How to transform big data from an obstacle into an asset

Talking about "big data" in Asia

In your organization, is “big data” an obstacle or an asset? Or is it still just a buzzword you’re trying to understand? A small group of us from SAS have spent the last week traveling to Mumbai, Singapore, Hong Kong, Seoul and Tokyo talking with business leaders about the benefits of using big data to improve their organizations.

One thing that seems to be resonating with these global business leaders is the idea that “big data” can become an asset when you apply high-performance analytics to an entire business process, not just a single application.

Let me use marketing as an example.  I’ve been browsing through this series of big data articles from, and a couple of them are really good, but I keep thinking about the fact that marketing is not an application. It is a process. If you want to take advantage of big data within marketing, you need to look at the whole business process:

  1. Explore data. Can you imagine actually looking at a billion rows of data? How can you drill down to know which variables are important or relevant? You need a visual exploration tool that allows you to look at big data using high-performance, in-memory capabilities to understand your data, discover new patterns and determine what data is relevant.
  2. Model data. Now you can feed the results from your visualizations in to models to segment customers or develop lists for specific campaigns. The results? You don’t have to plan your day around the processing time anymore. Campaign management becomes more of a collaboration between people as opposed to an all-day or all-night run before you can look at results and see if it’s good enough.
  3. Optimize the business process. This is where high-performance analytics becomes really important. It allows you sit around a table with people to collaborate on the results of processing big data. You can optimize hundreds of campaigns for millions of customers during a single meeting, instead of waiting overnight for the jobs to process.
  4. Share results. The last piece uses dashboards to make the information widely available on tablets, ipads or desktops, essentially sharing reports and making the results of your campaigns available to everyone in a format they choose. Big data doesn’t have to be confined to five or six people in the back room. Results can be distributed on the platform they are already comfortable with, so they can play with data as well in a more structured format.

If you follow this four-step process, you’ll remove obstacles associated with big data, and you can begin to link previously disparate programs together as a single process. Before you know it, these changes will make big data an asset in your organization too.

One Comment

  1. Posted July 22, 2012 at 11:47 pm | Permalink


    I admire your blog a lot but this time I am trifle puzzled. Isnt the four step method the same as for not so big data. Ideally I would love if you could include some specifics on Big Data here


    Ajay Ohri

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