Shedding light on Hadoop for marketing

Learn about Hadoop if you care about Big Data.

The sun sheds light on the Great Smoky Mountains. Photo credit: Barry Butler, Chicago, IL

The recent uptick in buzz around Hadoop caught my attention, and as always, my what’s-in-it-for-me filter kicked in, so I started sniffing around. It turns out that Hadoop brings some big advantages to the world of data that we marketers depend on so much, and as a result, I think it behooves marketing to know a little bit about Hadoop.

Here’s a quick litmus test of how much you need to know about Hadoop: Do you worry about big data (or do your customers worry about big data)? If so, please read on. Do you worry a lot about big data? Then read on and click on some of the links below. If you don’t care a whit about big data, then please read on simply because you like to read my blog posts.

Hadoop addresses the 3V’s of Big Data:

Hadoop enables distributed storage of data in ways that deliver efficiencies with real cost-saving implications. Fewer resources used up in data storage means more available for business-impacting investments like analytics to drive real-time offers and marketing operations management.

Hadoop is very well suited for managing and processing huge amounts of unstructured data. That means it brings the goal of the 360-degree view of customers that much closer by allowing your team to work with a wide variety of online and offline data you might have, from campaign responses, online behavior, social media activity and more.

Hadoop allows for distributed processing of data across all the servers where your data might be stored. This removes the need for all that uploading & downloading, importing & exporting – whatever you want to call it. It shortens the time interval between the data and your decision, which can improve the quality of how you respond to customers in real-time, or even tweak your website to capitalize on a trending development.

For an engaging way to get a little more depth on Hadoop, this page includes a compelling embedded video showing 3 of my smart colleagues doing a show & tell with candy dishes, platters and M&M candies.

5 Facts to Know about Hadoop

So you are not completely left in the dark when your more technical colleagues start talking about Hadoop, here are a few handy facts to know:

  1. It is a family of open-source products and technologies overseen by the Apache Software Foundation. It’s not a product, but an ecosystem of products from Apache in addition to vendor products.
  2. Being “open source” means that anybody can take Hadoop and build on it to provide added-value services – in this case, some of the vendor products address data management issues, such as reporting, data integration and analytics.
  3. Hadoop also delivers cost savings because it allows you to use low-cost commodity hardware to reliably store large amounts of data.
  4. It has parallel processing power is scalable because its distributed computing model can be expanded by adding more nodes.
  5. It has built-in data redundancy, so if one of the servers goes down, jobs are automatically redirected to other working servers. This protects both data and application processing from hardware failure.

For even more details about Hadoop, check out this short-and-sweet “Busting 10 myths about Hadoop,” by Philip Russom of TDWI for sascom magazine.

What SAS can do for you and Hadoop:

Finally, I think it’s also important to know how SAS is different when it comes to Hadoop:

SAS not only retrieves big data stored in the Hadoop Distributed File System (HDFS), but it also allows your IT team to incorporate and use other capabilities, such as the Pig, Hive and MapReduce.

SAS is focused on analytics (not storage) and because of our heritage as a vendor-neutral solution provider, you have the ability to deploy Hadoop with other data warehouse technologies. We’ve enhanced this element of choice with strategic relationships with enterprise-grade integrated big data solutions providers, such as Cloudera.

Complete support:
SAS supports the entire analytics life cycle from data to decisions - from data preparation to model development, production, deployment and monitoring.

So I hope that shedding a little light on Hadoop for marketing has been helpful for you. To get a broader perspective on big data beyond Hadoop, visit our Big Data in Marketing page to get started. As always, thanks for following!



About Author

John Balla

Principal Marketing Strategist

Hi, I'm + John Balla. I’m a digital content strategist here at SAS, and co-founder and former Editor of this blog. I like to find and share content and experiences that open doors, answer questions and maybe even challenge assumptions so better questions can be asked. Outside of work I stay busy with my wife and I keeping up with my 2 awesome teenagers, volunteering for the Boy Scouts, keeping my garden green, striving for green living, expressing myself with puns, and making my own café con leche every morning. I’ve lived and worked on 3 contents and can communicate fluently in Spanish, Portuguese, Hungarian and passable English. Prior to SAS, my experience in marketing ranges from Fortune 100 companies to co-founding two start ups. I studied economics at the University of Illinois at Urbana-Champaign and got an MBA from Georgetown. Follow me on Twitter. Connect with me on LinkedIn.


  1. The Information was very much useful for Hadoop Online Training Learners. Thank You for Sharing Valuable Information.

  2. Brilliant piece of information, I had come to know about your web-page from my friend Hardik, Delhi, I have read at least 9 posts of yours by now, and let me tell you, your webpage gives the best and the most interesting information. This is just the kind of information that i had been looking for, I’m already your rss reader now and i would regularly watch out for the new posts, once again hats off to you! Thanx a million once again, Regards,

    • John Balla

      You're most welcome! I hope you've subscribed to the blog so it delivers all future posts to you via email.

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