ENTRIES TAGGED "Marketing"

Big Data and Advertising: In the trenches

Volume, variety, velocity, and a rare peek inside sponsored search advertising at Google

The $35B merger of Omnicom and Publicis put the convergence of Big Data and Advertising1 in the front pages of business publications. Adtech2 companies have long been at the forefront of many data technologies, strategies, and techniques. By now it’s well-known that many impressive large scale, realtime analytics systems in production, support3 advertising. A lot of effort has gone towards accurately predicting and measuring click-through rates, so at least for online advertising, data scientists and data engineers have gone a long way towards addressing4 the famous “but we don’t know which half” line.

The industry has its share of problems: privacy & creepiness come to mind, and like other technology sectors adtech has its share of “interesting” patent filings (see for example here, here, here). With so many companies dependent on online advertising, some have lamented the industry’s hold5 on data scientists. But online advertising does offer data scientists and data engineers lots of interesting technical problems to work on, many of which involve the deployment (and creation) of open source tools for massive amounts of data.

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Three kinds of big data

Looking ahead at big data's role in enterprise business intelligence, civil engineering, and customer relationship optimization.

Photo of the columns of Castor and Pollux by OliverN5 on FlickrIn the past couple of years, marketers and pundits have spent a lot of time labeling everything¬†“big data.” The reasoning goes something like this:

  • Everything is on the Internet.
  • The Internet has a lot of data.
  • Therefore, everything is big data.

When you have a hammer, everything looks like a nail. When you have a Hadoop deployment, everything looks like big data. And if you’re trying to cloak your company in the mantle of a burgeoning industry, big data will do just fine. But seeing big data everywhere is a sure way to hasten the inevitable fall from the peak of high expectations to the trough of disillusionment.

We saw this with cloud computing. From early idealists saying everything would live in a magical, limitless, free data center to today’s pragmatism about virtualization and infrastructure, we soon took off our rose-colored glasses and put on welding goggles so we could actually build stuff.

So where will big data go to grow up?

Once we get over ourselves and start rolling up our sleeves, I think big data will fall into three major buckets: Enterprise BI, Civil Engineering, and Customer Relationship Optimization. This is where we’ll see most IT spending, most government oversight, and most early adoption in the next few years. Read more…

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Want to know where to build a new store? Check your human density data

Want to know where to build a new store? Check your human density data

Skyhook's Ted Morgan on the applications of human density data.

Ted Morgan, Skyhook co-founder and CEO, discusses the value of human density data and why it will help drive marketing, business and development decisions.

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Backtype: Using big data to make sense of social media

Nathan Marz on the data tools that help marketers understand their social media efforts.

Nathan Marz of Backtype discusses his work with Hadoop, Cascading and Clojure.

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