[00:00:05] SY: Welcome to the CodeNewbie Podcast where we talk to people on their coding journey in hopes of helping you on yours. I’m your host, Saron, and today we’re talking about SQL and why you should learn it with Sia Seko, Data Engineer at Spotify.

[00:00:18] SS: If you don’t need to do what YouTube does to store videos, do you need something other than SQL? Probably not.

[00:00:28] SY: Sia talks about what SQL is, what makes SQL different from other technical languages, and what it’s best at after this.

[MUSIC BREAK]

[00:00:48] SY: Thank you so much for being here.

[00:00:50] SS: Thank you, Saron. It’s really nice to reconnect with your orbit after two years.

[00:00:56] SY: My orbit. Oh, I had an orbit. I love it!

[00:00:59] SS: Yeah, you do have an orbit. Yeah.

[00:01:02] SY: So Sia, you’ve been at a lot of different data roles, different companies for the last seven years. And you are now a data engineer at Spotify, which sounds really neat. Tell us about how you found this niche of tech.

[00:01:16] SS: I would say in a nutshell, it was mostly because I was lazy and tired of working with Excel.

[00:01:23] SY: Fair. Okay.

[00:01:24] SS: So my very first job I was working with global compensation. You know, when people move between countries, mostly, these big companies, they move people. Somebody has to do all the math and all the expense management. And so I was part of the team that maintained the system on reporting of that. But it was all very manual because our customers were accountants and they like Excel.

[00:01:52] SY: Oh!

[00:01:53] SS: So I found myself doing a lot of things in Excel, so I could send it to them that way. And that was really tiring. So then I just started picking up some of the tools that would make my job easier.

[00:02:07] SY: So how did you go from not wanting to do Excel to finding the technical solution that was much better for you? What was that learning journey like?

[00:02:18] SS: Oh, you know what? I actually remember the moment.

[00:02:20] SY: Yeah.

[00:02:21] SS: I used to sit on this desk and there were like two people in the group of 50 who knew how to use SQL. And every time we had to fix a report or change a field, we’d have to go find this Stephanie lady, a very kind lady. And this one time, I was like, “I have to figure this out.” And she was there late and I was like, “Stephanie, can you please give me just a primer? I need to go and find my way around and I need your help to know the important things so that I can go learn it by myself.” And that was the day. So eventually, I kind of became as me on our team for SQL and reporting. But I actually remember the day because I was so frustrated. It was like, “Why am I here?” One of those moments. You know?

[00:03:13] SY: Got you. And before that, were you exposed to technology or coding when you were younger?

[00:03:21] SS: Not really. So I grew up in Tanzania and I would say maybe there was coding and technology, stuff like that, but I don’t remember ever owning a laptop until I was close to my 20s. After coming here, I think maybe the last year I was home before coming here, so like early 20s. So the first time I even tried to code was 2014 with Python. That was because I was in a stats class and I remember it being really hard. I was like, “Wow! I just figured out how to really format Google Docs well,” because I grew up in that intermediate.

[00:04:05] SY: Yup. Yup.

[00:04:06] SS: You know, where people went from Microsoft on the computer to Google Cloud, like Excel and docs, and I was like, “Okay, this is hard.” So yeah, 2014, I would say, was the first time.

[00:04:21] SY: And did you anticipate launching a new career at that point? Did you see yourself being a data engineer and all of that?

[00:04:29] SS: No. So I’m an immigrant and there’s all these rules about how long you can be without a job before you have to leave. I really honestly just took the job because I needed a job. And so I would say to be very honest, that first job was based on a security decision.

[00:04:49] SY: Absolutely. Yeah.

[00:04:50] SS: But yeah, I’m glad I learned all those things because I probably would not have some of the skills I have now that I use.

[00:05:00] SY: So you started this journey into SQL out of necessity, out of just not wanting to be in Excel, out of needing security for the job. Did you ever get to a point where you actually enjoyed it and liked what you were doing? Or has it mostly been very functional and very practical for you?

[00:05:19] SS: So I started using SQL in 2015 and it started out very functional. And in the beginning of 2016, I became really interested in not only doing the reporting, but automating it and learning how to maybe not just run a query, but how do I run a query that returns a report that sends it to someone’s email? And at that point, it became more enjoyable for me. And from there, it was just like, “Okay, how can I make this faster? How can I make this better? How can I save more time?” So I think the transition from functional to enjoyable was really quick for me.

[00:06:05] SY: And what was it about that transition? What was it that made you go, “Ooh, this is actually kind of fun”?

[00:06:10] SS: I’d say I’m pretty curious. So feeding my curiosity became really fulfilling. So that made it fun. The feeling you get when you just fix a bug that has been bugging you, that sort of thing.

[00:06:24] SY: Yep. Absolutely.

[00:06:25] SS: Never gets tired.

[00:06:27] SY: So tell me about your trajectory from that moment you first got that primer on SQL to years later being a data engineer at Spotify. What did that path look like?

[00:06:37] SS: It was more of an adventure.

[00:06:39] SY: Okay. Nice. Nice.

[00:06:41] SS: So after that job, around the end of 2017, if you remember in the US at that time, we had gotten a new administration. And so my company was more aligned with the benefits of that administration. And part of that was if we planned to help you get a permit or a work sponsorship, it was not going to happen. So I had about six months where I could either leave and try and find a new job or I could go back to school and extend the time I can work. So there is a window of time where you can work every time you get a degree in the US. It’s one year. And then if you get a STEM degree, you get up to three years.

[00:07:34] SY: Nice. Wow!

[00:07:35] SS: So you can buy time. So that’s what I did. I went back to school. I also worked at the time and I was doing research. I worked as a software development intern for a small business, for the business school where I used to go to school. And that was about two years of just picking up what I could get. In the middle of that, I went into this bootcamp where I ended up becoming a teaching assistant, and even up to now, develop content for some of the curriculums that they have. And I got this contract to work as a data analyst. So I was able to grow really quickly and became a senior analyst. I became a lead. I became a manager. And so that’s actually the last thing I did before this job.

[00:08:32] SY: So now you are a data engineer at Spotify. What does that mean?

[00:08:38] SS: For me right now, I joined as part of a new initiative. So it’s a situation where technically there is no “code base”. You are kind of doing archeology on what’s already there before you build the new thing. So I joined an internal initiative that helps other teams work easier so they have to do a bunch of reporting and billing and stuff like that. And the pipelines that I will get to build are going to help them do those jobs easier, less manual.

[00:09:19] SY: Interesting. Yeah.

[00:09:21] SS: So other people are probably doing more coding with the same title, but right now, I’m in the phase where I’m doing information gathering. I spend most of my days digging through databases asking questions, like, “What does this mean? Why was this created?” So it’s a really good way to learn, I think, because I get to go into the unknown. Sometimes people can’t answer my questions because they weren’t there. So we have to figure it out together. But it’s really fun. I can’t wait to code, but I’m not coding yet.

[00:10:00] SY: So if you’re not coding yet, what kinds of things are you doing to kind of prepare for that?

[00:10:04] SS: So LinkedIn Learning. I also use Udemy and then Spotify develops some of its own open source technologies. So I try to spend some of my time reviewing those, looking at questions people ask in public forums, like the issues they run into. Because if it’s by your company, even though it’s open source, the people who use it the most are probably going to know the depths of things that could happen. So that’s also part of my learning.

[00:10:42] SY: So I know that you studied mathematics and creative writing in undergrad. And so I’m wondering, is math a big part of being a data engineer or those two separate disciplines from your experience?

[00:10:57] SS: It kind of goes hand in hand, not necessarily from a one-plus-one-equals-two perspective. but thinking logically, being able to connect the dots. If you ever took a linear algebra class, one of my favorite things my professor used to say, “Math is just about taking a big problem and breaking it into smaller chunks that you know how to solve that will solve the bigger problem.”

[00:11:26] SY: That makes it sound very not scary.

[00:11:29] SS: It’s not scary, Saron. It’s not scary. And I don’t know how to change this, but one of the things I wish I could do with a Thanos ring is make people less scared of math because somebody told them it’s scary. They didn’t try it. Or somebody didn’t help them figure it out.

[00:11:48] SY: I completely agree because I never was really scared of math. but I definitely didn’t enjoy it for most of the time that I took math classes in school until I had a really good teacher. I remember him very well. His name was Justin. He was a professor, but he had us call him Justin. I don’t even know what his last name was. And he had a motorcycle. He was very cool. And he just made it really fun. And I was like, “Whoa! Maybe I do like calculus.” So yeah, I’m with you. I think it’s just poorly taught. I think that’s really the problem with math.

[00:12:22] SS: Yeah.

[00:12:23] SY: So what are the major technologies that someone should know if they want to get into data engineering? Tools, languages, frameworks that might be useful for people to learn today if they want to start their career in this industry.

[00:12:38] SS: I will approach your question as a framework.

[00:12:43] SY: Okay.

[00:12:43] SS: So if we think about the tasks that you have to learn to be able to contribute to building a system or a pipeline, essentially you are taking data in its role form and finding a way to make it easy to interpret and to use for people who are doing analysis or modeling. So you need to know how to transform it, to extract it, to load it, and maybe to connect it to things. And that’s how I tell people to approach landing things, not maybe specific tools because they will evolve. It’s a whole zoo out there. There are so many tools. The basics I would say is SQL, Python because it’s very versatile and also some form of scheduling, orchestration tool, like an Airflow or something like that.

[00:13:49] SY: And what is a scheduling tool?

[00:13:52] SS: So sometimes you might want to complete a set of tasks for your data and you don’t want to do that manually, right? You want to say, “Maybe I want to extract this from this source and then I want to extract another version of this from another source or a complimentary from a third source. And then I want to put them together and then I want to transform them in a way.” Well, you might have three scripts to do all these different things or more, but you don’t want to press a button to run each script every single time. And by the way, I’m really simplifying this.

[00:14:33] SY: Okay. We appreciate it.

[00:14:35] SS: Yeah. So you put all of these together and you define a set of instructions to say, “Okay, run this and then this. Maybe wait until this thing is confirmed before you run the next one.” Right? And all of that is housed somewhere. And those are those orchestration tools that you can use to say, “Okay, I want to have a graph that completes this workflow of events with these triggers and these checks along the way.”

[MUSIC BREAK]

[00:15:29] SY: So let’s dig into SQL, which is the star, I feel like, of the data world and definitely a big part of your career, kind of how you got started. Let's define it. What is SQL? What does it stand for? What does it do?

[00:15:43] SS: So SQL, Structured Querying Language, is a querying language. You know, querying is asking for something, you are asking a data store for something based on some conditions you define. If you think of a Google search, you say, “Hey, Google, I want to see maybe what songs Toni Braxton sang.” Google has a way of taking your question or your query and returning just those things that you ask for from the universe of things that are there. If you think about a lot of the ways that we get information, we have to query it. So it might not be SQL. But SQL is definitely the most common querying language when it comes to information retrieval.

[00:16:35] SY: So SQL first appeared a while ago, in 1974. And it’s still widely used today. Why do you think this particular technology has lasted? I feel like with tools, they come and go, frameworks come and go, languages get popular and they kind of fade away. SQL’s been thriving for almost 50 years now. What do you think makes it so special?

[00:16:59] SS: I think it depends on who you ask. So if you’re asking me as somebody who started out in data, in my mind, no one has come up with another way to retrieve information from a relational database or whatever database warehouse you’re looking at in a very human understandable manner like SQL does. If you think about some of the commands, it says select, give me this from this, where this condition applies. So first, it’s simplicity, right? And its ability to be adapted with multiple engines. That kind of gives you a head start, but in a way it feels like most people didn’t have that much data that is not structured in the before times. We didn’t have all these apps that have such huge chunks of unstructured data. We didn’t have YouTube. We didn’t have Twitter. All of these big, huge use cases that have so much data that you just have to figure out new ways to query it. Most of us didn’t have this problem until these use cases arrived. So I think that kind of made it so SQL got the chance to be, I don’t want to say like the boss, but if you don’t need to do what YouTube does to store videos, do you need something other than SQL? Probably not.

[00:18:47] SY: Right. Right.

[00:18:48] SS: For me, that would be a big reason I think why it still rules because it’s easy to learn. It takes you from Point A to Point B without a huge lift.

[00:19:01] SY: So you’ve been given the moniker DJ SQL, which sounds very cool. Tell us the story behind how you were given that name.

[00:19:11] SS: Okay. So Victoria, who is now Dr. Victoria Watson-Zink, is one of my favorite humans of all time. We met because we were paired to teach together at the bootcamp that I worked at. So, first of all, we were both fellows when we were learning. And so we kind of connected that way. And then finding out that we were paired together, I remember crying. I remember a lot of our messages being just like wholesome all of the emojis. I cry when I’m happy a lot. So part of our sessions where I will make playlists. I am very African. Most of the music I would put was African, just vibe before we start talking about these concepts that you want to understand, lighten the mood. And I also happened to teach SQL for the larger group. So we had these small groups that we taught, but then we would have like sessions where everyone in the bootcamp was just paying attention to that class. And so I taught the SQL class. I got really great feedback. I was really floored. And then the next time we came to class, Victoria said, “I think we should call you DJ SQL.” And that was it. I mean, and also to be given that name by someone you kind of look up to, I just never let you go. I just hold onto that because it makes me smile when I remember who gave it to me, why. It’s just a huge compliment.

[00:20:56] SY: That’s lovely. So I know that there is some contention about whether SQL is actually a coding language or not. Where do you stand in this debate?

[00:21:09] SS: Does it do the job? That’s where I stand. Listen, I think part of it is there are people who are like historians that are like, “This is how Pangea broke out so that the continents happened. And Panama exists because of colonialism.” Okay. But are there black people in Panama? Does SQL do its job? Yes. I don’t understand anything after that. So I really do not participate in the debate.

[00:21:41] SY: Got you.

[00:21:42] SS: I don’t argue either if somebody’s really adamant about, no, it’s not a programming language because you are not programming anything. It is a querying language. People get really specific about the semantics. So I’m, “Okay, we could both have this happy life. We’re both using it. It’s working.”

[00:22:02] SY: For those of us who may not be familiar with SQL, maybe never seen it, never worked with it, paint us a picture of what coding and SQL looks and feels like.

[00:22:13] SS: First of all, I would say if we are thinking of just the environment in which you are, SQL can come with any sort of canvas. There are so many engines that you could be querying SQL from a custom tool that is built maybe in your company or you could be using an enterprise tool. You could be using things like Snowflake. However, if you think about what you’re doing, it’s probably the least intimidating “coding language” you could read.

[00:22:51] SY: Okay.

[00:22:52] SS: If you are coding in SQL, you need to write out what you need. Literally say, “I want to get people from a data store of humans where all the people I get are assigned male at birth.” And then the SQL commands for the most part, the main commands, they never change. Select from where, same across, I should say 99.9%, if there is something new out there. So if you think about the experience of understanding what you want and translating it to code, it’s probably the least intimidating of the things that you could be coding in. When I teach SQL, we do not code. We use pieces of paper to start or whatever thing you like to write on. It could be like a blank sheet because you need to think through what you want. And then you put, “Is this going in the select block or is this going in the from? Is this going in the where?” Because it’s all English.

[00:24:06] SY: So when it comes to the world of data, what is SQL not good at? When would you use a different language, a different tool where maybe SQL isn’t really the right thing?

[00:24:20] SS: Sometimes you want to retrieve things that cannot be stored in a table or in an orderly role or observation. So, for example, you might want to store relationships between objects or diagrams or documents. SQL is not good for that. It’s mostly good for structured tabular data that is human readable for the most part. And sometimes you can maybe hack around to get metadata about the things that you are trying to retrieve because maybe like they’re a string. It can be maybe retrieved, but maybe it’s not the most efficient way. So it’s not just about retrieval. It’s about performance as well. And also it’s about how you store it. So are you storing a relationship? Are you storing a document? SQL might not be the best thing to retrieve that with.

[00:25:36] SY: Coming up next, Sia talks about where SQL fits into product development and the range of tech roles where knowledge of SQL might be a big part of the job after this.

[MUSIC BREAK]

[00:25:57] SY: So when it comes to where SQL fits into product development, where is it? It feels like if we’re talking about SQL in the context of databases, that feels mostly like a back-end thing. Is there a place for SQL on the front-end or other different parts of the stack?

[00:26:15] SS: It depends on who the end user is. Right? So for example, if I’m a data engineer, I’m mostly building tools for data analysts or scientists. And they might want to not only see maybe a dashboard, but be able to look into how I put the dashboard together. Right? Maybe they want to see, “How did you connect these two fields? How did you connect this to data endpoint?” I can’t think of a situation where somebody might want to use SQL directly, like the everyday person who is just Googling things. But I can think of work ecosystems where the person using your product wants to query it using SQL. Product managers, for example, they do a lot of research. There are some systems and tools nowadays, the modern data stack ecosystem, where you are maybe querying as you do your research.

[00:27:25] SY: Yeah, because the next question I was going to ask was going to be around looking into and exploring different jobs where they might need to do some queries. And so journalist was an example that came to mind, especially if you’re a reporter and you want to look at some data, look at some statistics, some numbers to create a well-researched analytical article. That feels like SQL would be a really helpful skill to learn in that role. Can you tell us a little bit about how and why a journalist might use a tool like SQL in their job?

[00:28:02] SS: If they don’t have a research department, I can definitely see that. For example, you’re writing a story about an election, like say the presidential election, and there are all these small breakdowns of geolocations, like the county and the district and the ZIP code. And you might want to de-aggregate the data as you display it and talk about it that way. So I could see a journalist or their assistant wanting to query this data. Now sometimes companies have a way for you to access data via SQL. But if they don’t, I probably see them using Excel and maybe Power Query, which is kind of an intermediate cleaning place that you can do with Excel, but if you need to de-aggregate things or segment things so that you can explain them. I could see that.

[00:29:05] SY: Another kind of tech role that came to mind was a project manager. How might a project manager leverage SQL knowledge in their job?

[00:29:15] SS: So I have been in a place where I was half a project manager and half an analyst.

[00:29:23] SY: Oh, okay. Yeah.

[00:29:24] SS: And sometimes you have quick questions, so you’re kind of an intermediary between the team and some stakeholders, even though you don’t really manage anyone. You manage the project. So you might want to know some high level or maybe some context of things before you may walk into a meeting. And instead of having somebody build a dashboard for you, you could go by yourself and query some things you want, a small table maybe, not some big results. I’ve had situations where I needed to say like, “How many people did we enroll into healthcare insurance in the past month or something?” I can quickly go and query that instead of having somebody doing a whole analysis for me. So situations where you need information that is not a whole product, I would say.

[00:30:27] SY: So what about a marketing manager? I know, especially these days, we want our marketing to be as data driven as it can possibly be. Where might SQL play a role in a marketing role?

[00:30:38] SS: I can see that person being more like a product marketing. So if I add the word product in front of marketing, I can definitely see someone who is doing research to not necessarily answer internal stakeholder questions, but to drive external stakeholder product development. So for example, if we think about… do you remember when Twitter had fleets?

[00:31:10] SY: Yeah, it was like the IG stories, right? Like the Snap.

[00:31:13] SS: Yeah. And then it disappeared after a day.

[00:31:16] SY: Yeah.

[00:31:16] SS: So when you asked me that, my mind went to somebody who had to market them, and so was trying to understand how impactful they have been with engagement.

[00:31:29] SY: Right. Right.

[00:31:31] SS: And maybe looking up numbers around impressions or logins, for example, associated with fleets. I could see somebody who’s a marketing manager looking into this high level, I say higher level because I would not expect them to just be in SQL all day.

[00:31:49] SY: Right. Right.

[00:31:50] SS: Because they are actually like a storyteller who needs data to tell a good story.

[00:31:57] SY: To tell their story. Yep.

[00:31:58] SS: So that’s where my mind went. I don’t know why it went there, but I was like, “I wonder how the person who had to market fleets said, ‘Okay, we should keep them or we should not keep them.’”

[00:32:09] SY: So do you think that SQL is a good language to learn early in your career? Would you prioritize that in your learning journey?

[00:32:17] SS: Okay. So I would say yes, but I would learn it knowing that I am not going to know everything. So I would want to know how to write a query. I would want to have the SQL knowledge of the marketing manager, if I was really going into it. But I know that I’m going to learn how to think about performance, security, integrations as my career progresses, because what a lot of us do is we think we have to learn everything at the same time. But then it’s a use it or lose it situation. And then if you never use it, you’re going to forget all these things. So I would learn enough to know how to get to the next step, but then always have the mindset of SQL is going to help me do different things. So I should always be learning depending on what I’m doing.

[00:33:21] SY: So if I am a developer and I have no interest in back-end work, no interest in data work, I’m just going to stick to my front-end, I’m going to stick to my CSS and the stuff that the user sees, I’m not going to deal with data, do you think in that situation it’s still important to have some base knowledge of SQL? Or is it maybe not really worth my time?

[00:33:46] SS: I think it would be, “Okay, am I trying to convince you to learn in a scenario or am I just trying to make you understand, ‘Hey, maybe you could be well rounded’”?

[00:33:56] SY: Fair. Yeah.

[00:33:58] SS: Because it’s two different things. If the person is like, “I will never, ever, ever touch this, even if you try and make me do it,” I would say, okay, try and understand what your search button is doing.

[00:34:11] SY: Right. Right.

[00:34:13] SS: Or when the result comes back as does not exist. What does that mean when you see it or when you build that? What might you want to communicate? What validations might you want to have on your page? So try and understand maybe how it impacts your customer experience, since you’re only going to be concerned about the front-end.

[00:34:40] SY: And what are some resources that you found helpful to learn SQL? I think you mentioned LinkedIn Learning was one. Any other ones that you might recommend?

[00:34:49] SS: Yeah. So I would say anything that freeCodeCamp does because it’s free. And also, there are some websites that it’s not a course, it’s more, like, “This page, you learn how to use this command. And then on this page, you learn how to use this command.” So one that I really go to when I’m stuck and I don’t remember off the top of my head what I need to do is W3Schools. Because if you’re using freeCodeCamp on the website, you can like do as you learn. So W3Schools is the same way where you don’t just read it and see the result. You can run the query. You can play around with it. And I really like that. I would also say if you have time, because it’s a time commitment, and you want to go to the bootcamp route, I would encourage people to look into Correlation One Data Engineering Program. So one, it’s free. The bootcamp is free. I realized not everyone is at the same place, some people are struggling with things beyond having a computer, but if you have access to a computer, it’s on Saturdays, the lady who runs the bootcamp, Kelly Hopkins, is one of my favorite people. I have a lot of favorite people. And I know like day-to-day, the kind of effort she puts into how to help people, not just learn, but like make the information digestible. And so I would really encourage people to go into that bootcamp because you don’t just learn. You also do case studies and you build things and you have a portfolio at the end and it’s free.

[00:36:46] SY: Now at the end of every episode, we ask our guests to fill in the blanks of some very important questions. Sia, are you ready to fill in the blanks?

[00:36:53] SS: Yes.

[00:36:54] SY: Number one, worst advice I’ve ever received is?

[00:36:58] SS: To change my name so that I could get a job in the US.

[00:37:01] SY: Really?

[00:37:03] SS: Yes.

[00:37:03] SY: Whoa! Tell me about that.

[00:37:05] SS: Yeah. I will not name this professor, but they said, “You know, your name is very not white or not Anglo-Saxon.” I don’t remember what they used, but that’s really what they were trying to say. They were like, “You should change your name. Your application will not be thrown out to the pile,” which maybe it’s true, but I was not going to change my name.

[00:37:29] SY: No, no, no. I do not agree with that advice.

[00:37:32] SS: Yeah.

[00:37:33] SY: Number two, best advice I’ve ever received is?

[00:37:37] SS: So this is probably a combination. I think it’s both of them, honestly. I can’t remember who said it first, but Natalie Davis and Angie Jones, who everybody knows. They always are like, “Be coachable. Keep learning because you just don’t know when something will come up that you need and don’t burn bridges.” It’s very easy to come back around to the same people. So keep those connections. They will come in handy.

[00:38:08] SY: Absolutely. Number three, my first coding project was about?

[00:38:13] SS: Ooh. Okay. So when I started learning Python, I had just gone home after five years and I thought, “Wow! We are still doing this. We need a bus system.” So I kind of made an app that was with Python, a bus scheduling system. It was mostly about SQL where I wanted the drivers, the bus owners and the government officials to all have a central place where the scheduling happens, instead of writing it down on a notebook and handshake agreements. So that was my first project that I really enjoyed.

[00:38:51] SY: Very cool. Number four, one thing I wish I knew when I first started to code is?

[00:38:56] SS: You can’t learn everything. Just learn what you need when you need it, but know the fundamentals really well and you’ll be fine.

[00:39:06] SY: Well, thank you again so much for joining us, Sia.

[00:39:08] SS: Thank you.

[00:39:16] SY: This show is produced and mixed by Levi Sharpe. You can reach out to us on Twitter at CodeNewbies or send me an email, hello@codenewbie.org. For more info on the podcast, check out www.codenewbie.org/podcast. Thanks for listening. See you next week.