September 24, 2014 at 8:23 pm
Comments posted to this topic are about the item The Value of Data
September 25, 2014 at 12:19 am
There is evidence that we are now at the stage where we can identify through data some decisions, previously based on human intuition, that we humans are more likely to get wrong. In some cases we can produce decision support systems and even completely automated systems that are more accurate by far.
Of course, all the above is based on problems that we can codify in some way alongside a set of data which can be mined for enough information for this purpose.
As for the reference to machine intelligence, nowadays I wonder if it is not the artificial intelligent abilities but the volume of local data storage required that will be the most impressive feat achieved...unless they run it in the cloud 😉
Gaz
-- Stop your grinnin' and drop your linen...they're everywhere!!!
September 25, 2014 at 12:25 am
As for the understanding of the data and its inherent value to the business, I tend to feel that it is not the data professionals who underestimate its worth, or at least its importance. It is often higher up the hierarchy where they completely lack the understanding of the effect on the business should their data disappear.
This can be seen when the sales data warehouse which supplies management with the details of completed sales is considered more important than the sales/orders and stock control data. Lose the first and you lose the ability to refine business decisions for a limited time. Lose the second and the business loses their income.
Gaz
-- Stop your grinnin' and drop your linen...they're everywhere!!!
September 25, 2014 at 5:54 am
More data isn't necessarily better data - something aptly demonstrated by the Google Flu trends fiasco.
How data is collected is just as important as quantity if not moreso, as anyone who has taken any but the most basic statistical courses can attest.
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Just my $0.02 from over here in the cheap seats of the peanut gallery - please adjust for inflation and/or your local currency.
September 25, 2014 at 7:03 am
I'm not sure if 21st century data is analogous to 20th century oil. Oil is a scarce commodity that is expended when it's used and can't be replicated. However, data is the antithesis of that. Perhaps IT professionals with data analysis skills are the new oil and data is just the raw dirt and bedrock from which useful information is extracted, assuming an organization can bring sufficient skillets to bear. Of course, some datasets are more rich than others, but still that in itself is not a scarce commodity.
I believe that in the 21st century fresh water may be the new oil.
"Do not seek to follow in the footsteps of the wise. Instead, seek what they sought." - Matsuo Basho
September 25, 2014 at 7:18 am
I am not great with analogies or metaphors but marketing departments are the new snake oil salesmen. Right?
Gaz
-- Stop your grinnin' and drop your linen...they're everywhere!!!
September 25, 2014 at 7:31 am
Gary Varga (9/25/2014)
I am not great with analogies or metaphors but marketing departments are the new snake oil salesmen. Right?
Folks in marketing have always been snake oil salesmen, figuratively and literally.
Data as the new "snake oil" ?
That's funny! 😛
"Do not seek to follow in the footsteps of the wise. Instead, seek what they sought." - Matsuo Basho
September 25, 2014 at 7:40 am
But snake oil is so hard to come by. Here is what some folks will resort to when all else doen't work for them. :w00t:
http://www.shirleys-wellness-cafe.com/UT/Urine.aspx
"Do not seek to follow in the footsteps of the wise. Instead, seek what they sought." - Matsuo Basho
September 25, 2014 at 7:41 am
Eric M Russell (9/25/2014)
But snake oil is so hard to come by. Here is what some folks will resort to when all else doen't work for them. :w00t:
Some URLs you just never need to click...
Gaz
-- Stop your grinnin' and drop your linen...they're everywhere!!!
September 25, 2014 at 8:13 am
I recently left a company that has been purchasing healthcare data for years and stockpiling it...not knowing what to do with it or how to use it. When my team finally looked at the data for analysis to determine what products we could develop for the market...it was quickly apparent that 95% of the data was useless as key medical attributes were missing. Even after relaying this to sales and product managers, they continued to pitch prototypes that we knew we could never build. They squandered millions over the years because they just cared about quantity and not quality.
Aigle de Guerre!
September 25, 2014 at 8:16 am
Data is cheap and ubiquitous. It is lower than information, which is organized data. Data has its own attributes such as quality, timeliness, and accuracy that only the collector may know. I suggest looking on wikipedia for Bloom's Taxonomy to see just how little value data really has. It is unprocessed and needs tremendous amounts of energy and time to become valuable. Humanity is at this point of huge energy usage to support complexity and struggling with greatly diminishing returns to add the tiniest new value from data.
Bloom's Taxonomy has the following stages: knowledge > comprehension > application > analysis > evaluation > synthesis
It has taken me over 50 years to reach synthesis in just a few lines of development such as developmental psychology and spirituality but I'm just at the beginning comprehension level in say cooking, gardening, and politics. Humanity needs synthesizers right now to fix the economy, environment, and energy problems but I'm not holding my breath until that happens.
September 25, 2014 at 8:33 am
I'll admit that I love working with data more than I love the most popular applications built on top of data. I'm like a musician who loves playing and writing music but hates going on concert tours, or a gourmet chef who loves the creative process of preparing food but doesn't care too much for eating it.
"Do not seek to follow in the footsteps of the wise. Instead, seek what they sought." - Matsuo Basho
September 25, 2014 at 9:07 am
Data is plentiful as is sand, but data as sand is only of small value. Good data is like gold for it is rich, solid, and shines under the light. High grade data is as a handful of diamonds that glitter in the sun with fire that catches the eye and causes one to imagine.
Can data predict the future? Does knowing the past and the now, dictate what is to come? Only as we best understand it, for many have looked as the truth and have gotten it wrong. Evaluating good data or high grade data can cause us to be aware of the probabilities of what may happen, but it cannot cause us to believe it. There are those who have a hunch, a gut feeling who will go contrary to the best analysis of the best high grade data, and they may be right, for data is not a god that it should know what is to happen; it can only tell us of the probabilities and we need to evaluate them and decide.
As ones who love data, it is our task to collect it in as high a grade of data as we can, analyze it for what it really is, and then present it such that those who are tasked with making the decision can understand it and make the best decision, if they choose.
Not all gray hairs are Dinosaurs!
September 25, 2014 at 10:06 am
lshanahan (9/25/2014)
More data isn't necessarily better data - something aptly demonstrated by the Google Flu trends fiasco.How data is collected is just as important as quantity if not moreso, as anyone who has taken any but the most basic statistical courses can attest.
Usually, but more data allows us to learn more. We might certainly learn that we are collecting data that isn't relevant to the area we think it is, but it may be elsewhere.
I think more data is better, but we need to be careful in how we use it and understand what it means.
We can always discard some data for a particular problem, but it's good to have it and not use it than not collect it. Of course, if we do it poorly, we want to fix that
September 26, 2014 at 1:58 pm
Read Daniel Kahneman's book on cognitive bias.
In theory we have the golden goose. In practise the powers that be begrudge the cost of the hen house and are wondering if the goose would make and acceptable quick meal.
If data tells people what they don't want to hear then they will try everything in their power to prove that the data is wrong or the collection method is wrong or that it is missing some fundamental attribute.
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