The Knowledge Exchange / Business Analytics / What is big data without big analytics?

What is big data without big analytics?

Keith Collins, SAS Senior Vice President and Chief Technology Officer

The most exciting thing in the industry right now isn’t “big data,” claims Keith Collins, senior vice president and chief technology officer at SAS—it’s “big analytics.” In this article, Collins explains the necessity of high-performance analytics for companies looking to make the most of their data.

Speaking from the perspective of somebody who’s been in this industry for many years, overcoming large data challenges has been a recurrent theme for many years. Not too long ago, we were debating the size of data that could be stored in an enterprise data warehouse (EDW). As data has continued to grow in volume, variety and velocity, we have moved onto discussing big data and its many uses. It’s not only about how big the data is. It’s about what you’re going to do with it. That’s why the exciting thing is big analytics—because it’s the analytics that help you do something with all of that data.

We’re going to start to see an amazing transformation as people understand the value of what they can do with the data they have. There’s been a real challenge as we look at the old architectures of our traditional EDWs, because those that were organized around transactions weren’t appropriate for analytics. This has been part of the heritage of SAS. We’ve known for a long time that you really have to organize the data for the way you want to get information out. Now, this theory is being validated in the era of big data. More and more people in the industry understand the importance of organizing your data in order to process it as quickly as possible.

It’s not about how big [the data] is. It’s about what you’re going to do with it. That’s why the exciting thing is big analytics because it’s the analytics that help you do something with all of that data.

Yes, it’s great that you can take a customer in retail optimizing a problem with 270 million SKU combinations from 30 hours of process time to two hours. Fantastic. The time savings is important, but what you’ve really done is provided the organization with the ability to do scenario analysis. That’s even more important.

Now the same retailer can really work to see if they have the best plan. Before, they worried about getting through the weekend so they could just have the inventory stocked through Monday. Now they can go through the simulations, and they can actually see what the different opportunities are to shift their market and get ahead of their competitors.

As this example illustrates, one of the things I’m really excited about with high-performance analytics is the focus on the next business problems to solve. Now we can ask the question, where are the bottlenecks in the organization? That’s really changing the outlook of our customers. Take the example of how many accurate models can be created. We’ve had customers that went from being able to do just 50 models to doing 1,000 models with the same staff of five analysts.

Why does that matter? Again, it’s not the speed so much as the ability to ask—and answer—20 times more questions and then change the business as a result. So now the percentage change you can make in the business—the lift in sales, the identification of the fraud, and so on—goes up. You are really having a bottom-line impact on the company.

With high-performance analytics, we’re already seeing customers change their thought processes, change their businesses and change their approach to the data.

Banks are changing how they look at risk portfolios, which allows them not just to understand risk after the fact but also as the transaction is occurring. Likewise, understanding fraud in the public sector is becoming easier. In the health care industry, we can actually do text mining across emergency medical service logs and start to identify disease outbreaks weeks earlier than we could by looking at hospital records. These are opportunities that we have now with this type of processing power.

Ultimately, you and I are going to benefit from these applications of analytics, too. Our economies are stronger when the banks have a better understanding of risk. Our taxes are lower when the government lowers its fraud expenses. And our communities are healthier when disease outbreaks are pinpointed and treated earlier.

That’s why I’m excited about high-performance analytics – and why you should be too.

Collins’ article is part of a larger SAS insights report called “Big data, bigger opportunities.” If you’re excited about high-performance analytics, download this special report and learn what you could be doing with your company’s big data.

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4 Comments

  1. Posted November 2, 2012 at 10:25 am | Permalink

    Thanks for the great post; big-data makes sense with analytics and analytics will have more weight when f-commerce and mobile commerce are used. Think mobile commerce and other retail transactions will trigger the usage of analytics.

    • Anna Brown, Editor
      Posted November 2, 2012 at 10:42 am | Permalink

      Glad you found the post interesting, Girish. And I agree, all the transactional “big” data will drive the use of analytics – oranizations won’t have a choice but to keep up with it all.

  2. Posted November 16, 2012 at 5:02 am | Permalink

    Hi,
    Your article content is quite resourceful and informative which gives valuable insights into how to manage ever growing big data. However, big data constitutes of unstructured and disconnected data. Separating and gathering useful information from the clutter or being able to identify “music” from “noise” is a big challenge anyway.
    Please visit our Blogs to share your views with us
    Thanks and Regards,
    Pia Sen,
    Marketing Manager @ Nuvento Systems Pvt Ltd

    • Anna Brown, Editor
      Posted November 19, 2012 at 9:28 am | Permalink

      Thanks for sharing, Pia. It’s always nice to know about other online channels discussing big data challenges.

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