At Every mine and mineral exploration project has its unique history, with variable data layers and metadata sources. Each project has challenges and opportunities that can be leveraged to add efficiency and clarity to historical records, e.g., paper or Excel tables.
To correctly interpret analytical data, it is necessary to understand the errors associated with sample handling, preparation, and laboratory procedures. All analytical data is subject to errors or bias (e.g. random errors vs systematic errors). Mistakes and biases can be easily corrected if a rigorous QAQC routine is established at the outset of each sample collection campaign. Garbage in, garbage out!