Research and applications related to data mining
Data Science automation is a hot topic recently, with several articles about it[1]. Most of them discuss the so-called “automation” tools[2]. Too often, editors claim that their tools can automate the Data Science process. This provides the feeling that combining these tools with a Big Data architecture can solve any business problems.
The misconception comes from the confusion between the whole Data Science process… Continue reading...
If you read this blog, you are very likely to be involved in any kind of data collection, manipulation or analysis. When not performed wisely, your analysis will lead you to incorrect conclusions. Alex Reinhart, in his book Statistics Done Wrong, has listed several concepts that are key when analysing data, such as statistical power, correlation/causation and publication bias.
Superforecasting – by Tetlock and Gartner – explains the huge study performed by Tetlock about the ability of people to predict future events (mainly geo-political). The closed questions (i.e. choose between yes/no) are far from real numbers you will predict in business forecasting. Tetlock discusses skills that have been identified as driving accurate forecasts. The point of the authors is that forecasting… Continue reading...
This is a guest post from Yaakov Smith.
Big data is changing the way the financial world handles client interaction. No matter what sector data analytics are employed in (IT, marketing, sales etc.), its implications are leading to a new wave of Business Intelligence (BI).
Any company that uses analytics on a daily basis will understand the ability of big data to transform customer relations and optimize management… Continue reading...
![Pageflex Persona [document: PRS0000045_00027]](http://www.dataminingblog.com/wp-content/uploads/001-Book.jpg)
While working on forecasting (understand “time series analysis”) I found several interesting and state of the art articles from Rob J. Hyndman. He is the co-author, with George Athanasopoulos of Forecasting: Principles and Practice. This is an excellent concise and comprehensive text explaining concepts behind forecasting, common algorithms and how to implement them in R (for a business… Continue reading... | 1 Comment
“You don’t need to predict the future. Just choose a future — a good future, a useful future — and make the kind of prediction that will alter human emotions and reactions in such a way that the future you predicted will be brought about. Better to make a good future than predict a bad one.”
Isaac Asimov, Prelude to Foundation
If you like hard science fiction with… Continue reading... | 1 Comment
This is a guest post from Ethan Millar.
Big data is the latest competitive advantage for businesses. Data are now woven into every industry and function across the global economy. The use of Big data will become the basis of competition and growth for businesses by enhancing the productivity and creating significant value for global economy with waste reduction and increased quality of products and services.
