Using Data Science to Eliminate Your Fear of Bad Data for Predictive Asset Management

When it comes to data quality, we are all familiar with the term “garbage in, garbage out.” But with the plethora of data available today, distinguishing good data from bad can be challenging. 

While invaluable, the manual scrutiny of data by humans is often hindered by time and resource constraints, making it impractical for a comprehensive analysis. To address this challenge, you can embrace data science to help prioritize human focus, offload mundane tasks, and ensure effective resource allocation. 

In this webinar, Dr. Andrew Waters and Kevin Birkby discuss a straightforward approach to building trust in your data. Additionally, they address the challenge of extracting actual value from your data, explore how integrating data science methodologies can transform this process, avoid dismissing valuable insights, and showcase several compelling case studies.  

After this webinar, you will understand how to perform a data health assessment and incorporate data science into their reliability resource toolkit to enhance predictive asset management strategies, eliminate manual efforts, and unlock the full potential of data-driven decision-making.