Bummer! This is just a preview. You need to be signed in with a Basic account to view the entire video.
Data is Everywhere3:13 with Ben Deitch
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.
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. 0:06 Data is there helping inform our decision making. 0:10 Data is a record of an event, or an attribute of something. 0:13 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. 0:22 That's data. 0:26 A collection of data is usually called a dataset. 0:27 Generally, this means that all the data in the set is related in some way. 0:31 It may come from a common source, or relate to one specific topic. 0:35 For example, a dataset of the nutritional information of vegetables 0:40 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. 0:50 We might look at school rankings or 0:53 neighborhood crime rates when choosing a place to live. 0:55 Read reviews of online products before buying them, or 0:58 compare features on different appliances before choosing one. 1:01 When we use information to make a decision, no matter how large or 1:05 small, we're using data. 1:09 Data is also useful for many hobbies. 1:12 If you're a sports fan, digging into the stats of your favorite players, 1:14 can be a great way to get started working with data. 1:18 Other interests may not be as datacentric as sports are, but 1:21 you can still approach them from an analytic angle. 1:25 For example, if you're a gardener, gathering data about your local weather 1:28 and how it affects different plants can help you to choose the best plants to 1:32 grow for your climate and give you the greatest chance of success as a gardener. 1:36 Or maybe you're just interested in data. 1:41 I'm sure there's a dataset out there that you'd find interesting, 1:43 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. 2:04 People in many different positions work with data. 2:09 In job titles the word analyst 2:11 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 2:21 machine learning. 2:25 Different analysts might work with different types of data within a company. 2:27 For example, a web analyst might make recommendations for a company's website 2:31 based on which pages are visited most, and which links are clicked most often. 2:36 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 2:48 products. 2:52 Since data is an emerging field, 2:54 the same title in different companies may mean different things. 2:56 If you are looking for a job working with the data, always read the job descriptions 3:00 to make sure that the position aligns with your interests and capabilities. 3:04 In the next video, we'll introduce the dataset we'll be working with and 3:08 start doing some analysis 3:12
You need to sign up for Treehouse in order to download course files.Sign up