection and preparation, enabling more efficient and accurate analysis. We delve into real-world case studies to demonstrate how organizations across various industries are successfully using RPA and Data Analytics to enhance their decision-making processes, reduce operational costs, and improve overall efficiency. We also discuss the key challenges and considerations in implementing RPA and Data Analytics, including data quality, security, and scalability. Moreover, we examine the role of artificial intelligence and machine learning in enhancing the capabilities of both technologies and providing predictive analytics.

Keyphrases: Automation, Business Process Automation, Robotic Process Automation

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Nikolas Emmitt and Lee Kasowaki},
  title = {Robotics Process Automation and Data Analytics: Unlocking Insights Through Automation},
  howpublished = {EasyChair Preprint no. 11257},

  year = {EasyChair, 2023}}
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