Are you suffering from big data chaos? #bigdata #analytics


The top funded venture capital categories are technology companies that deal with gaining insights out of data. Whether they’re a social media company or a transportation company looking for better routes to reduce fuel consumption, they are all trying to find insight into their business data.  But, no matter what new solutions are developed to track or improve a specific problem, a new problem is being created where companies are now experiencing too many data sources, leading to big data chaos.

Check out the following slide from Luma showing all the different marketing technology companies (updated March 2013). In the marketing segment alone, it’s all too clear that there is a level of big data chaos like we have never seen before. Everyone claims their solution will collaborate with your existing process, handle all the big data and guaranteeing to deliver better insight. So far we’re hearing companies are spending time, money and patience as they discover more problems and experience the same disappointing results.


The real issue is that we don’t have just one system, we have multiple systems.  Companies’ big data issues are not about the volume of data, but rather the number of data sources.  As a result, we are forced to visit numerous sources to view the built-in reporting solution to glean any insight into the performance of the business.  This provides a VERY limited perspective of data to determine the true results of a campaign, project or even daily operations.  It’s actually a HUGE productivity drain. And that is just marketing systems.

Think about how we need to integrate other lines of business data sources into an intelligence enterprise.   Today, it’s a new level of data chaos like never seen before, but not for the reasons you may think.  Data chaos doesn’t come from the volume of data, but results from the following (to name just a few):

  • numerous data and reporting solutions
  • various data storage and retrieval locations
  • technology moving faster than a company’s capital resources
  • constant change in technology upgrades

Business intelligence and analytic software companies would lead us to believe that purchasing their self-serve BI tools will fix the issue, but it often ends up making it worse, in the long run because analytics quickly become inaccurate, delayed and untrusted.


In my experience, companies are beginning to take a step back and slowing their purchasing decisions, thinking about what they actually need from the volumes of data and making sure it aligns with their strategic objectives. It is time to go back to the basics and re-think the kind of data we need to run our businesses.  We need to develop smarter data warehouses which can assist in the collection of these numerous data sources.  We need to re-think our delivery methods to mobile devices and not just provide another dashboard squished down to fit the device, but maybe just the metrics that someone cares about this month in a real-time fashion.

Regards, Patrick

Patrick Husting is a business intelligence mastermind who has guided companies like Microsoft, Intel, Gallup, HP, Dell, Honeywell, Nordstrom and Polo Ralph Lauren over the past 18 years – establishing a new way for organizations to leverage data in their business intelligence solutions.   Using his own capital, Husting created Extended Results on the premise to provide a different experience called Personal Business Intelligence, for businesses.  In just three years, Husting grew Extended Results nearly 578% in revenue, in spite of the recession. Being the CEO and founder of a leading Business Intelligence Services and Software company, Husting is revolutionizing the way companies evolve by offering business intelligence solutions to companies across numerous industries, including media/entertainment, financial services, government, health care, manufacturing, high technology, and retail with new and emerging technologies.  

For an interview or to learn more about Patrick and Extended Results please email



  1. Terrific post-you have it exactly right. Many of the companies I work with are struggling with the cost and sheer unwieldiness of “everything by everything” off the shelf applications. Don’t know if you have had the same experience, but I’ve seen companies successfully use an approach consisting of a small permanent core of data experts who build (actually mash together) custom databases for specific problems from various internal and external data sources.

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