3 Mitos de Big Data revelados Uno. Sobre el tamaño de datos: el verdadero valor está en cómo utilizamos los datos, no la cantidad de datos que tenemos. Dos. Todas las personas necesitan acceder a la información de manera fácil y rápida. Para resolver esta necesidad requerimos alguien especializado en datos (un Data Scientist) Tres. Existen lo que se denomina "framework de software" especiales como Hadoop. Es un sistema bueno, pero generalmente necesitamos unir información de fuentes dispares que se encuentra dispersa.

1. 3
Big Data
Myths

2. Big Data is
BIG

3. Talk to any business, and they’ve
probably discussed the topic of
big data and what it means
for their organization.
Perhaps they’ve even made an
investment in big data with
the promise of insight.

4. But today, few organizations are realizing
the promised value of big data.
That’s because they are thinking
about it all wrong.

5. 1 It’s all about size
2 You need a data scientist
3 You need a system like Hadoop
3 myths about big data

6. It’s all
about size
Myth

7. Talking about size, speed, and
complexity misses the real point of
big data. Every day, data gets bigger,
faster, and more complex.
But now we’ve reached a tipping point.

8. We’re collecting data about
processes and activities that
we’ve never captured before.
We call this datafication:
it’s the idea that almost
anything can be quantified.
And because storage and
processing are cheap,
we can collect data about
almost anything, just
in case we need it.

9. But just because you have a lot of data
doesn’t mean you have business value.

10. People are still the most
important asset of any company.
And now the real question
becomes “what can you learn
from your data that would
change your business?”
The most important thing IT can
do is to work with the business
to determine how the answers
to new questions can help drive
the business forward.

11. Myth
You need a
data scientist to
tame big data.

12. Your most valuable technology
asset isn’t really a technology
at all. It’s your data. The ability
to manage your data well and
to extract value from it is critical.
But it’s not necessary to hire a
super human data scientist
to do it all for you.

13. What is important is that you create a
culture of data-driven decision making
and ensure that everyone across your
organization has the data they
need to do their job well.

14. And, here’s a little secret:
Most people in your company don’t need
big data. They need small data. But they
need it in a way that is easy to use and
gives them the information they need
in terms they can understand.

15. Myth
You need a
big data system
like Hadoop

16. There are a number of new
technologies today that
help you deal with data –
including Hadoop.
These are great tools to
have in your toolbox. But
just as you don’t need a
hammer for every fix-it job,
you don’t need a Hadoop-
like system to solve every
data problem.

17. It’s important to recognize and
embrace data disparity. The
reality is that your data is not all
going to reside in one location.
Remember the data warehouse?
It was rarely, if ever, the only
place that you needed to go
for all of your data. And, today,
your data may be in even more
locations than ever before
with the addition of big data
architectures and cloud.

18. What matters most is the ability to
bring data together from many
disparate sources in order to solve a
business problem or tell a story
about a customer.

19. So embrace big data
and its complexity.
Design for it.

20. Imagine what you’ll discover.

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