3
Big Data
Myths
Big Data is
BIG
Talk to any business, and they’ve
probably discussed the topic of
big data and what it means
for their organization.
Perha...
But today, few organizations are realizing
the promised value of big data.
That’s because they are thinking
about it all w...
1 It’s all about size
2 You need a data scientist
3 You need a system like Hadoop
3 myths about big data
It’s all
about size
Myth
Talking about size, speed, and
complexity misses the real point of
big data. Every day, data gets bigger,
faster, and more...
We’re collecting data about
processes and activities that
we’ve never captured before.
We call this datafication:
it’s the...
But just because you have a lot of data
doesn’t mean you have business value.
People are still the most
important asset of any company.
And now the real question
becomes “what can you learn
from your ...
Myth
You need a
data scientist to
tame big data.
Your most valuable technology
asset isn’t really a technology
at all. It’s your data. The ability
to manage your data well...
What is important is that you create a
culture of data-driven decision making
and ensure that everyone across your
organiz...
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 ...
Myth
You need a
big data system
like Hadoop
There are a number of new
technologies today that
help you deal with data –
including Hadoop.
These are great tools to
hav...
It’s important to recognize and
embrace data disparity. The
reality is that your data is not all
going to reside in one lo...
What matters most is the ability to
bring data together from many
disparate sources in order to solve a
business problem o...
So embrace big data
and its complexity.
Design for it.
Imagine what you’ll discover.
© 2014 QlikTech International AB. All rights reserved. Qlik®
, QlikView®
, QlikTech®
, and the QlikTech logos are trademar...
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3 Mitos de Big Data revelados

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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.

3 Mitos de Big Data revelados

  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.
  21. © 2014 QlikTech International AB. All rights reserved. Qlik® , QlikView® , QlikTech® , and the QlikTech logos are trademarks of QlikTech International AB which have been registered in multiple countries. Other marks and logos mentioned herein are trademarks or registered trademarks of their respective owners. qlik.com

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