Empowering better decision making

The quality of an organization’s decision-making depends on the quality of its data—and organizations that make efforts to improve data quality see tremendous benefit. One economic impact study from Forrester found that keeping models accurate over time helped increase total profits anywhere from $4.1 million to $15.6 million while reducing model monitoring efforts by 35-50%.

Monitoring machine learning models will enable you to analyze the accuracy of predictions, eliminate prediction errors, and tweak models to ensure the best performance—ultimately helping you make better decisions. 

Read this whitepaper to understand:

  • Why model monitoring is important 
  • Approaches to monitor drift
  • How Fosfor Refract helps optimize model monitoring

Get the whitepaper

Harnessing the power of Lumin and Streamlit in Snowflake: From Data Exploration, Visualization to Decision Intelligence

As a data enthusiast myself, I understand the importance of data exploration, visualization, and decision intelligence in today's data driven world. That is why I am thrilled to share with you how Lumin and Streamlit can revolutionize your data analysis experience in Snowflake, the leading cloud-based data warehouse platform. So, fasten your seatbelts as we embark on a journey to harness the true power of Lumin and Streamlit to unlock the potential of your data.

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Considering that more people are becoming tech-savvy, enterprises need to focus on data and derive actionable insights as quickly as possible.

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Although according to a 2020 McKinsey study1, 50% of the companies surveyed had already adopted AI in at least one business function, the state of AI in 2023 according to a similar McKinsey study suggests that adoption rates have effectively plateaued over the last 3 years2.

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