Analytics in Data Centers

Nokia just bought a mobile analytics company.

Nokia to buy mobile analytics firm

by Lance Whitney

Nokia N96

Ovi on Nokia's N96 phone.

(Credit: Nokia)

Nokia announced Friday that it will acquire Motally, a small, privately held mobile analytics firm in San Francisco.

Staffed by a team of only eight people, Motally offers mobile app developers a service for tracking the usage of their software. The goal is to help developers enhance and optimize their apps by understanding how people use them.

Looking to support developers selling apps through Nokia'sOvi Store, Motally's service will be adapted to work with Symbian, MeeGo, Qt, and Java, said Nokia. But support will continue for Motally's current customers.

The mobile analytics is a hot industry.

Analytics in the data center is hidden and being done by companies you wouldn’t normally think of.

Amazon Web Services is one example of analytics being applied.  Data Analytics is in Amazon’s DNA.


Google Analytics is another example.

The one advantage Google and Amazon have is to unify the data across the company.  Most companies are defined by divisions and fiefdoms.  The more data you have the bigger insights you can discover.

A smart guy gave me the tip, Oracle has gained invaluable insights to the database community with their acquisition of MySQL.  Some of the smartest people are working on MySQL and Oracle just learned a bunch when treated MySQL as classic A/B testing Oracle vs. MySQL.

Here is a description of the A/B method applied in advertising, but it works in other places too.

What is A/B Testing and how can it help me?

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A/B Testing allows you to compare different versions of advertising content and their effectiveness at referring quality leads and customers.

Often, multiple versions of promotional content link to the same landing page on a web site. A/B Testing provides a way for you to tag each version of the promotional content, even when all versions link to the same landing page, so that you can see which ones are most effective (version A or version B). You can view data on clickthrough rates, new leads, average page depth, visitor loyalty, conversion figures, and revenue for each version of content.

A/B testing uses the variables set in your tracking URLs to compare values. Specifically, A/B testing requires the use of utm_source , utm_medium, andutm_content. (For AdWords campaigns, it is only necessary to add the 'utm_content' variable to your links. The 'source' and 'medium' variables are filled automatically by auto-tagging for AdWords campaigns.)