Cleanroom monitoring: How to make the most of your data
Our latest article, published by Cleanroom Technologies, outlines the DIKUW hierarchy; this is a framework we use here at Microgenetics - consisting of just five steps (data, information, knowledge, understanding and wisdom) - to help us think about data and generate useful insights.
“Imagine you’re a Quality Control manager, and your job is to maintain the cleanliness of a cleanroom. For this, you collect data about the site: you layout settle plates, place contact plates, conduct finger dabs, and take air samples, and you keep records of all this data.
This data-collection process becomes more sophisticated as time goes by; you record which operator worked in which room and when, and store this in the database. This information is known as meta-data: data about the data.
Next, you collect more meta-data, this time about the conditions of the room itself: you record the temperature, humidity and air pressure, measured at various intervals throughout the day. This information is stored in a spreadsheet or database so that it’s easy to access, and you believe you have an accurate picture of what’s going on in your cleanrooms.
You also have the task of drawing out insights from the data. But where to begin? Your database is so vast it’s dizzying. You’re drowning in data.”
Sound familiar? Click here to read the full article.