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Data Management // Big Data Analytics
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1/22/2016
09:05 AM
Lisa Morgan
Lisa Morgan
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8 Ways To Monetize Data

Data may be a company's most valuable asset, but few are maximizing its economic benefit. Here eight ways that organizations are deriving real, bottom-line value from their data.
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(Image: Geralt via Pixabay)

(Image: Geralt via Pixabay)

Data is the new currency. Armed with it, new companies are disrupting established industries, and traditional businesses are transforming the way they operate. Not all organizations are equally adept at translating data into dollars, but their ability to do so is impacting their ability to compete.

"Where knowledge is power, data is wealth. It's not intrinsic in the data, it's what you do with it," said Bruce Daley, an analyst at market intelligence firm Tractica and author of Where Data Is Wealth: Profiting From Data Storage in a Digital Society. "The companies that are most progressive in thinking about data differently are the companies that are changing the economy, like Google and Uber. Most businesses lag way behind in terms of the idea that data could be their primary reason for being."

Some businesses, such as information service providers, have always been about deriving value from data. However, the ability to use and monetize data is now impacting almost every type of business. As a result, driving value from data must now be contemplated as part an overall business strategy.

[Read about machine learning and AI trends for 2016.]

"The organizations that are doing this well are trying to address a business problem at hand, not a data problem at hand," said Dan DiFilippo, global & US data and analytics leader at PricewaterhouseCoopers (PwC), in an interview. "You have to look at the problem you're trying to solve, whether that's expanding into a new market, trying to leverage more from existing customers, or acquiring new customers or employees. Then you can start looking at how data plays into to that."

Most organizations realize they have a wealth of data -- but not all of them are able to realize its potential value because technological and cultural challenges often stand in the way. Even though more lines of business are better at leveraging their data for their own purposes than they once were, the value of the data from an enterprise perspective may not yet be fully realized. Data quality issues are common. In addition, compliance, privacy, and security issues may limit the ways in which the data can be used.

"I think the piece a lot of folks miss is: You need to understand the business so you can understand the value of the data and then [you can] monetize it," said Young Bang, VP of the civil health business at Booz Allen Hamilton, in an interview.

Here are some ways to positively impact the bottom line using data.

Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include ... View Full Bio

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soozyg
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soozyg,
User Rank: Ninja
1/24/2016 | 1:58:31 PM
Re: Sysiphean work
what is called Big Data is mostly worthless.

Well, it can be worthless out of context. When companies use Big Data correctly, they start with a purpose and plan and then use Big Data to support the plan. Companies that collect data without already knowing how they are applying it are making it worthless.
jagibbons
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jagibbons,
User Rank: Ninja
1/26/2016 | 9:35:15 AM
Re: Sysiphean work
Companies that collect data without already knowing how they are applying it are making it worthless.

It could even be worse that worthless. If you have enough data, the systems analyzing that data will find patterns that appear significant but don't really mean anything. There are countless naturally correlations that have no causal relationship. Making a decision based on one of those faulty assumptions can be hugely detrimental to the business.
soozyg
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soozyg,
User Rank: Ninja
2/6/2016 | 1:20:38 PM
Re: Sysiphean work
@jagibbons what do you mean by this?

There are countless naturally correlations that have no causal relationship.
jagibbons
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jagibbons,
User Rank: Ninja
2/6/2016 | 1:39:00 PM
Re: Sysiphean work
When looking at large data sets, there will be patterns that appear to be there but don't mean anything. Even if a pattern is somewhat consistent but the variables don't have a cause and effect relationship, you can't use them to make business decisions. That is a trap of big data and algorithm analysis. Look up the Parable of Google Flu to see how computer date analysis can lead to misleading results.
soozyg
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soozyg,
User Rank: Ninja
2/6/2016 | 3:22:58 PM
Re: Sysiphean work
Even if a pattern is somewhat consistent but the variables don't have a cause and effect relationship, you can't use them to make business decisions.

And you can see the cause and effect in the data?
jagibbons
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jagibbons,
User Rank: Ninja
2/6/2016 | 4:09:19 PM
Re: Sysiphean work
That's the problem with analyzing only raw data points using algorithms. You can only see patterns, not what those patterns might mean. Causation requires experience and logic to think about whether one action really can reliably affect another. That's the human part of the process. We ask, "Does this really make sense?" Or are both correlated items really the effects of something completely different. This is partly why the role is called a data "scientist."
soozyg
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soozyg,
User Rank: Ninja
2/6/2016 | 4:12:52 PM
Re: Sysiphean work
Ah, I see.

And do you have to review the data in context to get the effect? Does the initial plan help?
jagibbons
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jagibbons,
User Rank: Ninja
2/6/2016 | 4:15:28 PM
Re: Sysiphean work
The tools help. Then, the human looks to see if what the computer identified makes sense. The tool is important, but not the part of the equation. A good analyst with a good tool and good criteria can make far better decisions than with any of those key pieces missing.
soozyg
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soozyg,
User Rank: Ninja
2/6/2016 | 4:46:25 PM
Re: Sysiphean work
Yes, I can totally see that. Data has no purpose unless it can be applied to a human issue, unless it can answer a real question. I wonder how often analysts are surprised by the results even after the data is accurate and is applied to an algorithm or designed program.
CuseOrange87
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CuseOrange87,
User Rank: Apprentice
4/6/2016 | 11:40:01 AM
Re: Sysiphean work
There are some concrete examples of practical big data monetization/industry use in the marketing technology world, where companies like Adobe and Circulate monetize data for publishers and platforms very effectively
shamika
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shamika,
User Rank: Ninja
1/30/2016 | 8:54:13 AM
Re: Sysiphean work
I agree with you. Without a proper plan it is not worth of having data. It is important to see what you need to do with the data.
soozyg
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soozyg,
User Rank: Ninja
1/24/2016 | 2:00:51 PM
Under Stop Revenue Leaks
Each procedure has a description and an assigned code, both of which may include errors.

Yes, and if companies aren't streamlined, the codes could vary by department and location.
soozyg
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soozyg,
User Rank: Ninja
1/24/2016 | 2:07:45 PM
Pricing
"One of our partners, which sells on dozens of e-commerce websites, builds datasets of their own products and pricing. When they compare that with their existing expected pricing data, they are able to detect stolen goods and suppliers who are mispricing their items"

That sounds like a smart idea; however, don't prices wildly vary due to the variety of retail sites our there?
jagibbons
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jagibbons,
User Rank: Ninja
1/26/2016 | 9:32:14 AM
Re: Pricing
That's a great question, soozyg. Prices do vary widely, even for legitimate merchandise. Compare prices at Amazon for items they are bulk buying versus the same item from the manufacturer directly. Often Amazon will be so much less that it can appear "too good to be true." There are other discount sites out there that have a similar story to tell. I wonder how the algorythm will tell if something is legitimately really cheap or stolen.
soozyg
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soozyg,
User Rank: Ninja
2/6/2016 | 1:18:54 PM
Re: Pricing
For example, my daughter recently bought a dress for a school dance. On the designer's website it was something like $179. On Amazon, it was something like $30. Crazy!

Also, I did some research for my mother's business, which is homemade luxury faux fur quilts. The prices ranged from $15 to thousands.
Where-Data-is-Wealth
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Where-Data-is-Wealth,
User Rank: Apprentice
1/26/2016 | 7:39:32 PM
Re: Sysiphean work
You make some very good points, but I would like to point out that some of the research into Deep Learning has demontrated at least the possibility of unsupervised learning creating some kind of value out of unstructured data.
shamika
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shamika,
User Rank: Ninja
1/30/2016 | 8:51:15 AM
Re: Sysiphean work
In my opinion survey is very good method of collecting data for analysis. However it is important to get the right questions with the right measures which will help in performing a better analysis on the data. 
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