This is the start of our series of articles on visualisations useful in minerals processing analytics.
To receive the whole article series as a pdf now, please follow this link: www.clarofy.ai/download
Analytics and analytical workflows are an iterative process in making a hypothesis, forming it into a driving question, building visuals, analytical workflows and modelling to answer those questions. Interlate have found that, in general, our workflows follow these steps, often jumping back to step 2 as we learn more about the data and the transformations that are required.
- Connection with/extraction of the data
- Preparation and filtering of the data
- Modelling (if required)
One of the most important tools in doing this successfully is visualisations, and the role they play in exploration and evaluation. These may be simple, like scatter plots & histograms or through to more complex constructions such as heatmaps. They are the primary means of getting a conceptual understanding of the data and our plant. As well as delivering that understanding to others.
Critical in exploring the data and significantly useful in evaluation; insight gained from visualisations inform the whole analytical workflow. Some types of visualisations lend themselves better to one use over the other and, making the decision of which to use in each application is a learning process. At Interlate, our experience with analytics in Minerals processing plants has given us an appreciation for how to make these decisions, and we will outline some of our insights in the following sections.
This is article 1/7 in our series will focussing on our key visualisations, Interlate hope to share our experience to others and provide a robust understanding for their place in Clarofy our visualisation and data analytics application. No software installation required and runs straight from your browser www.clarofy.ai
Keep your eyes on this space for the next articles from the series.