Big Data // Big Data Analytics
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2/18/2014
09:06 AM
Phil Simon
Phil Simon
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Why Big Data In The Enterprise Is Mostly Lip Service

Here are six reasons organizations are taking the wrong approach to big data or not utilizing it at all.

These days, it's not hard to find surveys, polls, and reports saying that "most" organizations are embracing big data. For instance, as Matt Asay on ReadWriteWeb writes:

According to a recent Gartner report, 64% of enterprises surveyed indicate that they're deploying or planning Big Data projects. Yet even more acknowledge that they still don't know what to do with Big Data. Have the inmates officially taken over the Big Data asylum?...

That's a big jump (64% in 2013 compared to 58% in 2012), and it reflects a growing confidence that Big Data can help enhance the customer experience (54% cited this as their driving motivation), improve process efficiency (42%) and launch new products or business models (39%).

[Data analysis is a do-or-die requirement for today's businesses. Read 16 Top Big Data Analytics Platforms.]

So, slowly but surely, big data is making significant inroads in the enterprise, right?

Not so fast. I had my doubts about big-data enterprise adoption when I wrote Too Big to Ignore and, if anything, they've only solidified in the past year. For every Amazon, Apple, Facebook, Twitter, Netflix, and Google, I would wager that thousands of midsized and large organizations are doing nothing with big data beyond giving it lip service. That is, the fact that a CXO has heard of big data is hardly to the same thing as her company actually doing anything with the massive amounts of unstructured data flying at us faster than ever.

This begs two simple yet critical questions: Why the lack of adoption? And how can organizations overcome the obstacles currently impeding them?

In short, most organizations today are making one or more of the following mistakes around big data:

They are trying to ascertain the ROI of big data. That's a big mistake (pun intended). They need to embrace uncertainty and data discovery. They need to disabuse themselves of the notion that they know what they'll find. Certainty is a myth.

They don't know where to start. Sure, anyone can go to Kaggle and post a project. For a relatively small amount of money, you can crowdsource a sea of data scientists. But to fully unleash the power of big data throughout the organization, though, one needs the commitment of everyone. Digital advertising company Quantcast (covered in Too Big to Ignore) spend a great deal of financial resources to fork Apache Hadoop's distributed file system HDFS to make Hadoop even bigger, improve its performance, and meet Quantcast's specific needs. (For more on the project, click here.) Forking Hadoop in this manner certainly isn't for the faint of heart and demonstrates the executive commitment at Quantcast to big data.

They are failing to embrace new technologies. Many companies erroneously believe that traditional BI tools and relational databases can handle big data. They can't. They need to make some new investments (re: Hadoop, NoSQL databases, etc.).

They are thinking of big data as "IT projects" and, as I know all too well, organizations' batting averages with IT projects are abysmal. Healthcare.gov only differs from thousands of CRM and ERP failures by a matter of degree.

They are looking at what big-data heavyweights like Amazon, Apple, Facebook, Google, Twitter, and Netflix do and are justifiably intimidated. They are thinking that they cannot begin to do the same things. They fail to realize, however, that these companies have built their internal data management and discovery capabilities over the course of more than a decade. You don't go from zero to Google overnight.

They are confused (again, justifiably) by the incessant noise around big data. Social media has given every software vendor a "platform" to tout its wares. This is a bit self-serving, but I believe that organizations would strongly benefit from the advice of independent thought leaders with zero skin in the game.

What say you? Are you implementing big-data tools and strategies or just talking about them?

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Phil Simon is a frequent keynote speaker and recognized technology expert. He is the award-winning author of six management books, including the The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions. He consults organizations on matters ... View Full Bio

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Shane M. O'Neill
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Shane M. O'Neill,
User Rank: Author
2/18/2014 | 9:55:20 AM
All in
"To fully unleash the power of big data throughout the organization, though, one needs the commitment of everyone."

I think a lot of companies see the only way to get everybody on board with a big data mindset is to make it an IT project with an ROI number on it. Phil, how can companies overcome this potential conflict?
_philsimon
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_philsimon,
User Rank: Apprentice
2/18/2014 | 9:58:18 AM
Re: All in
Well, they can start by reading Too Big to Ignore. Kidding aside, look at Amazon, Apple, Facebook, Netflix, and Google. Those companies to the best of my knowledge put arbitrary numbers on ROI and they certainly fall victim to the project mentality.
BellaLeirTingle
IW Pick
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BellaLeirTingle,
User Rank: Apprentice
2/18/2014 | 10:38:19 AM
Re: All in
So true! They forget that the data acquired needs to be used in multiple departments, therefore to get the most out of a project like this, it needs to be collaborated upon across those departments. Not just placed in the lap of IT. BUT, how to correct this issue......well...... 
Paul Ross
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Paul Ross,
User Rank: Apprentice
2/18/2014 | 4:40:19 PM
Big Data Analytics Projects Are Delivering Value
There is no doubt that a lot has been written and talked about in relation to Big Data that does not reflect the reality in many organizations. The lack of skills to both manage new types of data, and to take advantage of that data in meaningful ways is a big blocker to success - this skill gap also includes the ability to make decisions about where to invest in Big Data. However, my experience regarding Big Data analytics at Alteryx with customers like Rentrak is that judicious use of technology that is more accessible than just coding or scripting will enable more people to get real value from these new sources of data. The second problem I see is using Big Data as an all encompassing term, when really its about organizations looking at the data they have in a new way and seeing if there is actually value to be had.
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