Datalogix, Complexity, TBATS, & Momos


Less than a year after the acquisition of Bluekai, Oracle acquired Datalogix.

Bluekai is the digital solution to advertising measurement, Datalogix is the offline solution. Apparently, Facebook and Twitter already are using Datalogix to measure effectiveness of their ads. And most of the data originate from loyalty card transactions. Have a look for more details.

The idea is that both Datalogix and Bluekai's data can be combined to measure advertising effectiveness.

Hence, both companies will become third-party data-enhancements that publishers (or anyone else) can purchase to determine the effectiveness of their advertising. Great synergy!


Not sure if you have noted but the trend toward "complexity" is here. It's interesting because in many respect the actual process and means seem to matter more than the applicable results.

"Complexity cost is the debt you accrue by complicating features or technologies in order to solve problems"
– Kris Gale

Now, "complexity" is often deemed necessary to achieve a competitive advantage, but many organizations get lost by way of organizational, product, systems, and code complexity. Here's a great article on the matter. Of late, we've seen many companies focused on product and system rather than insights.


Speaking of complexity, there many occasions when one data point (times series) may contain complex seasonal patterns. De Livera, Hyman, & Snyder have recently introduced a framework to deal with this issue. It basically decomposes a time series into multiple seasonality in one procedure. Want to see the full paper? Have a look here.

Want some code example? Take a look here and here.


If you’re looking for something good to eat in these cold winter months, we recommend you try some Momos. We definitely think it’s worth a listen, a look, and... of course a bite. Yummy!

Perseverance, secret of all triumphs.
-Victor Hugo.

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