Data Science Successes, But At What Cost?
Reports of where Data Science has successfully optimized businesses have started to flow in the mass media and social media:
- revelytix.com lists the most well-known ones, including baseball statistics, presidential campaigns, recommend systems, and others.
- A Reddit.com discussion thread lists some anonymous ones: optimizing telephone sales pitches, optimizing cinema ads, optimizing gambling minimum bets, and more.
- Ford described there use of sentiment analysis to gauge new features.
But I wonder whether any of these efforts have produced any net profit, especially if the investments into Data Science are combined with the investments into Hadoop, which has suffered from some overhype as Michael Walker was quoted in the Wall Street Journal.
Going back to my webmaster analogy, if we're at the year 2000 about now, then we may be due for a Big Data/Data Science crash soon. That doesn't mean Big Data and Data Science are worthless. It means the Pets.com's and WebVans of the Big Data and Data Science fields will be cleared and the successes we've started to see now will become repeatable, and that investments in these technologies will be made soberly. In a few years, we'll know how much to invest in Big Data and Data Science and which technologies to choose just as well as we do know now for building websites.