- [Instructor] This may be the end of this course,
but it's just a beginning for you,
and so it's time to start making plans
on how you're going to produce
your own big data revolution.
Remember, this course is a map.
I've simply been showing you the outlines of big data,
the ways it is used in so many different fields
and so many different domains.
It's from here that you can plan what you want to do next.
Now, I can make a few general recommendations.
You're going to get a lot further with big data
if you know how to do some computer programming.
Python is a very common choice,
and R, a statistical programming language,
is also a powerful option.
It's good to get started with open data
'cause if you want to have a lot of data
and diverse data all at once,
going to sources like data.gov
can get you started with the sets you need
to start finding insight.
And then learning more
about both machine learning and artificial intelligence.
And fortunately, we have a wide range of courses available
for you right here to get you started
on these more sophisticated topics
that can give you potentially greater insight
into your own data.
Also, because big data works within a context,
it's good to know more about business strategy,
and specifically, about data-driven decision-making.
And you want to know how these things work
and how big data could be applied in your own context,
be it enterprise and banking,
be it medicine, be it nonprofit healthcare,
and even in small businesses.
It's also a good idea to get connected with people
in big data and data science, machine learning,
and artificial intelligence to get inspired
and to get support in what you're learning.
You can try events like the Strata Data Conferences
or ODSC, which is for Open Data Science Conference.
There are others like
the Marketing Analytics and Data Science Conference.
That's a small, professional conference,
and then depending on where you live,
you'll have local events.
Like, I'm in Utah,
and each year we have the Silicon Slopes Tech Summit.
You'll be able to find a range of opportunities
no matter where you are,
either in person or even online,
to help get you connected with other people
in the big data world, to support you in your learning,
and to give you ideas on what you can discover
and what you can accomplish with big data.
But remember that big data like all data
is fundamentally about people.
The reason you work with big data
is so you can better understand
the people in the world around you,
and also so you can turn that understanding
into something of value for the people you work with,
be it at a large enterprise scale
or at a very small bakery scale.
Thanks so much for joining me,
and best of luck in your own big data work.