Multi-Structured Data: The New Innovation Opportunity - InformationWeek

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Data Management // Big Data Analytics
09:06 AM
Ben Werther
Ben Werther

Multi-Structured Data: The New Innovation Opportunity

Multi-structured data sets come in dozens of formats and reside in non-transactional systems such as sensors and customer interaction streams. Are you harnessing their power?

Remember when Nicholas Carr declared in 2003 that you can't innovate with IT?  Today, I'll argue that you can no longer innovate with most of the data you're currently analyzing, because you're not really analyzing it at all.

More specifically, I'm talking about the commoditized information every organization has siloed inside its business intelligence, financial, and CRM systems -- just to name a few. When it comes to modern analytics, the most significant opportunities come from breaking down data silos to provide a holistic view of enterprise data.

This is just one part of the innovation opportunity, though. Just as critical is figuring out how to harness the big, unruly multi-structured data sets that result from breaking down the silos. These data sets come in dozens of formats and reside in non-transactional systems such as machines, sensors, and customer interaction streams. Not only are the systems varied, they're producing data at volumes, varieties, and velocities like we've never seen.

This knowledge isn't new. We've actually had multi-structured data for a long time, but very few organizations could work with it before because it is so expensive to store and so hard to wrangle using the traditional data warehousing model. Last year, Gartner estimated that 85% of the Fortune 500 will remain unable to exploit big data through 2015.

[How will big data change your searches? Read Web Search, Transformed: Looking Out For You.]

There is good news on the horizon. Two significant breakthroughs are quickly evolving the capabilities of multi-structured data:

  1. Less expensive, centralized storage and processing of multi-structured data in Hadoop.
  2. Exponentially more powerful analytics applications that improve analyst productivity.

Today, if you're using platforms that can analyze multi-structured data, most of the IT-centric data preparation steps and support requirements can be eliminated. You can be more flexible and go all the way down to raw data, empowering analysts to work iteratively against 100% of their data, no longer forced to make big data "small" through months of painstaking up-front work.

It's now possible for an analyst to work with the full "iceberg" of data, enabling a level of self-service that dramatically accelerates productivity. The modern analyst workflow is self-driven and iterative, so that questions are asked and insights can be gained in hours instead of months. As proof, look no further than the world's most analytics-driven companies such as Disney, Cox Automotive, FedEx, and Riot Games (creators of one of the world's most popular online games, League of Legends). These companies are touting successes in using new and complex data sets to find once undiscoverable patterns in cross-channel customer behavior, product experience, fraud, and cyber security, among other areas.

Three big-data opportunities to seize now
So now you must be asking, "What would harnessing multi-structured data look like at my company?"

When analysts can complete tasks in much shorter timeframes, a new analytics culture emerges, which has a quickening effect on innovation that extends all the way to the C-suite. All of a sudden, you don't need to allocate huge budgets just to build and change a complex data model several times

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Ben Werther launched Platfora to transform the way businesses use big-data analytics. Under his leadership, Platfora has become a leader in big-data analytics. Before founding Platfora, Ben was Vice President of Products for DataStax, where he shaped the company's enterprise ... View Full Bio
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User Rank: Ninja
12/9/2014 | 2:29:19 PM
Opportunity knocks
Great post. When it comes to data, there are so many avenues of opportunity. According to a recent IDG survey, organizations have significant interest in leveraging multiple data sources, yet most haven't taken the step beyond interest level. I think this just demonstrates that the market is still maturing. 


Peter Fretty, IDG blogger working on behalf of SAS
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