My name is Ufuk Baysal. I am working at BSH as a regional controller. In the future, I want to use my data science skills to create efficient solutions in a fast, automated and visualized way.
Big Brother is Watching - Using Digital Disease Surveillance Tools for Near Real-Time Forecasting
In our increasingly interconnected world, it is crucial to understand the risk of an outbreak originating in one country/region and spreading to the rest of the world. Digital disease surveillance tools such as ProMed, HealthMap etc. have the potential to serve as important early warning systems as well as complement the field surveillance data during an ongoing outbreak. While there are a number of systems that carry out digital disease surveillance, there is as yet a lack of tools that can compile and analyse the generated data to produce easily understood actionable reports. You can watch Sangeeta Bhatia’s presentation of a flexible statistical model that uses different streams of data (such as disease surveillance data, mobility data etc.) for short-term incidence trend forecasting from this link. In this presentation, you will also find a highlight of an example of disaggregating aggregated data to obtain incidence information at a fine spatial scale. This could be particularly important in instances where information at sub-national levels is lacking or incomplete. The model has been developed in R and will be made available as a R package as well as through a website for use by non-technical stakeholders.
As a regional controller at BSH, I prepare both short-term and long-term planning scenarios for decision makers and present them. The outcome of these scenarios are evaulated in strategic decisions.
Nowadays, it become more common between companies to predict future values of a time series based on historical trends. For businesses, being able quantify expected outcomes for a given time period is essential for managing marketing, planning and finances. You may find a basic non-technical introduction to forecasting in this link. This article provides you to get familiar with the key concepts and how to perform some basic forecasting in R.
In his book Blink, Malcolm Gladwell summarises a common misconception about good decision making. According to folk wisdom, the more time, information, and effort you put into a decision, the better it gets. In other words, “More is better.” However, decades of research in cognitive science and machine learning have shown that the “More is better” theory is, in many real-world decisions, flat wrong. In contrast, there are many cases where, as Dr. Gerd Gigerenzer has put it, “Less is more.” Please find “Making fast, good decisions with the FFTrees R package” article in this link.
With ever increasing volume of data, it is impossible to tell stories without visualizations. Data visualization is an art of how to turn numbers into useful knowledge. R Programming lets you learn this art by offering a set of inbuilt functions and libraries to build visualizations and present data. This article may help you how to select the right chart type and how to use these visualizations in R.