Skip to 0 minutes and 17 secondsWelcome to the first content video for data analytics for decision-making. So this is topic 1 and our first module topic 1a, just looking at an introduction to data analytics, big data some terminology that'll set us up for the rest of the course. looking at the outline for topic 1 as I said, introduction I'm going to introduce the idea of variables, data. We'll talk about what they mean then in module 2 we're gonna look at graphical descriptive techniques, they're just graphs. Visual displays as well as looking at summary statistics or descriptive statistics in module C.
Skip to 1 minute and 3 secondsAnd finally would have round out the important role of ethics, and how that plays through entirety of the course and all data analytics that you might do. So let's get into this introduction though. Talked a bit about the the welcome video kind of about where we're going in forming our decision-making as managers, using our data analytics data-driven we talked about and let's just have a look at what this is all about. Well we've got data that's the starting point and businesses all over the world now have huge amounts of data, but having tons and tons of rows of customer information or sales data accounting information that's not useful on its own if you don't turn it into information.
Skip to 1 minute and 55 secondsNow information is data that's been transformed, that's been analysed such that it is useful for decision making. So maybe you have analysed all of that sales data and found out that the best way that you advertise your business is actually through radio, not TV, not online. You know but you've, that's information you can then use that to inform decision making but just lines and lines of data, that's not the same, it's not as informative. So we're trying to change data into information that can help us make decisions through analysis, and that's the data analytics the analysis. That green box is what this subject is all about.
Skip to 2 minutes and 42 secondsTo give you some sort of ideas of the kinds of questions we're going to be looking at, and they're everywhere, you know, how can we make sense out of all this data. Are there any patterns in the data, increasing trends over time of cost, did they just occur by chance or is it something systematic that you've had product errors, product flaws. How do we differentiate valid from flawed claims?Look at hypothesis testing. Are there any relationships between two different pieces of data again like advertising, sales are there any relationships there. All sorts of questions and these are the kinds of questions that we're looking at answering in this course. But wait there's more!
Skip to 3 minutes and 33 secondsSo how do we convert survey results into a useful graph? So we'll be looking at that in the next topic with graphical descriptive techniques. Another specific example might be based on past data. So we're informed by what's happened in the past how likely is it that we will sell more than 100 laptops each week? So the data is just the amount of sales every day in history. But that's just data, so we're gonna transform this into information and say how likely is it that we'll sell more than 100 laptops this week? And that can help us understand how much stock we need to have on hand ready to sell and available to sell.
Skip to 4 minutes and 28 secondsDo you want to know your customers better? As managers I hope everyone jumped up and said yes absolutely! We do want to know our customers better. and again there the analytics the analysis you're going to learn in this course. You can use that on data that you gather about your customers to convert that into information.To help you make decisions understand them better serve your customers better. And there's still more, you know, specifically you know are sales influenced by advertising? If so what is the relationship specifically? What's the relationship so we know how that happens if you get given some information the median level of customer satisfaction is this. How do you interpret that?
Skip to 5 minutes and 17 secondsAgain you'll learn how to do that and in fact that will be in module one see so that will be in two videos time where you'll learn about how to interpret the median. How can I test if my product labels are misleading? You know we say it has a certain amount of, for example an active compound in a drug, or a certain amount of grams of food in a can or bag. How do we test to make sure that we're truly supplying the customer what we say we are. So all of these questions and more, they're the motivation for this subject. So I hope you can start to see how varied, how interesting some of this works going to be.
Skip to 6 minutes and 3 secondsSo just to go back a step any tips that I have for you well the first one is you've got to practice you've got to practice, practice and practice but don't focus on aw in Excel I click here then I click there, right? Focus on understanding the underlying technique, that is what is going to help you in the exam as that is what is going to help you as managers going forward now look I understand many students find you know numbers statistics data analytics sort of a bit scary, and and difficult initially but if you practice and practice then you get there, and we have computers we have excelled to do all of the calculations for us so it's not really too scary from a calculation point of view it really is of course more about understanding the technique, directing the computer to do what we want.
Skip to 7 minutes and 0 secondsBeing able to interpret the output. That's what all of this is about so I hope you really find it interesting challenging and rewarding, how it can sort of help you guide your decision-making with better informed data-driven approaches. One other tip logic checks always do this always with your analysis. We all make mistakes myself included. The only question is will you notice your mistake first and fix it before everybody else knows or, are other people going to notice and say hey you made a mistake or it's not very good? So it's all about noticing the mistakes yourself first and fixing them before anyone else knows.
Skip to 7 minutes and 49 secondsFor example you you run a model you do something you do some of the analysis, and it comes out with an answer. The recommended quantity is negative 4. Excuse me what does negative four mean, you can't have negative four as a quantity it must be a positive number. So you know that somewhere there was an error so now you go back and fix it before anyone sees the problem.
Skip to 8 minutes and 15 secondsAnd often you'll find that if you make a mistake it'll come up with a really silly strange answer that if you apply a logic check, you can realise something's wrong here let me go back, I'll fix it no one will ever know that I made a mistake, and they'll all think that I never ever make mistakes which is not true but you catch them before anybody else sees them. Another example this idea of negative again if you say the price that you should charge is negative two dollars fifty I can, that's ridiculous it can't, can't be true. So apply those logic checks.
Learning Tips for Week 1
If you’ve gotten this far then you’ve taken your first few steps for completing this online course.
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Over the next two weeks, we hope you’ll join in the comments and activities with us as we learn about some introductory data analytics in today’s data-driven world. In this video, Adrian provides an outline for the course and some learning tips. In the next step we will also describe the terminology we will be using throughout the course.
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