Alexis
Welcome to Talk Tech with Data Dave. My name is Alexis, and I am a super non-technical person who works at D3Clarity. And I’m here to learn stuff from Data Dave.

Data Dave
Hi, Alexis. Good morning. I think Alexis is selling herself short, but we’ll keep that among ourselves. I’m. I’m Dave, I’m the CTO of D3Clarity. I’ve been working with data and technology for about 25-30 years, up through different different roles, different positions. So Alexis assures me that I am suitable for having this conversation. So, we’ll go from there.

Alexis
Our goal here today is to talk about a data topic and learn a little bit along the way. Again, if you’re a technical person, Dave’s gonna be your guy. If you’re a non-technical person, don’t worry. I’m gonna ask all the easy questions here. So, Dave, our topic today is what is data? Can you talk to me about that?

Data Dave
Of course. Yes. Alexis, I can talk to you about data. Let’s talk about data. The first thing I did looking at this question. Right? This is very simple question. Was I looked up what data was according to the dictionary, right? So when I read the dictionary and I just did a Google search on data, it says facts and statistics collected together for reference or analysis. It says the quantities, characters, or symbols on which operations are performed by a computer being stored and transmitted in the form of electrical signals, which is a little too technical. And the last one I like. From the philosophical point of view, is the things known or assumed as facts, making the basis of reasoning or calculation. Right?

Alexis
I mean, that’s so good, but what does any of that actually mean?

Data Dave
So, the way I look at this is that data is the evidence of a fact. So, if you take that last definition, it’s the information that describes a people, place, thing, or event. It isn’t the thing itself. Right? But it is the information that describes it. So, to go back to this, it’s the things known or assumes as facts.

Alexis
So, we both wear eyeglasses and so you’re saying that like our prescriptions aren’t necessarily data, but all of the little, you know, “1-2, A –B” things that they do is the data that actually helps us figure out our prescriptions.

Data Dave
Yes, that’s a piece of data that describes the prescription. A piece of data that describes Alexis is the fact that you wear glasses. Do you wear glasses? Yes or no? Right? It isn’t the glasses and it’s not Alexis. It’s the information that describes something about you.

Alexis
So, from a technical perspective or from a working perspective, what does data mean for the everyday person?

Data Dave
So, data is everything. If you go to your phone number. Your phone number is a fact. So, if you go to your, if you go to your phone, right, your handy dandy cell phone that we all have. Then the phone number of an individual is a fact that describes them. It is a piece of data that describes the way to connect to that person. So, the demographics of Alexis is your name. It’s not you, it’s your name. It’s the data that describes you. It is your address. It’s address, that is information that describes where you live. Your phone number is information that describes how to connect to you. If you take these together. Name, address, phone number. I’ve actually got a pretty good representation of the identity of Alexis. I don’t have Alexis. I have information that describes Alexis.

Alexis
OK, I like that. Absolutely.

Data Dave
Makes sense? That becomes crucial because that’s what you need if you go to a hospital, for example. And you have an incident, you have to present yourself to a hospital. Then they want to know who you are, and they want to be able to track that with multiple visits to that hospital. So, who is Alexis? So, this information describes who Alexis is. Right? And that becomes the data about Alexis.

Alexis
I love that. I love that idea of the collective idea of what is a person. It could be, but not actually, who the person is. That makes total sense. So, how do we, as D3Clarity, use data?

Data Dave
Well, we use data. We’re a data analytics data management company. So, what we provide is the ability to help other organizations manage the data. So, if we go back to that healthcare situation, if you present to hospital. But they type your name as Alexis versus Alex for two different visits. Is it the same person or not? How do you know? How do you describe to the manager of that data that these two visits are the same person? And that can be really valuable, right? Because you want to be able to go back to your health record and say, oh, I’ve visited the hospital this number of times versus that number of times you want to be confident that you’re not being confused with other patients.
Right? Because that could actually be very material from a patient perspective from a patient health perspective. Alex might have cancer. Alexis does not.

Alexis
I actually had that happen to me once. Before I changed my name, there was another Alexis Keller in the city that I was at the Doctor of, and we had the same birthday. And it wasn’t until somebody was like, “oh, what a pretty middle name”. And then they said the other girl’s middle name. And I was like, that’s not me, but…. That’s… yeah, those are all data points and if we would have checked all of them from the beginning, we could have clarified it.

Data Dave
Exactly. So that’s, that’s where we get involved data. So, we help, we help organizations work with their data to make sure the data actually describes what they think it describes and make sure they’re using it effectively and use it for decision-making. Right? If you look at our name, data, digital, and decisions being in driving clarity through that, so does the data that you’re collecting actually describe what you think it’s describing and how confident can you be in that data? Are the points that we spend time on, right, where we help organizations and this goes across, right? Does the product data that you collect actually describe the products that you sell?

We’ve had organizations that it took them a year to work out what they actually sold because their data really didn’t describe what they thought it described. We’ve had organizations, you know, customer data, who did I sell this to that could be either an organization or a person, whatever. And so, data describes everything that occurs in an organization.

When you go into Walmart, when you buy something in Walmart. The point of sale data, the fact that you bought something is data that is collected. They need that data to replenish the shelves, know what they did know what inventory they’ve got, et cetera. So, they use the data for all kinds of things across the business. But remember the data is not the thing, it is just the information that describes it.

Alexis
You use that Walmart example. I like that. So here we have Kroger. That’s one of our big grocery stores. I don’t know if there are Krogers where you are, but I digress. And we have, you know, Kroger cards and that’s when they scan it and it helps us get discounts. Is that them collecting my data?

Data Dave
Yes, that’s exactly what that is. The reason they create those is because if you pay cash for an item in a grocery store, that’s a low fidelity touch point or it’s a very weak touch point. You are anonymous. You handed over a buyer bond, a bearer bond for an item. All they know is that you’ve purchased. That item has gone off the shelf.

Alexis
That’s a great word.

Data Dave
Thank you! They don’t know who bought it. They don’t know anything about you. They don’t know how you paid for it. They just know that it was cash. That’s all right. The reason they created these loyalty programs is so that now they can know what are the demographics of the people buying this product. Because now they’ve got you attached to that purchase. Now they can say, “Alexis bought this product and Alexis lives it.” Well, they know where you live cause the store you went to, but they know they know who you are. You know, probably your age, your gender, various things about you that they didn’t know before, so now they can start to look at all the sales that go through their entire organization. Start to say, okay who’s likely to purchase a coat in January? Right? Which stores are likely to do that? What are they likely to buy? What is happening? What? What is happening at my point of sale? They know far more about you than they did before. And they can track you over time. So, you can say, “Ohh, Alexis comes in the store once a week”. And they can predict that they know that and they can start to plan their inventories and plan their lives around that. That’s why they created these loyalty programs.

Alexis
I’m going to synopsize everything you just said into a really dumbed-down answer which is kind of, data is all around us and it’s used to understand who and what things are.

Data Dave
Yes, it’s all the information that is everywhere. Every time you write something down, you are collecting data. If you write down my phone number, you are collecting data about me. Right? If you put it in your phone, if you put it into a computer, you’re collecting data. Data is everywhere. It’s the information that describes people, places, things and, time or events. So, data describes the sale data and describes a customer. Data describes a person. It isn’t the thing itself, but it is the information that describes that. Now, what has happened in recent years is with the power of computing. It’s not that we’re collecting more data, but we’re able to analyze that data so much faster. And do more with it, and we’re collecting it ourselves as much as organizations are collecting it.

Alexis
That was about to be my next question, so it sounds like there’s a lot of data out there for everything. How does one? How do I? How do you take all of that data and make sense of it?

Data Dave
That’s the multi-million-dollar question, right, because people put a tremendous amount of money into exactly that, right? And it depends on what answers you want to get. If you ask the question, how do I contact day-to-day? You’re gonna look in your phone. You can look up my name and you’re gonna get the data that is by phone. Your heads down, but that is you making use of data. So, it’s that question and answer the way I always look at it is that question-and-answer construct. What am I asking and how do I get the answer? So, if you’re an organization that’s collecting like we just said at Walmart, which is the I’m collecting all the Loyalty program cards information for all the sales across all my stores. Now, you start to realize Walmart might be interested in, “Where should I stock the most winter coats?” Right? Well, which stores last year sold the most winter coats?

Alexis
Probably here and not where you are because it’s snowing here?

Data Dave
Exactly, but you get the point. Now they can. Now they can manage their inventory by asking that question of last year’s data. They can predict where to go this year, and they can do the same with “Okay, you know, what is the most likely thing to be purchased in Chicago by 25-year-old females?” They can ask all sorts of questions, but they can look at the data that they’ve collected in previous years and start to answer those questions.

Now for the amount of data that they have. Some of these questions are ridiculously hard to answer.

Alexis
That’s what I was thinking.

Data Dave
Just from the amount of data that they have. And sometimes they have to ask, “Do I trust the answer? Because is my data good enough? What quality of data do I have? How good is it and how much do I trust it and therefore, trust the answer that I’m getting.”
Now for some things, it doesn’t have to be a precise answer. Right? If I’m saying, where should I stock winter coats? I don’t need to know exactly how many winter coats were sold in Chicago. I just need to know that Chicago’s a fairly cold place from last year. That was evidenced by the fact that we sold a lot of coats there and a lot is enough information to know. I don’t have to know that I sold 17,293,000 or whatever the number is, right? But you can see how this starts to work and how people start to channel. Amazon collects a huge amount of data.

Alexis
Obviously, yeah.

Data Dave
And the Amazon touchpoint is way higher than the Walmart touchpoint. Because Amazon, you have an account. And you connect other family members to your account. So, they know who’s in your household. They know you share lists; you create lists. All this is data that allows them to target and to work with you and provide a higher customer experience and improved customer experience. You bought this next week, so you probably want this this week. Right? That’s why I get ads for things that I was looking at before or why if I, you know, buy X, it also recommends Y, Z, and Q.

Alexis
To go with it.

Data Dave
That’s right. Exactly. Exactly. All this is the data mining and data analysis that is happening behind the scenes.

Alexis
Data mining, that is a great word. That sounds like a topic for another week or another month of discussion, though this was an awesome day, today, I feel like I have a little bit of a better understanding of kind of what data is and how it affects our everyday life. I hope everyone will join us next time when we talk more about I think maybe data mining changes our lives and works through our lives.

Yes, thank you so much for being with us here today, everyone. Thanks Data Dave for having this conversation with me, and I hope everyone has a fantastic day.

Data Dave
Thank you, Alexis. Thank you very much.