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Data is all around us! In this video, we'll see where we can find data and talk about who uses data inside an organization.
Here's a few good places to find public datasets:
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To create an analysis,
first we need to find some data.
0:00
Luckily, it's all around us.
0:04
From how many steps you take in a day,
to how much gas is left in the car.
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Data is there helping
inform our decision making.
0:10
Data is a record of an event,
or an attribute of something.
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You have the power to create data just by
recording the things happening around you.
0:17
For example, every morning you could
write down how many hours you slept.
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That's data.
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A collection of data is
usually called a dataset.
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Generally, this means that all the data
in the set is related in some way.
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It may come from a common source,
or relate to one specific topic.
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For example, a dataset of the nutritional
information of vegetables
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is unlikely to include bananas.
0:44
We saw in the grocery store example
that we all use data naturally.
0:46
This happens in many of
our daily decisions.
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We might look at school rankings or
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neighborhood crime rates when
choosing a place to live.
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Read reviews of online products
before buying them, or
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compare features on different
appliances before choosing one.
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When we use information to make
a decision, no matter how large or
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small, we're using data.
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Data is also useful for many hobbies.
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If you're a sports fan, digging into
the stats of your favorite players,
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can be a great way to get
started working with data.
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Other interests may not be as
datacentric as sports are, but
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you can still approach them
from an analytic angle.
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For example, if you're a gardener,
gathering data about your local weather
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and how it affects different plants can
help you to choose the best plants to
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grow for your climate and give you the
greatest chance of success as a gardener.
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Or maybe you're just interested in data.
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I'm sure there's a dataset out
there that you'd find interesting,
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and there are tons of websites devoted
to sharing data with the public.
1:46
A few you might want to look into are
Caggle, data.gov, and the UCI repository.
1:50
Check out the information in the teacher's
notes below to get started in exploring.
1:56
In the workplace,
data analysis is a growing field.
2:01
More and more companies are creating
data teams to help them make decisions.
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People in many different
positions work with data.
2:09
In job titles the word analyst
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often indicates that the position
involves data analysis.
2:14
However, other titles are possible.
2:18
For example, data scientists combine
data analysis with programming and
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machine learning.
2:25
Different analysts might work with
different types of data within a company.
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For example, a web analyst might make
recommendations for a company's website
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based on which pages are visited most,
and which links are clicked most often.
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On the other hand, a financial
analyst would look at revenue and
2:41
expenses to forecast a company's
financial performance.
2:45
And a pricing analyst might use purchasing
data to determine the optimal prices for
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products.
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Since data is an emerging field,
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the same title in different
companies may mean different things.
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If you are looking for a job working with
the data, always read the job descriptions
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to make sure that the position aligns
with your interests and capabilities.
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In the next video, we'll introduce
the dataset we'll be working with and
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start doing some analysis
3:12
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