Data Science Book Review: Superforecasting

June 18, 2017 by · Leave a Comment
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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 is a skill which can be improved. Superforecasters are accurate thanks to various good practices: they split the problem, update their forecast frequently, are objective, learn from their past errors, etc.

To be fair, the book title should be “Superforecasters”. Indeed, the book is about these common people that have the ability to forecast more accurately than the rest of the crowd, and even experts. This also means that the book is not about forecasting. It doesn’t cover any topic related to forecasting, in the sense of time series analysis. (ESM, ARIMA, etc.) nor business forecasting (forecast horizon, update frequency, etc.)

Tetlock and Gardner cover a wide range of topics in their book. They discuss the imprecision in language when discussing forecasts, which make them ambiguous to verify. Even when using precise numbers, forecasts are often misinterpreted. An excellent example is the “70% chance of rain tomorrow”. When it is not raining the day after, people believe the forecast was wrong. Such conclusions are not valid when looking at only one event.

I wasn’t a big fan of Chapter 10 which was too historical. Beside this chapter, the book is a real pleasure to read. In conclusions, Tetlock and Gartner book is an excellent summary of Tetlock’s comprehensive research on the people ability to forecast. Not related to business forecasting, the book explains the skills you need to have to correctly answer geo-political questions. Superforecasting is a must have to understand psychological aspects behind (good) decision making and issues related to sharing and understanding forecasts.

 

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What Could Big Data Mean for Debt Management?

January 6, 2017 by · Leave a Comment
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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...

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Data Science Book Review: Forecasting

November 22, 2016 by · 1 Comment
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Pageflex Persona [document: PRS0000045_00027]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

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Asimov, Psychohistory and Predictive Analytics

November 11, 2016 by · 1 Comment
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“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

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Top 5 Benefits Serve By Big Data To The Businesses

November 2, 2016 by · 7 Comments
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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.

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Data Scientist: Why it may be the best career after college

October 27, 2016 by · 1 Comment
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This infographic is proposed by Sandipan Pal.

Finally, the day has arrived.

After years of teaming up for group studies, setting goals and planning to fare better than your competition, you have achieved it.

Topped your grades and now waiting to make a mark in your field.

But, how do you make a mark?

Easier said than done, isn’t it?

Traditionally, it would mean… Continue reading... | 1 Comment

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How Analytics tools are shaping the growth story across industries

September 20, 2016 by · 4 Comments
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Today’s guest post is written by Mohammad Farooq

If there’s one thing that businesses across all industries have in common today, it’s in their increased adoption of data to shape business decisions. Below is a demonstration of how key industries use analytics tools and the benefits these tools have in solving challenges of data capture and use to shape growth.

Insurance

Traditionally, insurers have relied on manual sampling of… Continue reading... | 4 Comments

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