The Art of Data: Analytics in Everyday Life | Tyler Pernes | Skillshare

The Art of Data: Analytics in Everyday Life

Tyler Pernes, Data Analyst & Engineer

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8 Lessons (46m)
    • 1. Introduction

      1:45
    • 2. What is data, and who really cares?

      7:27
    • 3. Process Flow: Science Side

      5:18
    • 4. Process Flow: Art Side

      4:45
    • 5. Project Overview: Haptracker

      3:15
    • 6. Haptracker, Part I

      5:35
    • 7. Haptracker, Part II

      16:56
    • 8. Final Thoughts

      1:14
38 students are watching this class

About This Class

Learn how to leverage data in your day-to-day life to help you reach your goals.

If you're looking to get started with data analytics, then this course is for you.  This course will go over the fundamentals of data analytics through a simple, step-by-step process.  You'll learn to:

  • Gather data from different sources
  • Load data into specific storage systems
  • Visualize data using a business intelligence tool
  • Bring everything together by building a story

By the end of this course, you will have the foundation to get started with a variety of different analytical projects, both in your career and your personal life.  

Dataset for the project is found here.

The whole point of data is to inform decisions - why not use data for the decisions that matter most?

Transcripts

1. Introduction: Hello, everyone. My name is Tyler Pernis and I'm a data analyst in Data Engineer. They gonna talk to you about no surprise that usually when people speak mentioned data in everyday conversation, we're talking about a specific fine, like 80% of people and then they mentioned wider matter union they have. Maybe there's action night based off that finding. But what's not shown here is other steps involved to get to that. And that's what I like to do over in this. I like to go over both sides of what I call the data process. The first side is gonna be the science. This is very focused on getting the data in the first place, structuring it and making sure story from the LA way More the engineering side of that, I want you happy sign sights set up. You can focus on the other side, which is the right side of that. This leverages creativity a lot more. This is more about building visuals. Toe ultimately gain value. Out of that data, which is really the whole point about it in the first place in this course will go over each step in this process flow and were used those findings by working on projects together that's focused on gaining clarity in your Hopefully, by the end of this, not only will you have a good time standing up data in a very high level, you also have some hands on experience. You can get started with your 2. What is data, and who really cares?: Hey, guys, Thanks for tuning in for this course as mentioned in the Trevor, this course is gonna get you started with Data Analytics. Rather, that's for your everyday life or for your business. In this video. I'd like to talk about a few things. First, what exactly is data? What's the whole wink of using data? And then I'll go over each step in the process. Flow these on the high level as well as the remaining venues going to look like during this entire course. I do suggest if you have any questions to reach out in the comments, because I want this to be very interactive. So let's get started. First thing to talk about what exactly is data data in its purest form has ability, simple definition information. This means the color of your shirt. This means any voice that comes out of your mouth. This means leaves behind you. Every blade of grass that I'm sitting on is information in there for data. The point is, data is everywhere, but the trick is to be able to fill throughout the data you don't care about, so that you can focus on the pieces of information that's relevant to you. But how do we know what that is? The filter out. Well, you need to make sure you always have an overall wreaking question. This is ultimately where you're trying to answer by using the data. Let's say you're at home and you having a conversation with one of your good friends. Let's call him John. And halfway through the conversation, you realize something you haven't spoken for 30 40 minutes now, and Johnny is continuing to talk about things that you honestly do not care about really gets you thinking. Does Johnny ever talk about important topics? This is your overtaking Christian, and you want to focus. So what you decide to do is any next conversation. You take your phone and you put on the record, but which means you accord everywhere, both by you and Johnny. Talk about this is you extracting the data from the source. The source in this case is going to be Johnny, and your extraction method is the quarter. You do this for a few weeks, maybe even a couple months, so that you have a solid amount of data about you can reference board once you feel comfortable with the amount of data you have, you figure out it's time to actually put it to good use. To do this. You start listening to are the recordings you have. We start realizing something. Those are a lot of extra fluff, and there's a lot of words in here that's just not useful to answer your question. So you decide to do is, instead of typing down every single word on the recording, you pick out just the topics that he's talking about, and then you put each of these on. That's a sticking up so that you can have it stored for future use. This is you transforming the data in this case for more quoting in conversation form into one worth topics that stole it on a sticky note. Now that you have out of topics in sticky note form, I figured it's time to actually lavish these topics and use them to answer your question. The thing is, you have about 200 different sticky notes here, and it's really hard to organize it. Do what you do is you open up a scratchy let's say Microsoft excel and you start typing down each of the topics. This is your process of loading and storing the information. So now that you have a spent, she said, you want to intimidate. You want to figure out how to use it to answer your question. You open up the spreadsheet and you're ready to get started, but you get a little bit over mom. Still, even though this is a more structured ray of showing that it's still a wall of text, it's still not particularly intuitive what to do with it. So you take some time to look into it, and you explore the data to see what it looks like. Then you decide to make visual, so it's a little bit easier to understand that what exactly has happened. You built a few visuals, and now you're really ready to dig deep and figure out. Does Johnny actually talk about useful things? You see a chart that shows his top topics or most used topics, and you see the top of the I celebrities who know you types of hot sauce in puppies. You also realize TheStreet topics account for the vast majority of are the conversations. In fact, they account for 90% of our conversations. This is you analyzing the data to gather specific findings. Now that you have these findings, so what does that mean? Well, you started thinking about it. Of the top three topics, only one of them is particularly important. And that's puppies. The other two were really closer to the Who care side of the spectrum. So you categorize each according. You do this for all the topics and you realize something. 72% of all of Johnny's conversations are based on topics that really are not important. The other 28% all right, of about 20% 99% of it is related to puppies. What this means then it's that Johnny does speak about important topics on occasion, but it's almost are due to one topic of puppies. That is an example of you toning a story to help gain a conclusion to answer your overtaking question. So quick overview of what we just did way figured out. What are overtaking question is, we extracted the data from a source. We transformed the data into sticking out form. We loaded in, store the data into a spreadsheet, and then we explored and visualize the data so that we can analyze it to gain findings and bolder story toe ultimately draw a conclusion will be going over all these steps in detail in the next few videos, and then we'll apply them through a project that I think it's gonna be particularly relevant to you guys is actually gonna be a project. Focus on helping you guys keep track of something very important. At least I would assume would be very important. I'm a huge believer that data should be used more often in our everyday lives, because the whole point of that is to help us help us informed decisions. If that's the point, I don't see why we shouldn't use data in our everyday life more often. I actually think the main road block is that people just don't know how to get started, despite the fact that it's actually pretty simple, completely free and not too much time investment 3. Process Flow: Science Side: Hey, everyone, in this video, we're gonna get started with the data fundamentals from the start of the data process flow , which is the science side, the whole point of the science side. It's you prepare the data in a structured manner so that we can ultimately gain value from it by using nights. I think of it as this preparation stage. But what I mean when I think structure generally you want your data to be set up in a table form, which consists of condoms and lows. Columns are found at the top of the table, and they find the data into the question. What does this that I represent? For example, let's say you're shown a series of numbers on a spreadsheet without any column hairs. We have no idea what this data represents until we see what the header shows. So if one of the condoms says revenue been, it's very clear what these numbers represent. Rose, on the other hand, store the information in the table. They actually act as the data itself. If we have no woes and just columns, then we have no data. We just have definitions of data that could be in there and feature. Since you can always gain more information about a subject, the number of lows can and should fluctuate, both adding and taking a LeBeau's. However, definitions of that I really shouldn't change because of this. The number in order of columns should stay the same. So that's how a table set up. And this is what our goal is. We want to get to a point where we have a structure, consistent table that makes sense. So how do we actually get there? Well, let's take a look at a flame that always comes from one or more Swiss. Six. This could be email this congee from application. This could be directly from someone's word of mouth. The point is that it could come from a variety of Swiss is. This also means that that it can come in a variety of forms. Sometimes it could be table form. Sometimes you might just have a line of text that represent that sometimes you might have an actual voice mental or quoting that you have to use regardless of what the form is. We first need to extract the data, and that's a very important step. One Once you have the data, we need to start looking at the structure. And we need to answer the question. Is the status set up in a logical way? Consider these two tables. The table on the right is our gold table. This is how we want our data to look. The table on the left is are extracted table. Notice the difference between the two in the dough table. We have three columns. Country month in population. The same data is stored in the extracted file. But we have one card for each month and populations are stored in each of those columns. Think about how this extracted data can stick within the gold data set. Can they fit together like a jigsaw puzzle? If not, we need a way to transform the extracted data so that it can better fit with our go with that in terms of loading the data, this is just taking the data that you just transformed and putting it into the table you've created. If this is the first time you've had this data set, you'll likely need to first create the table so that he could then load the data in terms of status storage. There's two different types of storage systems. First, those spreadsheets. This is more of a small scare solution is very simple. A set up. The benefit of using spreadsheet is very quick. The issue of spreadsheets. You don't want to use it If you have too much data, a couple of examples are gonna be Google sheets. In Microsoft Excel. The type of data source system is the database. Now this is more of a large scale solution, takes a little bit more time to set up and cries more technical skills. It's a whole lot more robust, and you want to use it when you have a lot of data. But because it takes a decent kind of set up and it takes a decent amount of expertise, we're just gonna focus on using spreadsheets. That's it goes, That's the four steps on the science side of the data process float. Now. One thing I do want to mention is that these steps can be extremely simple or extremely complicated, and it depends on the number of sources, the amount of that, the frequency of data and how complicated that that is in the first place. for our purposes. When we go over the project, we're gonna have a daily basic set up that you guys don't need any technical background for and can get started with additional projects using this same classes in the next video, we'll learn how to leverage this prepared data set by going over the right side of data. 4. Process Flow: Art Side: All right, guys, at this point, we have figured out how to prepare a structured data set. Now let's talk about how to actually leverage this data to reach our overall gold by going over the right side of the data process flow to bring back a rear topic. Our goal is the answer. Are overtaking question. Before we jump into this, I'd like to first talk about a specific type of tool, and that's a business intelligence tour for B. I tour for short B. I tours connector a data set and allows us to build different types of visuals, which makes it a lot easier to understand what our data is showing versus, say, looking at table itself. We'll be using one tool in particular during this course, and that's tableau. The main reason I will be using tableau. It's simply because that's what I have experienced with. But given that there are a ton of different tours in the space so fearfully to use whatever told your most comfortable with, I will say that's happening, how the pay version. But don't worry. We'll be using the free public version for a project. Let's look at the right side of the data process flow similar to the science side. Those four steps explore, visualize, analyze in story tell Before we even get started with the exploration stage, you first need to connect data to your FBI tour those usually an intuitive user interface to set up this connection. Once the data is connected, we can start investigating the data through the exploration stage. This step is all about testing out different ways to view the data. Simply drag and drop columns and you'll be I tall and see what visuals look good when looking at a visual. Think about these questions. Does the visual provided useful insights? Is anything in this visual out of the ordinary? Does this visual relate to our overtaking question? Not every visual you test is going to be relevant so expected for a few of the mouth. After this stage, you should have a few relevant visual to use for the remaining steps. The next step is to visualize the data by building a dashboard. A dashboard is a collection of visuals that provide a vast amount of information at once. It oftentimes country in activity, which gives you the ability to filter out specific data or draw down into specific sections , since the dashboard is natively connected to your data set. As more data flows into the data, set more data with all the map to show up in the dashboard. Once you have Dashwood set up, it's time to actually in the next two data. This stage focuses on turning the dash What you built into meaningful findings. What are the key takeaways from this dashboard? How does his Dashwood help support over in question? Think about a few different ideas and don't worry about putting them together. For now. Just put the ideas down on some kind of paper or some kind of document so that you left and moving forward. I do know that it's better to have too many findings versus too few. If you're not sure if a fine is going to be particularly relevant, jotted down anyway, what do you have this list of findings? It's time to put everything together and build a story to help answer overtaking question. Building a story in this case is simply answering. How do our findings late to our question how you show this story is completely up to you typically depends on your audience. Is your audience gonna be a customer or client? Is it gonna be a specific class that maybe you're teaching? Are you just presenting something to a friend, or maybe, or even just showing something to yourself so that you can figure out what you need to do next? It was a lot of different ways you can show and build a story such as a power point presentation or just writing things down on paper. But again, I think about your audience. Think about what the best approach is on that really guide how you actually present the story. That's it does. That's all we have for the right side of data. Those are the four steps. And at this point, we've gone over all eight steps of the data process flow both the science and the outside. Now that we know every step, we can use these learnings to work together on a project which is gonna be what next three videos gonna be focused on 5. Project Overview: Haptracker: quick recap on me. We are be gone over the data process flow. Step on step both the science side in the right side. Next up is the fun part. Let's apply Ronaldo's to a real life situation for this project. We will be analyzing something very simple happiness specifically will set up a project tracker Happiness at different points in a day and build a dashboard to help us analyze it . For the purpose of this course, let's call this the Happiness Tracker or half track for short. The first step, with any project is planning to keep it simple. Let's just focus on entering these four questions. Number one. What is our over aching question? Force War. Just looking to increase our happiness. So the overall impression is going to be simply how can you increase our overall happiness ? Number two. What are the sources of data? Well, the source needs to understand how happy are at a given moment, So there's really only one option here, and that's you. You are going to be the source of that Number three. What tours are we going to use? And what processes will we have in place to leverage these tours for the extraction phase, I suggest having an application that's very quick and simple to use, so that you can easily jot down where your happiness rating is at any point of the day that his draft. This is a very quick tour, very simple. There's no lo time and its basic. You really don't need to get too crazy with three extraction for here now, since this is also happening multiple times of the day to me, very easy for us to just kind of forget toe impotent what happiness is. So I suggest putting a couple of daily in line set up eso. It could easily get reminded up. It's time to actually jot this down for the transform loading store steps. We need to have to take a scratchy. I suggest using Google sheets. Now. This would like buy Google Sheets versus Excel. It is connected online's collected to her server, which means it can natively connect the tableau without you having to do any manual intervention. If you do store Microsoft Excel, you're gonna have to have it stored locally, which means it's not gonna automatically update when you do connected to be Iittle And that's it for the science. I forgot. All right, side everything is gonna be using tableau. It's really not too much. We have to go over here. I will say the exploration stage is kind of a painting phase. Anyway, so would have to go too much detail. You know, the last question is, who is the audience? This is simply just gonna guide what your storytelling approach is going to be. So it's good to know this beforehand. The audience in this case is gonna be yourself. Because of this. You don't have to be too crazy with your story, Tony. Method. You have to have a presentation or PowerPoint or anything fancy. As long as you have an idea of how your findings were late to your over a compression, then you should be good. All right. That's a for the planning phase. The next video, we'll put it to action 6. Haptracker, Part I: All right, let's dive building on our project. In this video, we're gonna build out each of the science steps, and the next video is gonna be focused on the right steps. Step run. Before he even started with the extraction step, we first have to Donald R extraction tool, which is gonna be the draft app. So open up your mobile phone, go to the app store and Donald drafts. What do you have dress down? Let's go into it. You'll see a blank screen, simply tap on it and you can start typing in whatever you know. Maybe for us, I suggest, is putting in a number so that you can very easily understand what you're hyping. This waiting was at that given time. Now click on top left. Here you see all the notes as well as when it was less access to both dating time. And if you click on a specific no and go to the top, you'll see the information about it, including rent and rare. It was created just some exit information that you don't have to talk down, uh, lasting know about many going to know section you can swipe left and right to either trash or and that's really only need to know about draft. Other things know is that if you do, just type in a number and then lock your phone, it's gonna automatically save it. You have to weigh about any type of safe, but it's gotta artist a future. Okay, Uh, since this is gonna happen so often during the day, let's set up a couple of lines just so that we can get my mind for it. So let's open up the mom and you can see here. I just set up daily live at in the morning, in the afternoon. In the evening, you're more than welcome toe. Choose whatever time you want to track, how often you want to track and so forth. I just use this because it's fixed well with my schedule. That's it for the extraction step. Next, let's focus on the others. Three steps, which is going to require us to use Google sheets. So let's look in the back to get in the good four seats off in your browser and type in google dot com slash sheets. Now use your feet. You're gonna need a Google account so you don't have on make one, it's completely free. And on the Google sheets screen you're going to see on the bottom are gonna be some of your existing sheets. But just click on a new blank sheet and I'll take you to the untitled special. Okay, so this is especially, especially provide. Move my own and maneuver to different cells or select multiple cells and allows you to input data with that's numbers or text for our purposes. Would just gonna use specially to build one table with three condoms. Date in a time of day, and we're gonna have happiness feeding. Now you're gonna open drafts and you're gonna start typing in the information that's found in each of your draft notes. So let's say we have one note on 8 27 2017 for the morning that happens waiting. Six. Your input, each running accordingly. Do the same thing for both be afternoon and for the evening time of days. No, I do suggest insist takes a little bit of investment to open up. That's Petchey. Maybe do this one for a week, by the way, about doing every day. But one thing I want is you have the ability to copy and paste by right clicking, copy or just hit control C in the my click and paste or control the This makes a little bit easier to use what you already created, you know, type everything from scratch. Last thing I want to talk about the bottom. Here are the ability to add more tax. It's come in useful if you want to have two different data sets. For example, Johnny's Data and my dad. What's higher is that on. Then you can change the title of the spreadsheet at the top. So let's call this Pap tracker for Tiring and Johnny. Now it's gonna take some time for you to get a robot status that, since you're only going to be adding three rows at most every day, so what I'll do is I'm gonna share my data set so that you can get started with the right side and you can see the data set in the in the description. When he opened up this data set, your see data are the way back from the start of 2017. Click on this square top left likely can hit copy and then open up your own or this it's file new, go into the first so and then likely hit paste. And that's all you really have to do here to get the data again. This is gonna let you set up a dashboard with my data, and then we can do is you can just replace my data with your data so that nothing really has changed. In other words, since he already built everything, everything's just gonna flow in nationally with new data you have. That's it for setting the science side for this project. In general, there's a lot of different ways you can set up this process. So as you have more projects moving forward, use whatever approach you feel most comfortable with. I would say those a lot of ways you can automate this, but we're not gonna go over this yet. We'll go over this maybe in a future video. Let's keep going and then look at the art side for this project. 7. Haptracker, Part II: in terms of setting up the art side, everything is gonna be focused on our business intelligence tool, which is gonna be tableau. So first up, it's down little tableau public. So open up your browser type in public, dr dot com and various is in your email just in your email here, click down the AB and that should start downloading the installer. Here's tableau. You We care about the left side when he opened up. This is the connection screen. So scroll down until you see Google Sheets, which is stored in memory for me. You might have to put on the more section, and you can see everything that type of connects to. It's quite a bit, and also just search if you love overwhelmed. Since click on legal sheets, it's going to pop up a log in. We don't including your people, she information to once you have logged in allowed and then it's gonna show all your Google , she said you connected. No, I'm gonna connect to this one connect, and then I take a second to connect. Now you see the actual connection Using face screen, you wouldn't have to worry about too much on it here. It should automatically populate with your data. The are in multiple she options. If you have that in more than one tab and you can just drag and drop into this interface anyway, let's move on to the actual worksheet. Okay, so this is what the user interface looks like. Four tableaux school on the talk. Here you see the data Solis itself, and if you click, you can see information about the data. I view the data. For example, if you want to see how it looks, which should be the same as you do she this section are you mentions measures, which is just another way of saying you're different comments cuz date, time of day and happiness waiting Are the three columns we have. You don't notice these three other ones that are italicized. These come with any default data set in tableau. Don't worry about it. For now. We'll go over that in a video. You know, everything on this right side of the screen is very visual actually happens. Common loves just represents what columns are going to be within the column. In low sections, you also have the ability to drag and drop different calms into each of the sections here on in the Mike's Car. You know this area square here lets you change the visualization itself. Example. Let's to have a drop time of day onto the take columns, and then that's tracking about happiness rating onto both. You know you have a decent looking graph that shows what your overall happiness waiting is for each of the time of days. Now. One thing and notice. Okay, so what happened here was double clicked on something, and it automatically filtered it so you can see the photo up here. What's cool about Tableau is, though, is the ability to undo which you can see up here by just clicking controls the orders. Clinton's undo button and it ignores Redux. So it's very similar to anyone who's had experience with Excel. Just control Z control. Why to go under or video recording. There's a lot of different ways you can show this, and you can click on the Show Me button on the top life to show different types of visualization, especially if you've never used Have little four. This is gonna be very, very useful. So go on here you can see text tables. Just click on that now. Just gave us a text version. Go back on. Who was entre bars? Is the sum total Have accept everything switched on. What didn't know is when you do click on one of these Show me buttons. Notice how the car pills, how the pillows change. So on the bars you had called him up here for happiness waiting. And then over here you have for the text. We have this undertaxed. The second is the text. You could change type Here's square and this is example off visual. That just doesn't make sense. There's no reason we want to have both text and square behind it. So this is something you wouldn't use control. See that And we're just wired different things. See what looks good? See what doesn't look good and you can drag and drop much different things as well. Now let's go back to the bar, and actually I like the other Barlow but are easy to see. So there's a button that allows swap clothes and columns appear. Oh, you know, they just do it in the actual pill itself. So this is what I'm saying when I say tweeting intuitive because of the dragon dropped features. One thing I want to show you is that these numbers are way higher despite the fact that in our happiness rating scale, it's between one in 10. The reason this is happening is you notice you see a sum of happiness with never. It's not taking the average for every afternoon. It's something all the app turns up and the ratings they haven't so you can do it quickly. Stopped many orders. Hit right click and breezy measure. Change it to average. That looks a whole lot better. This shows what and let's say we want to change. No, that's a car Time a day you can do I haven't got time to date on the color and you could see the change here. That said, we also want to see some labels on top. Maybe not time of day. You can see what happens. How are they really shows what time of day waas for every time of day. It doesn't make sense so we can take it off and take it off. You can notice drag. Drop it out of the way. You can see this went X next to the mouth. That means okay, we're gonna go with this. Well, could make sense for you. Brag about happiness. Rating on the main wasn't doing the same thing where it's gonna default to some. So those few things you could do here you can change the default properties and changing the application to the average. Now drag it's going automatically show the average. I actually don't like how many decimals air here, so it's right. Click on the text and change the format in this case. Actually, there's a lot of different raising informer and I don't want to do it for money too much. So let's actually take a step back instead of changing the format here, let's change the default properties number format and that's changed too. Number custom with one decimal prince you got. Now, I think that looks a little bit better on this is actually a decent Do you think so? To go back to a bright flame like the first step is to explore. And that's really where the vast amount of time, the most amount time for this entire side is gonna be on because once you have explored that once you have a few visuals, set up the rest of the steps kind of just fall in place so that you don't let's try a few different a few different visuals now, since this is one that we might and abusing, let's keep it and you can sweet name the sheet on the bottom. So let's call this time of day. Comparisons you can do is you can just make a Newt graph a new visual. Or I should say I try and get that now. One other big thing to know is many driving drop date automatically show year and a few age . You can change this for us. Since everything is 2017 it's not particularly useful to show date, but you can click press two drill down all the way down to the day. But I don't like the way this is set up, so I'm just gonna undo this a few times. And instead of driving and dropping date with the left quick, I'm gonna hold right click and drag and drop date and then do something usually wanted something green so green means continuous blue means discreet. I don't really worry, too, much about this yet. Let's say you want to see month. Let's stick it to green. Okay, Now you have a month on the extractive. This do the same thing that happened, is waiting. Okay, Now you can see how hard a little happens, changing over time. And I kind of like bars. You can scroll up to the mikes section. You can change different type area. Mine I keep it has barred. For now. I don't have the size. So they intuitive Krepon size and change it. No, it's automatically changing the with the day. I like manual kind of change. How big or small? Let's just go with that. They had time to see here. That the overall happened to in is in defeating all the time. This it looks like it. But to get a better understanding, you can literally just right click. Trend lines showed her alliance incentives going up. That's good champions in general. We are increasing our happiness, so I consider this. He's for as well rename this and call it a car monthly happiness. I guess now we already have two different graphs that could be out of it. Let's keep going and That's literally this dragon drug offenses. Okay, drop that here. What time of day by day? Let's say we do day. Let's look by weekday. Sure, it's kind of cool. It's actually kind of gives a counter type of you. Not cry, but could be used for the things I don't like. Text. I think the text itself. It's just it's hard to really understand exactly happening. I think it's much easier to see color so and see how it can change was picking this highlight table. All right, there you go. So you can see here. It's a little easier now to know what specific days in what specific time of days are the best for me. You can see here that Saturday Sunday seem to be the darkest. So that's probably where I was happy for, for obvious reasons. And on Tuesday afternoon, I'm just not feeling too out. You can see that here now, even changed the cover car at a car. Maybe you want to see some kind of red green comparison it apply and you'll see more of stop right stop like type of set up here. So continue exploring a few different visual. Let's continue exploring the data set until you have a number of visual you feel pretty comfortable using for your dashboard. Once you're comfortable. Rec visuals, you have time to move on to the visualization stage, which is simply setting up a dashboard. So if you score the bottom, this middle button isn't that what that? And you'll see the dashboard creation screen. Now that sport is simply dragging and dropping different visuals on it just allows you to set up a dash however you want whenever you can drag and drop this graph here dragged off another one here, and you can pretty much is playing around with whatever you think makes sense. Now I'm gonna controls er this and show two different ways of showing that what you just saw was the tiles and you see those squares. I know it's tiled. It's Penis saying, Okay, this stash, this visual fits in this dash through this time, I personally don't like that. I would much rather used the floating option, but she could do by holding holding a shift in the driving drop. You see, there is no square populating its just a floating square above the entire rights and what this lets you do, it gives you a little bit more flexibility to choose. Rare. Exactly every dash graph. It's been a shock. So that's put time of dating pairs here. Maybe you want actually monthly in time. If they have to talk. Both of them are probably more like high level things, So it makes sense to have a talk. I don't want to show this correct, really obvious that each for each color represents here. I'm gonna get rid of that. Imagine that's resize this and you can just kind of play around each of these if something is showing that you don't want to hit the X button. And the other thing I want to mention is, whenever you click on one of these visuals, curriculum dropped on many, and it fit to change the latest fits within the screen so you can see here those scores on for bar. I don't like this. I would much rather be able to see the entire view. So click on fit entire view and maybe this experience. Okay, that's pretty decent. Now continue this, and eventually you can have a decent looking dashboard that can give you cried a few insights. Last thing I want to mention is the ability to filter. So I don't think we felt filter its goal of the sheet. And thats dragging drop day in click monthly again, right? Click, drag and drop, I think month and year. And let's say you had official. It's not particularly useful on this. Try to do this so it's actually try a different tribe. Sure, let's do this one saying things Month, year and this is Gina. Now you see You see, you see the number of change because it's filtering my It's going for my entire data set into just January. Now you can do is click on the table. You just added the ability to right click or click the doctor hit filters and then add the filter you just added, which was month, year of date. And then you see this popular now it's kind of cool is if you click the drop down on this filter hit apply to worksheets. All are using this status with now. This is gonna finish photo everything at once. Now you see everything just for may, and if you want, you can have it fried only to retreat. You care about for me? I want us. I want to filter for months since this shows month anyway. So I'm gonna take off the monthly happiness as option and then you got. Now you can see this affects the left to on this one is staying intact. When you're done with visualize Stage, you should have a dash were created that can allow you to help in the life that we already have. Some findings from the exploration stage back and write down, such as March 12th has pretty high rating over our I am increasing happiness, which is good. And then Tuesday afternoon is pretty low, which is something that I might want to take into account Moving for it. Maybe I could try to be happy that that day you can continue to dig into whatever visualization you have. If you have interactivity, maybe clicking the things. Here's something kind of interesting. On 6 19 in 6 20 I have three low happiness relative to everything else in June. So maybe I check my calendar and see what happened. Those days were caused that low Know of a happiness waiting. Anyway, do this for your visualization, figure out a few findings, and then the last step is a story. Tony, Really. There's not too much to say in terms of storytelling since you're the audience. But use this Teoh into your question. Look at your findings. See what the lowest instances in Haifa instances of happiness, and try to understand what caused those and if you can, maybe moving forward. You can be more rare about it, and you can do things. They'll increase it over happiness. And the court thing is, as you continue to track your happiness, you can really see if what you're doing is working. Currently. Have a strategy. Try it out for a month and your happiness has not increased. May be suspicious strategy up a little bit, not take us. When you're done with your project, you'll save it on the top of public and feel free to share what you have under the course description Project section. Courting might have a public is everything is open source, which means you have the ability to download your bricks or the people who report to see how they didn't think. So let's make this interactive, make this collaborative and maybe even learn from each other's findings. 8. Final Thoughts: That's it for this course, guys, I hope you gain value out of this. Whether that's through the project you built what? Just getting a better understanding of how data fits from the start to the end. One thing I will say is we barely even scratched the surface on this entire thing. Each of these steps can honestly have an entire career dedicated to it. What I want to do is I want to get feedback from you guys in terms of what you want the next course to be focused on. So maybe you really like building the dashboards. We can have another video focused on more advanced tableau dashboard creation. Or maybe you want to get a better understanding of how to pour down and stored in a database. We could have entire course on database concepts in using some sequel. Teoh, move that data around. Thank you so much for joining this course. Guys. I really do appreciate it. And I hope you continue to learn more about this topic. This is the first day of a built. So if you guys don't mind putting some feet back down well, maybe getting a view and be honest with it. I don't want to say it's amazing. It was amazing. And those anything in particularly thought I can work on. Please let me know that I would really appreciate that from moving forward. Hope to see you, sir.