Data is everywhere in our new interconnected global world. It is captured in almost every aspect of our lives — groceries we purchase, websites we visit and opinions we share. As the importance of the data continues to growth so does the use of this data by organizations to better understand their customers, optimize their promotions, and much more.
Business and Data analysts have become the main driving force to answer more complex business questions.
Many analysts find it difficult to address this new data challenge because their traditional tools and approaches are not efficient enough to handle this new situation. Utilizing spreadsheets like Excel, manual processes and custom scripting are all too time-consuming and complicated in the face of the number of ad-hoc requests that analysts receive each day. …
Decomposition of growth into S-shaped logistic components also known as Loglet-analysis is a better predictor for the covid-19 spread, as it takes into account the evolution of multiple waves.
In the last article we showed how to make a forecast for the next 30 days using covid data from the Johns Hopkins Institute with KNIME, Jupyter and Tableau. The projections were optimized for a logistic growth model. We will show that the decomposition of growth into S-shaped logistic components also known as Loglet analysis, is more accurate as it takes into account the evolution of multiple covid waves.
The term “Loglet”, coined at The Rockefeller University in 1994 joins “logistic” and “wavelet”. The Loglet analysis is interesting because it can handle multi-peak profiles which is a common challenge for curve fitting techniques. …
While the USA is already in the midst of the third covid19 wave, Austria has just declared the second lockdown.