EN
PL
The quality of decisions made in manufacturing companies is inseparably linked to the quality of the available data. Statistical models and artificial intelligence algorithms — no matter how advanced — cannot generate meaningful insights if the input data is inconsistent, incomplete, or error-prone.
In practice, as much as 70–80% of the time in analytics projects is spent not on building models, but on preparing, cleaning, and transforming data. This stage ultimately determines whether the results obtained will be reliable and useful for business. Reliable data therefore forms the foundation of effective analysis and the basis for sound decision-making in quality assurance.
We invite you to join our webinar, where we will focus on the key data-related challenges that most often hinder effective analysis and decision-making in the area of quality. We will discuss common issues such as lack of data consistency and completeness, errors resulting from manual data entry, and difficulties in integrating data from various sources. We will also present proven methods and tools that enable efficient data organization, collection, and analysis using statistics, visualization, and artificial intelligence.
Participants will learn how to avoid the most common data pitfalls and how to turn data into a reliable source of insight into their processes. This knowledge will help them implement solutions that genuinely improve quality and production efficiency.
The event is free of charge, but the number of seats is limited.