Alter Everything

MaddieJ · ‎10-03-2022

What’s the best way to build your personal brand in the analytics world? Kate Strachnyi, founder of the DATAcated Circle, joins us to share why she’s passionate about helping folks upskill in data analytics, and shares concrete tips for fostering a meaningful career in the data space.

Panelists

Kate Strachnyi – DATACated, LinkedIn, Twitter
Mariem Ayadi – @mariemayadi, LinkedIn

Topics

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Transcript

Episode Transcription

MADDIE 00:02	Welcome to Alter Everything, a podcast about data science and analytics culture. I'm Maddie Johannsen, and today I pass my hosting mic to my colleague, Mariem Ayadi. Mariem is a senior data scientist at Alteryx, and not only does she have the data science background and know-how, but Mariem is so easy to talk to and she loves helping people with their careers. So who better to interview our guest, Kate Strachnyi, the founder of DATAcated and host of the DATAcated on-air podcast? Kate is equally passionate about helping folks build their careers. So for this episode, Mariem and Kate chat about building your brand and data. So if you're curious about different careers in data and how you can stand out in an increasingly noisy world, especially on social media, this episode is for you. Let's get started.
MARIEM 00:52	Good morning, good afternoon, and good evening everyone. My name is Mariem Ayadi. I'm a senior data scientist here at Alteryx, and I have the pleasure of having Kate with us today. Welcome to Alter Everything, Kate.
KATE 01:07	Awesome. Thank you so much for having me here.
MARIEM 01:10	We're really happy to have you and to have the show focus a little bit on the topic of careers in tech, but with a bit of a larger topic and sort of focus on building a brand and the data analytics tech space more broadly. First of all, however, I'd love to introduce you to our audience. You're someone who is extremely passionate about what you do, which includes helping people learn and navigate their careers in data. You have a podcast. You actively post on a variety of platforms. You've been a recognized LinkedIn top [creator?]. You have a continuously growing community. You have and continued to launch courses with the most recent one on LinkedIn Learning Platform. And though I'm sure I'm probably missing quite a few things, you have published and continued to publish books. So let me maybe pass it to you to tell us a little bit about your journey from a degree in finance to consulting to what you're doing today. And maybe over time, who has your target audience been in your various endeavors and how did those come about?
KATE 02:20	Yeah, absolutely, I'd love to talk about all of that. And thank you so much for that introduction. I think you haven't missed anything from what I'm working on. Maybe conferences. I don't know if you mentioned conferences. Those are time-consuming, so I want to mention that. But yeah, the journey so far has been extremely fun. Like you mentioned, I started off with the green finance. I went on to do some sales in risk management, which led me to working in risk management, going into consulting, regulatory compliance all over the world of risk management, of regulatory compliance. And then about eight years ago, I shifted into data analytics.
KATE 02:56	And for me personally, it was love at first sight. The first time I had a data set and I used Tableau to manipulate that data set and create data visualizations, I'm like, "Okay, this is where I'm supposed to be. I have found my people and I have found my world." And simultaneously, when I started getting into data, that's also when my social media career was born because I lived out loud and I thought that documenting my journey somewhere would be a fun thing to do. And I've chosen YouTube and LinkedIn as the platforms where I decided to document what I'm learning, who I'm speaking to, highlighting other professionals in this space. And yeah, that's what led me to starting my own company called DATAcated. And that's what keeps me busy these days.
MARIEM 03:43	That's awesome. And who would you say your target audience has been maybe at the beginning, over time, now?
KATE 03:51	Yeah. I think it started out being aspiring data professionals, data scientists, data analysts, those who wanted to break into the world of data. That's the audience I attracted because that's where I was in the beginning. So as I shared, "How do you use Tableau?" And, "How do you find data sets to train on and play with?" I think that attracted more of the students, the people trying to break into the career and following me on that journey. Now I'm in a place where I talk to all people in the data world. So it could be data engineers, chief data officers, data scientists, machine learning engineers, and it's all over the spectrum because part of what I do, you mentioned podcast, I have a live weekly show called The DATAcated Show that we host on Tuesdays at 11:00 AM Eastern. We bring on a variety of guests but we talk about different topics like data mass, data strategy, data observability. We do talk about branding. We talk about all these different topics. So it's taken me-- it's broadened my perspective in this space and it's also increased the connections that I'm able to make in the world of data.
MARIEM 04:53	I love it, and I love that your work has an impact on such a broad set of people. Here at Alteryx, we have a really awesome analytics education program targeted at students, career switchers, and really all lifelong learners. And the program is called SparkED. We also have a highly active community where people from all different walks of life and different stages in their analytics journey help each other. For example, for me, something that was really special is meeting users of our products who initially had this sort of anxiety around the perceived learning curve when it comes to analytics, and hearing their story of how because our software is so intuitive, they just naturally learned the data and analytics lingo and the concepts without even realizing it, almost. And they were doing things like table joins, getting all sorts of mixed up input data to play nicely together, learning that fancy words like imputation just means that empty cells and nulls are really just things that maybe you should watch out for and probably handle when you're playing with data.
MARIEM 06:03	So for a lot of our users, Alteryx was the mean that helped them embrace a career in data. And I'm really excited for us to hone in on this idea then of branding and why it matters in the first place. But maybe we cover a little bit of ground around data rules to give our audience a sense of the career paths that we've been alluding to or talking about today. People often default to the name data scientists, or at least I've seen that definition of the role, honestly, evolve over the years. So maybe what would you say is the latest on that and also just other roles out there which you started talking about?
KATE 06:41	Yeah. I think it's great that you mentioned that there are some terms like imputations that might sound scary for people. And then they're doing it, they didn't realize they were doing it, they were like, "Oh wow, I can't believe I know how to do this." Because there are technologies like Alteryx and Tableau, I would say as well, that have made things so simple with the drag-and-drop features that it lets you do things without really thinking too much about it or having to study a whole textbook on how to do something which I think is really great at just bringing people into this profession. Because there is quite a bit of intimidation rate where people are like, "Oh, I don't know math. I don't know statistics. I don't think I could do this." And I think the good news is if you have a curious mind and you really want to break into this space, there are definitely roles available that can get you in there, right? So you mentioned data scientist, which I think it's a popular term, but I think we're still in a place where we're sometimes calling a role of a data scientist a data analyst, and a data analyst a data scientist. And I think there's still a bit of a misunderstanding between job descriptions and rules that people are applying for. So I think we definitely need standardization and some clarity on what each role actually does.
KATE 07:52	But I do want to answer your other question where you ask what are some other types of roles? So we have data analysts, we have business analysts, we have data scientists, data engineers, machine learning engineers, analytics engineers, chief data officers, right? There are just so many types of roles out there. And then you can't forget data stewardships, so taking care of data quality and data governance. There's just such a wide spectrum of roles out there that I think it makes sense to take the time and get an understanding of what are the types of activities you like to do personally before you start trying to get a job in data. Get an understanding, talk to some people, have those job titles, and actually ask them like, "Hey, data engineer, what do you do all day? Tell me exactly what you do." And I'm actually trying to address this problem with a course. Another course I'm working on for LinkedIn Learning, it's all about data careers. So we're trying to demystify the roles and talk through some of the nuances, some of the differences between the roles that we just discussed.
MARIEM 08:47	Yeah. And also something that I think has become popular is just the idea of data literacy. So even if your role or actual career is not quite any of the ones we just discussed, some sort of learning around data has become a bit more popular and more availability around that.
KATE 09:04	Yes, absolutely. I think everyone should be data literate to some extent. I don't think we all need to know what the p-value is or imputations. But I think depending on what you do for a living, you should have some understanding of data and trying to understand differences between different chart types and how to read data, how to read data that you see in the news or on social media, and the importance of actually questioning what you're seeing and not taking things for granted just because it's a pretty chart, I'm going to accept it as fact, right? We need to move away from that. I even wrote a book with Jordan Morrow called Data Literacy for Kids because I think it starts with kids. We need to learn about this kind of stuff. Age six and up is what I'm thinking.
MARIEM 09:49	I will pivot us to now the topic I'm very excited about: branding. And I'll try to be the voice of all the ranges of people out there because you'll have folks that are actively trying to figure out their brand and strengthening it. And we'll shortly bring up the topic of how to be successful at that. But also you'll have people that either feel shy about it or maybe already are getting some good internal recognition from their manager or their team, and they don't see the need maybe to be vocal out there. Some people see it as maybe bragging and it feels uncomfortable. So maybe starting with this latter group, the why. Why does building a brand matter?
KATE 10:33	Yeah. So let's start with the why. So I think building a brand is important for a couple of reasons. Number one, it helps you stand out from your competition. So now if we're in the mindset of an individual who's trying to break into the data career, for example, there are a lot of people like you out there who also want to get a cool job in data, whatever career you decide to go with. And the issue becomes that if it's such a cool job and everybody wants it, there's competition, right? So when there's competition, it's important to stand out so that you are the one who selected for that specific job.
KATE 11:08	The other side of it is opening things up to opportunities, right? I think when you have a strong personal brand, like it or not, you're going to become a magnet for specific opportunities related to that brand. I can talk about this for a pretty long time because I've been extremely lucky to have had several opportunities come my way for the simple fact that I post content on LinkedIn, right? I talk about data all the time. And because of that, people want you to speak at conferences, people want you to write books, people want you to be a part of whatever they're doing. They want to give you jobs. Like I said, number of opportunities are just unreal. It feels like magic. But when you think about it, it just makes sense. When you have a personal brand and you're known for something, when people have that need, they're looking to fill a need, they're like, "Oh, Kate does data. Let's ask Kate." So you catch all the opportunities. You might not want them all, right? But at least you can pass them on to your friends if that's not something you're looking for. But yeah, those are some reasons for the why.
MARIEM 12:12	Yeah. It almost speaks for itself. It gives you that little opener that's out there already, I guess, when getting started somewhere or going for an interview. And maybe one other thought that we hear out there. I'll continue to play the devil's advocate just a teeny bit, but some people might see it as maybe posting a lot on social media or trying to build a brand is maybe a distraction or maybe it's not welcomed in the workspace. How would you answer that? I personally think there are so many ways to combine it so that it's very relevant, actually, to what you do. Maybe you could do courses within your company, things of that sort. But to maybe address this misconception, thoughts on that?
KATE 12:54	Yes. And I think you bring up a very good point because there might be people trying to build a brand who, let's say, already have a job. And not everybody wants to be this celebrity like a person that everybody recognizes. Some people like to maintain a lower profile, but I think those individuals should still consider building a strong personal brand, maybe even internally within a company that you're working for. It doesn't have to be as public as posting on LinkedIn twice a day. It could be hosting maybe a lunch and chat with your organization employees who are interested in the specific topic that you want to build your personal brand on. Let's say you're really good at PowerPoint, right? That's your thing. You could do a PowerPoint training. Come join me for 45 minutes while you're having lunch, or do a little webinar, have your coworkers join. Now, you're known as the go-to person for PowerPoint, right? So it is as easy as that. Obviously, you'll put some work into putting together a 45-minute webinar. But if it's something you're truly passionate about and you love doing, you'll probably have fun doing that too.
MARIEM 14:00	Yeah. And speaking of fun, we can now also talk about the how. So branding matters and maybe the next thing people think is, "Okay, but how do I determine my personal brand?"
KATE 14:17	Yeah. So I think it's also good to define what is a personal brand, right? So a personal brand is what people think about you sometimes when you're not even there. I'll give you an example. When you leave the room and have a friend of yours sit in that room and say, "Hey, what do you think about Mariem? What do you think she's good at? What do you think she knows?" If people jot down five things, chances are there'll be different things, but there will definitely be overlap. They're going to say, she's good at this, she's good at that. And that compilation of what people already think about you could be the start of your personal brand, at least your existing personal brand. I think from there, you have to decide, is this what I want to be known for?
KATE 14:54	Because back when I had an actual job in an organization, I was the person who was known for the PowerPoint. The example I brought up earlier. And I didn't want to be known for this. I liked it, I enjoyed it. But when other people come to you and say, "Hey, Kate. Can you clean up this deck?" And I'm like, "Sure." They're like, "You're so good at it." And I'm like, "Yeah, okay. Thanks." So you might have a personal brand that you don't want to be your personal brand. So that takes some work because now you have to define what are the things you want to be known for and then start working towards sort of revamping your brand to become what it is you want to be known for.
KATE 15:30	So, for me, things like data storytelling, data visualization, personal branding, I like to talk about that a lot. Social media, LinkedIn, running. So it can be a compilation of different things. But I think it's good for you to just take a few minutes and define what exactly you want to be known for because that's going to drive the next step, which is actually building that personal brand.
MARIEM 15:52	Yeah. And I love that in other posts, you also talk about the idea that you should enjoy it, and it almost wouldn't feel like work. And that's one step. So even if you might be, like you were saying if I were to summarize, may be known for something that is not necessarily your personal brand, it might be something you want to be recognized for, even if it's something that you haven't quite mastered yet. Also, I love the idea that you mentioned, a target audience versus getting one post that gets hundreds and thousands of views. This idea of figuring out what is it that you're aiming towards?
KATE 16:27	Yes. That is a very good point because I think a lot of times we get confused and a little bit caught up with the metrics, right? Let's say we start posting. We're not seeing much traction. It's like screaming into an empty room with your first couple of posts. No one's liking it, no one's commenting. You're frustrated. You're like, "I'm investing my time. It took me an hour to create this post." Especially the first few posts, I noticed it takes people a pretty long time because they're either a perfectionist or they just don't want someone to say they're wrong about something. It doesn't have to be that complicated. But I know humans are complicated. We tend to just make things more difficult for ourselves. And I think first simplify it. No one's really going to over-analyze your post. But then once you actually post it, it gets frustrating and you're like, "No one's listening to me. No one cares." But getting over that fact and understanding that you have a specific perspective that you can share with your audience, I think, will go a long way.
MARIEM 17:26	Yeah, no, I can't agree anymore. Another thing, maybe getting into the hands-on side of things, people often wonder, okay, but what means should I do? A short post or long post or videos? Or if I'm in the programming, maybe like code on Stack Overflow and make a name out of myself. So the idea of experimenting with means, how do you recommend people to navigate what sort of works for them?
KATE 17:51	I think it starts with trying to understand what you're trying to accomplish. And sorry, I didn't answer your original question about your audience. I'll just briefly touch on that one because it relates to the type of content you're going to post as well. So at first, defining the people you want to view your content, right? Do you care who views it? Probably, right? If you're trying to build a brand in data, well, you probably want data professionals or people who care about data to watch your content. You don't want someone maybe in construction or in the furniture business unless they're somehow going to work with data in the future to be liking your content. They can, but it's not really going to give you what you're looking for. A lot of times, we're looking for either job opportunities, consulting gigs, speaking opportunities, or just being recognized as a thought leader. So creating the type of content that will deliver value to your specific audience is extremely important.
KATE 18:48	We can't get caught up in putting a post out there just because it's going to receive 1,000 likes. You can almost create a post that will become viral because you know how to touch on some of the hot issues maybe that will trigger people like some polarizing topic. But you have to take a step back and think, "Is this really what I want?" Because you might get a ton of engagement and traffic, but it might not be from the right audience. So that answers that prior question about defining who you want to see your content. Who would be the best person to see it? If you're looking for a job, it's probably hiring managers at the specific industry you want to work in.
KATE 19:26	And quick side note there, if you want to work in, let's say, the financial services industry, then go ahead and connect with maybe chief data officers, chief data scientists, or anyone in data professionals in those organizations. Because once you connect with them, what happens is they start seeing your content in their feed. So it's not gaining the system, but you're basically inviting them into a room where you're going to be speaking. Otherwise, they won't even be in that room so who are you talking to?
MARIEM 19:57	Fair, fair.
KATE 19:58	But in terms of the format, there are so many ways you can go about this. And I think a little part of it is personality driven. So some people love to be on camera and they're fine with live streaming and putting together great videos and editing them. Others prefer audio podcasts. Sometimes you prefer pictures, text, long-form text, short-form text, or polls. And I think you should not just do one thing. I think experiment with all of those formats. It is fun. I think if you just come to terms with the fact that it's not scary and that you can have fun with it. I probably use all of those mediums just because I like to experiment and see what's working, what's not working. And different platforms are good for different things. If you love taking pictures, Instagram is your thing. Long-form videos, you'd probably do well on YouTube. So depending on your personality and your style, I think that can actually drive you towards selecting the platform that you're going to grow in as well.
MARIEM 20:58	And actually speaking of platforms, say for posting since maybe that's the easiest thing to start with, you'll have things like medium.com, LinkedIn, Towards Data Science, KDnuggets. Would you, let's say, quote-unquote, "copy-paste" across those platforms? Are some more known for certain things or is there may be an advantage to sticking to one platform since a blog is a blog, at the end of the day?
KATE 21:23	Again, it goes back to what is your goal. I think if your goal is to reach more people, then I don't see the harm in copy-pasting or maybe editing it a little bit to make it slightly different for each of those platforms. I am definitely guilty of copy-pasting. If I have a podcast and I have some show notes, I'll put it on my website, I'll put it on Medium, sometimes publish it on Towards Data Science or somewhere else. I haven't seen any up or downside from either doing it or not doing it. But again, it goes back to what are you trying to accomplish. Sometimes people are trying to build their own blog site and they want that traffic to their web page, then I would say maybe avoid putting it on LinkedIn and Medium because then you're diluting that traffic. If you want all that traffic directed to the site, keep it on the site.
MARIEM 22:07	Awesome. Another fun topic around hosting are hashtags, which I think we all notice that they're super commonly used and are relevant and helpful. But something I liked that you had mentioned is also little tips like checking how many followers that specific hashtag has. But another thing that I didn't think about before is this idea of don't put a bunch of them. It seems obvious, but at the same time, I think we easily fall into that from time to time. So maybe tell us more about the disadvantages at times to stay focused and things of that sort.
KATE 22:42	Yeah. And I think this is very platform driven as well. So I'll first cover LinkedIn because that's my main platform that I use. I'd say anywhere between two to five hashtags is probably acceptable. And in terms of placement, I typically place them all the way at the end of the post for the reason being I want the hashtag to trigger those who are interested in those topics to show up in their feed. But I don't want them inside the body of the text because that seems to be distracting to a lot of people. It just catches your eye in the wrong way. Specific hashtag and you can't even space them out because you need, let's say, two or three words, it's all one word and starts to look awkward. So it's almost robotic. And in terms of followers, yeah, on LinkedIn, you can actually look up a hashtag to see how many followers it has. So I'd say unless you're going to use a unique hashtag for a very long time, I'd avoid creating specific hashtags. Let's say, DATAcated loves data hashtag. Something super random like that. Because there are no followers. You're literally just cluttering space. It's like throwing paint at a painting for no reason. But if you use a hashtag, like hashtag data or hashtag analytics, that has probably hundreds of thousands, if not a million followers of that specific word, that is more-- it makes more sense because now it shows up in the feed, it's a shorter hashtag, and it takes up less space.
KATE 24:02	And then I'll briefly cover something like Instagram, where I know people use like 20, 30 hashtags. And I think that's the accepted norm. Not sure why. I think it's crazy when you have this big paragraph of hashtags, but people do it. I think that is the acceptable way of using hashtags on that platform. Just learn the platform that you're working with. YouTube is also great. You have to add hashtags, and I think you have 300 characters that you can add. So using those will definitely help you with showing up in search. So do the research on the platform that you're using.
MARIEM 24:33	There's so much more that I'd like us to talk about, but at least I know that some of this content is also covered and the courses that you have and the books. And I'd love to have a little call of action for the exciting things that you have coming up and tell the audience how and where they can follow you. But maybe a little side parentheses that's tangential to this. In a prior book, The Disruptors, you interview Dr. DJ Patil. And for people in the audience, he is the first United States chief data scientist. He was announced back in 2015 by former President Barack Obama. Tell us a little bit about that experience and any highlights from the discussion with them.
KATE 25:15	Yes. The Disruptors: Data Science Leaders. It was a book I actually wrote in 2018. It was my attempt to highlight 10 data science leaders in our world right now, just to hear their journey. How did they get to their specific roles? What's the outlook for the future? What are some of the innovative things that they're working on? And the way I went about coming up with that list is just doing some research and picking the names that are like, "Oh, my God. Will they really speak to me and let me interview them and let me put them in my book?" DJ Patil was one of the first people on my list. And obviously, I wanted the first chief data scientist at the White House. I messaged them directly on LinkedIn. This is why I love LinkedIn. The barrier to just reaching people is so small. He actually responded to my shock. I think we're still not actually connected on the platform, but you can still message [inaudible]. So I messaged him and he responded. He's like, "What's this book?" And he's like, "Oh, I don't know. Maybe I'll participate." Long story short, he ended up saying yes. We got on a call. I told him what I'm trying to accomplish and then he gave me an hour of his time to really just ask him a bunch of questions, record the conversation, and put that conversation into the book.
KATE 26:29	I was shocked. I still am shocked that some of the people in this book actually said yes because it was almost at the very beginning of my content creation career, my data career, and the fact that all these really busy and awesome individuals were willing to participate. It was so heartwarming. I'm like, this data community is awesome. So I absolutely love the community.
MARIEM 26:52	Super cool.
KATE 26:53	Yeah, definitely. My DJ Patil story.
MARIEM 26:54	I love that when you and I were briefly chatting before, if anything, this is another proof of why branding is important and the types of connections and amazing experiences that you can come across, basically. But let me make sure to give you time for telling us how people can follow you and the things that are upcoming.
KATE 27:13	Oh, yeah. Thank you so much. People can follow me on LinkedIn, or if you want to follow me on YouTube, it's DATAcated. I am trying to create more video content for that platform. You can also go to datacated.com. I have a community of my own called The DATAcated Circle, where I have some courses. We're actually adding an Alteryx course. Hopefully, when people hear this, we're already on our way to including that course in The DATAcated Circle. I'm also writing a book called ColorWise that is set to launch either late in 2022 or early 2023. It's all about using color intentionally and properly for data visualization and data storytelling. So you'll probably find that on Amazon. But besides that, yeah, I think LinkedIn is the best place to connect to chat. Feel free to reach out.
MADDIE 28:02	Thanks for listening. For links to all of the resources mentioned in this episode, check out our show notes at community.alteryx.com/podcast. Catch you next time.

MADDIE 00:02 Welcome to Alter Everything, a podcast about data science and analytics culture. I'm Maddie Johannsen, and today I pass my hosting mic to my colleague, Mariem Ayadi. Mariem is a senior data scientist at Alteryx, and not only does she have the data science background and know-how, but Mariem is so easy to talk to and she loves helping people with their careers. So who better to interview our guest, Kate Strachnyi, the founder of DATAcated and host of the DATAcated on-air podcast? Kate is equally passionate about helping folks build their careers. So for this episode, Mariem and Kate chat about building your brand and data. So if you're curious about different careers in data and how you can stand out in an increasingly noisy world, especially on social media, this episode is for you. Let's get started. MARIEM 00:52 Good morning, good afternoon, and good evening everyone. My name is Mariem Ayadi. I'm a senior data scientist here at Alteryx, and I have the pleasure of having Kate with us today. Welcome to Alter Everything, Kate. KATE 01:07 Awesome. Thank you so much for having me here. MARIEM 01:10 We're really happy to have you and to have the show focus a little bit on the topic of careers in tech, but with a bit of a larger topic and sort of focus on building a brand and the data analytics tech space more broadly. First of all, however, I'd love to introduce you to our audience. You're someone who is extremely passionate about what you do, which includes helping people learn and navigate their careers in data. You have a podcast. You actively post on a variety of platforms. You've been a recognized LinkedIn top [creator?]. You have a continuously growing community. You have and continued to launch courses with the most recent one on LinkedIn Learning Platform. And though I'm sure I'm probably missing quite a few things, you have published and continued to publish books. So let me maybe pass it to you to tell us a little bit about your journey from a degree in finance to consulting to what you're doing today. And maybe over time, who has your target audience been in your various endeavors and how did those come about? KATE 02:20 Yeah, absolutely, I'd love to talk about all of that. And thank you so much for that introduction. I think you haven't missed anything from what I'm working on. Maybe conferences. I don't know if you mentioned conferences. Those are time-consuming, so I want to mention that. But yeah, the journey so far has been extremely fun. Like you mentioned, I started off with the green finance. I went on to do some sales in risk management, which led me to working in risk management, going into consulting, regulatory compliance all over the world of risk management, of regulatory compliance. And then about eight years ago, I shifted into data analytics. KATE 02:56 And for me personally, it was love at first sight. The first time I had a data set and I used Tableau to manipulate that data set and create data visualizations, I'm like, "Okay, this is where I'm supposed to be. I have found my people and I have found my world." And simultaneously, when I started getting into data, that's also when my social media career was born because I lived out loud and I thought that documenting my journey somewhere would be a fun thing to do. And I've chosen YouTube and LinkedIn as the platforms where I decided to document what I'm learning, who I'm speaking to, highlighting other professionals in this space. And yeah, that's what led me to starting my own company called DATAcated. And that's what keeps me busy these days. MARIEM 03:43 That's awesome. And who would you say your target audience has been maybe at the beginning, over time, now? KATE 03:51 Yeah. I think it started out being aspiring data professionals, data scientists, data analysts, those who wanted to break into the world of data. That's the audience I attracted because that's where I was in the beginning. So as I shared, "How do you use Tableau?" And, "How do you find data sets to train on and play with?" I think that attracted more of the students, the people trying to break into the career and following me on that journey. Now I'm in a place where I talk to all people in the data world. So it could be data engineers, chief data officers, data scientists, machine learning engineers, and it's all over the spectrum because part of what I do, you mentioned podcast, I have a live weekly show called The DATAcated Show that we host on Tuesdays at 11:00 AM Eastern. We bring on a variety of guests but we talk about different topics like data mass, data strategy, data observability. We do talk about branding. We talk about all these different topics. So it's taken me-- it's broadened my perspective in this space and it's also increased the connections that I'm able to make in the world of data. MARIEM 04:53 I love it, and I love that your work has an impact on such a broad set of people. Here at Alteryx, we have a really awesome analytics education program targeted at students, career switchers, and really all lifelong learners. And the program is called SparkED. We also have a highly active community where people from all different walks of life and different stages in their analytics journey help each other. For example, for me, something that was really special is meeting users of our products who initially had this sort of anxiety around the perceived learning curve when it comes to analytics, and hearing their story of how because our software is so intuitive, they just naturally learned the data and analytics lingo and the concepts without even realizing it, almost. And they were doing things like table joins, getting all sorts of mixed up input data to play nicely together, learning that fancy words like imputation just means that empty cells and nulls are really just things that maybe you should watch out for and probably handle when you're playing with data. MARIEM 06:03 So for a lot of our users, Alteryx was the mean that helped them embrace a career in data. And I'm really excited for us to hone in on this idea then of branding and why it matters in the first place. But maybe we cover a little bit of ground around data rules to give our audience a sense of the career paths that we've been alluding to or talking about today. People often default to the name data scientists, or at least I've seen that definition of the role, honestly, evolve over the years. So maybe what would you say is the latest on that and also just other roles out there which you started talking about? KATE 06:41 Yeah. I think it's great that you mentioned that there are some terms like imputations that might sound scary for people. And then they're doing it, they didn't realize they were doing it, they were like, "Oh wow, I can't believe I know how to do this." Because there are technologies like Alteryx and Tableau, I would say as well, that have made things so simple with the drag-and-drop features that it lets you do things without really thinking too much about it or having to study a whole textbook on how to do something which I think is really great at just bringing people into this profession. Because there is quite a bit of intimidation rate where people are like, "Oh, I don't know math. I don't know statistics. I don't think I could do this." And I think the good news is if you have a curious mind and you really want to break into this space, there are definitely roles available that can get you in there, right? So you mentioned data scientist, which I think it's a popular term, but I think we're still in a place where we're sometimes calling a role of a data scientist a data analyst, and a data analyst a data scientist. And I think there's still a bit of a misunderstanding between job descriptions and rules that people are applying for. So I think we definitely need standardization and some clarity on what each role actually does. KATE 07:52 But I do want to answer your other question where you ask what are some other types of roles? So we have data analysts, we have business analysts, we have data scientists, data engineers, machine learning engineers, analytics engineers, chief data officers, right? There are just so many types of roles out there. And then you can't forget data stewardships, so taking care of data quality and data governance. There's just such a wide spectrum of roles out there that I think it makes sense to take the time and get an understanding of what are the types of activities you like to do personally before you start trying to get a job in data. Get an understanding, talk to some people, have those job titles, and actually ask them like, "Hey, data engineer, what do you do all day? Tell me exactly what you do." And I'm actually trying to address this problem with a course. Another course I'm working on for LinkedIn Learning, it's all about data careers. So we're trying to demystify the roles and talk through some of the nuances, some of the differences between the roles that we just discussed. MARIEM 08:47 Yeah. And also something that I think has become popular is just the idea of data literacy. So even if your role or actual career is not quite any of the ones we just discussed, some sort of learning around data has become a bit more popular and more availability around that. KATE 09:04 Yes, absolutely. I think everyone should be data literate to some extent. I don't think we all need to know what the p-value is or imputations. But I think depending on what you do for a living, you should have some understanding of data and trying to understand differences between different chart types and how to read data, how to read data that you see in the news or on social media, and the importance of actually questioning what you're seeing and not taking things for granted just because it's a pretty chart, I'm going to accept it as fact, right? We need to move away from that. I even wrote a book with Jordan Morrow called Data Literacy for Kids because I think it starts with kids. We need to learn about this kind of stuff. Age six and up is what I'm thinking. MARIEM 09:49 I will pivot us to now the topic I'm very excited about: branding. And I'll try to be the voice of all the ranges of people out there because you'll have folks that are actively trying to figure out their brand and strengthening it. And we'll shortly bring up the topic of how to be successful at that. But also you'll have people that either feel shy about it or maybe already are getting some good internal recognition from their manager or their team, and they don't see the need maybe to be vocal out there. Some people see it as maybe bragging and it feels uncomfortable. So maybe starting with this latter group, the why. Why does building a brand matter? KATE 10:33 Yeah. So let's start with the why. So I think building a brand is important for a couple of reasons. Number one, it helps you stand out from your competition. So now if we're in the mindset of an individual who's trying to break into the data career, for example, there are a lot of people like you out there who also want to get a cool job in data, whatever career you decide to go with. And the issue becomes that if it's such a cool job and everybody wants it, there's competition, right? So when there's competition, it's important to stand out so that you are the one who selected for that specific job. KATE 11:08 The other side of it is opening things up to opportunities, right? I think when you have a strong personal brand, like it or not, you're going to become a magnet for specific opportunities related to that brand. I can talk about this for a pretty long time because I've been extremely lucky to have had several opportunities come my way for the simple fact that I post content on LinkedIn, right? I talk about data all the time. And because of that, people want you to speak at conferences, people want you to write books, people want you to be a part of whatever they're doing. They want to give you jobs. Like I said, number of opportunities are just unreal. It feels like magic. But when you think about it, it just makes sense. When you have a personal brand and you're known for something, when people have that need, they're looking to fill a need, they're like, "Oh, Kate does data. Let's ask Kate." So you catch all the opportunities. You might not want them all, right? But at least you can pass them on to your friends if that's not something you're looking for. But yeah, those are some reasons for the why. MARIEM 12:12 Yeah. It almost speaks for itself. It gives you that little opener that's out there already, I guess, when getting started somewhere or going for an interview. And maybe one other thought that we hear out there. I'll continue to play the devil's advocate just a teeny bit, but some people might see it as maybe posting a lot on social media or trying to build a brand is maybe a distraction or maybe it's not welcomed in the workspace. How would you answer that? I personally think there are so many ways to combine it so that it's very relevant, actually, to what you do. Maybe you could do courses within your company, things of that sort. But to maybe address this misconception, thoughts on that? KATE 12:54 Yes. And I think you bring up a very good point because there might be people trying to build a brand who, let's say, already have a job. And not everybody wants to be this celebrity like a person that everybody recognizes. Some people like to maintain a lower profile, but I think those individuals should still consider building a strong personal brand, maybe even internally within a company that you're working for. It doesn't have to be as public as posting on LinkedIn twice a day. It could be hosting maybe a lunch and chat with your organization employees who are interested in the specific topic that you want to build your personal brand on. Let's say you're really good at PowerPoint, right? That's your thing. You could do a PowerPoint training. Come join me for 45 minutes while you're having lunch, or do a little webinar, have your coworkers join. Now, you're known as the go-to person for PowerPoint, right? So it is as easy as that. Obviously, you'll put some work into putting together a 45-minute webinar. But if it's something you're truly passionate about and you love doing, you'll probably have fun doing that too. MARIEM 14:00 Yeah. And speaking of fun, we can now also talk about the how. So branding matters and maybe the next thing people think is, "Okay, but how do I determine my personal brand?" KATE 14:17 Yeah. So I think it's also good to define what is a personal brand, right? So a personal brand is what people think about you sometimes when you're not even there. I'll give you an example. When you leave the room and have a friend of yours sit in that room and say, "Hey, what do you think about Mariem? What do you think she's good at? What do you think she knows?" If people jot down five things, chances are there'll be different things, but there will definitely be overlap. They're going to say, she's good at this, she's good at that. And that compilation of what people already think about you could be the start of your personal brand, at least your existing personal brand. I think from there, you have to decide, is this what I want to be known for? KATE 14:54 Because back when I had an actual job in an organization, I was the person who was known for the PowerPoint. The example I brought up earlier. And I didn't want to be known for this. I liked it, I enjoyed it. But when other people come to you and say, "Hey, Kate. Can you clean up this deck?" And I'm like, "Sure." They're like, "You're so good at it." And I'm like, "Yeah, okay. Thanks." So you might have a personal brand that you don't want to be your personal brand. So that takes some work because now you have to define what are the things you want to be known for and then start working towards sort of revamping your brand to become what it is you want to be known for. KATE 15:30 So, for me, things like data storytelling, data visualization, personal branding, I like to talk about that a lot. Social media, LinkedIn, running. So it can be a compilation of different things. But I think it's good for you to just take a few minutes and define what exactly you want to be known for because that's going to drive the next step, which is actually building that personal brand. MARIEM 15:52 Yeah. And I love that in other posts, you also talk about the idea that you should enjoy it, and it almost wouldn't feel like work. And that's one step. So even if you might be, like you were saying if I were to summarize, may be known for something that is not necessarily your personal brand, it might be something you want to be recognized for, even if it's something that you haven't quite mastered yet. Also, I love the idea that you mentioned, a target audience versus getting one post that gets hundreds and thousands of views. This idea of figuring out what is it that you're aiming towards? KATE 16:27 Yes. That is a very good point because I think a lot of times we get confused and a little bit caught up with the metrics, right? Let's say we start posting. We're not seeing much traction. It's like screaming into an empty room with your first couple of posts. No one's liking it, no one's commenting. You're frustrated. You're like, "I'm investing my time. It took me an hour to create this post." Especially the first few posts, I noticed it takes people a pretty long time because they're either a perfectionist or they just don't want someone to say they're wrong about something. It doesn't have to be that complicated. But I know humans are complicated. We tend to just make things more difficult for ourselves. And I think first simplify it. No one's really going to over-analyze your post. But then once you actually post it, it gets frustrating and you're like, "No one's listening to me. No one cares." But getting over that fact and understanding that you have a specific perspective that you can share with your audience, I think, will go a long way. MARIEM 17:26 Yeah, no, I can't agree anymore. Another thing, maybe getting into the hands-on side of things, people often wonder, okay, but what means should I do? A short post or long post or videos? Or if I'm in the programming, maybe like code on Stack Overflow and make a name out of myself. So the idea of experimenting with means, how do you recommend people to navigate what sort of works for them? KATE 17:51 I think it starts with trying to understand what you're trying to accomplish. And sorry, I didn't answer your original question about your audience. I'll just briefly touch on that one because it relates to the type of content you're going to post as well. So at first, defining the people you want to view your content, right? Do you care who views it? Probably, right? If you're trying to build a brand in data, well, you probably want data professionals or people who care about data to watch your content. You don't want someone maybe in construction or in the furniture business unless they're somehow going to work with data in the future to be liking your content. They can, but it's not really going to give you what you're looking for. A lot of times, we're looking for either job opportunities, consulting gigs, speaking opportunities, or just being recognized as a thought leader. So creating the type of content that will deliver value to your specific audience is extremely important. KATE 18:48 We can't get caught up in putting a post out there just because it's going to receive 1,000 likes. You can almost create a post that will become viral because you know how to touch on some of the hot issues maybe that will trigger people like some polarizing topic. But you have to take a step back and think, "Is this really what I want?" Because you might get a ton of engagement and traffic, but it might not be from the right audience. So that answers that prior question about defining who you want to see your content. Who would be the best person to see it? If you're looking for a job, it's probably hiring managers at the specific industry you want to work in. KATE 19:26 And quick side note there, if you want to work in, let's say, the financial services industry, then go ahead and connect with maybe chief data officers, chief data scientists, or anyone in data professionals in those organizations. Because once you connect with them, what happens is they start seeing your content in their feed. So it's not gaining the system, but you're basically inviting them into a room where you're going to be speaking. Otherwise, they won't even be in that room so who are you talking to? MARIEM 19:57 Fair, fair. KATE 19:58 But in terms of the format, there are so many ways you can go about this. And I think a little part of it is personality driven. So some people love to be on camera and they're fine with live streaming and putting together great videos and editing them. Others prefer audio podcasts. Sometimes you prefer pictures, text, long-form text, short-form text, or polls. And I think you should not just do one thing. I think experiment with all of those formats. It is fun. I think if you just come to terms with the fact that it's not scary and that you can have fun with it. I probably use all of those mediums just because I like to experiment and see what's working, what's not working. And different platforms are good for different things. If you love taking pictures, Instagram is your thing. Long-form videos, you'd probably do well on YouTube. So depending on your personality and your style, I think that can actually drive you towards selecting the platform that you're going to grow in as well. MARIEM 20:58 And actually speaking of platforms, say for posting since maybe that's the easiest thing to start with, you'll have things like medium.com, LinkedIn, Towards Data Science, KDnuggets. Would you, let's say, quote-unquote, "copy-paste" across those platforms? Are some more known for certain things or is there may be an advantage to sticking to one platform since a blog is a blog, at the end of the day? KATE 21:23 Again, it goes back to what is your goal. I think if your goal is to reach more people, then I don't see the harm in copy-pasting or maybe editing it a little bit to make it slightly different for each of those platforms. I am definitely guilty of copy-pasting. If I have a podcast and I have some show notes, I'll put it on my website, I'll put it on Medium, sometimes publish it on Towards Data Science or somewhere else. I haven't seen any up or downside from either doing it or not doing it. But again, it goes back to what are you trying to accomplish. Sometimes people are trying to build their own blog site and they want that traffic to their web page, then I would say maybe avoid putting it on LinkedIn and Medium because then you're diluting that traffic. If you want all that traffic directed to the site, keep it on the site. MARIEM 22:07 Awesome. Another fun topic around hosting are hashtags, which I think we all notice that they're super commonly used and are relevant and helpful. But something I liked that you had mentioned is also little tips like checking how many followers that specific hashtag has. But another thing that I didn't think about before is this idea of don't put a bunch of them. It seems obvious, but at the same time, I think we easily fall into that from time to time. So maybe tell us more about the disadvantages at times to stay focused and things of that sort. KATE 22:42 Yeah. And I think this is very platform driven as well. So I'll first cover LinkedIn because that's my main platform that I use. I'd say anywhere between two to five hashtags is probably acceptable. And in terms of placement, I typically place them all the way at the end of the post for the reason being I want the hashtag to trigger those who are interested in those topics to show up in their feed. But I don't want them inside the body of the text because that seems to be distracting to a lot of people. It just catches your eye in the wrong way. Specific hashtag and you can't even space them out because you need, let's say, two or three words, it's all one word and starts to look awkward. So it's almost robotic. And in terms of followers, yeah, on LinkedIn, you can actually look up a hashtag to see how many followers it has. So I'd say unless you're going to use a unique hashtag for a very long time, I'd avoid creating specific hashtags. Let's say, DATAcated loves data hashtag. Something super random like that. Because there are no followers. You're literally just cluttering space. It's like throwing paint at a painting for no reason. But if you use a hashtag, like hashtag data or hashtag analytics, that has probably hundreds of thousands, if not a million followers of that specific word, that is more-- it makes more sense because now it shows up in the feed, it's a shorter hashtag, and it takes up less space. KATE 24:02 And then I'll briefly cover something like Instagram, where I know people use like 20, 30 hashtags. And I think that's the accepted norm. Not sure why. I think it's crazy when you have this big paragraph of hashtags, but people do it. I think that is the acceptable way of using hashtags on that platform. Just learn the platform that you're working with. YouTube is also great. You have to add hashtags, and I think you have 300 characters that you can add. So using those will definitely help you with showing up in search. So do the research on the platform that you're using. MARIEM 24:33 There's so much more that I'd like us to talk about, but at least I know that some of this content is also covered and the courses that you have and the books. And I'd love to have a little call of action for the exciting things that you have coming up and tell the audience how and where they can follow you. But maybe a little side parentheses that's tangential to this. In a prior book, The Disruptors, you interview Dr. DJ Patil. And for people in the audience, he is the first United States chief data scientist. He was announced back in 2015 by former President Barack Obama. Tell us a little bit about that experience and any highlights from the discussion with them. KATE 25:15 Yes. The Disruptors: Data Science Leaders. It was a book I actually wrote in 2018. It was my attempt to highlight 10 data science leaders in our world right now, just to hear their journey. How did they get to their specific roles? What's the outlook for the future? What are some of the innovative things that they're working on? And the way I went about coming up with that list is just doing some research and picking the names that are like, "Oh, my God. Will they really speak to me and let me interview them and let me put them in my book?" DJ Patil was one of the first people on my list. And obviously, I wanted the first chief data scientist at the White House. I messaged them directly on LinkedIn. This is why I love LinkedIn. The barrier to just reaching people is so small. He actually responded to my shock. I think we're still not actually connected on the platform, but you can still message [inaudible]. So I messaged him and he responded. He's like, "What's this book?" And he's like, "Oh, I don't know. Maybe I'll participate." Long story short, he ended up saying yes. We got on a call. I told him what I'm trying to accomplish and then he gave me an hour of his time to really just ask him a bunch of questions, record the conversation, and put that conversation into the book. KATE 26:29 I was shocked. I still am shocked that some of the people in this book actually said yes because it was almost at the very beginning of my content creation career, my data career, and the fact that all these really busy and awesome individuals were willing to participate. It was so heartwarming. I'm like, this data community is awesome. So I absolutely love the community. MARIEM 26:52 Super cool. KATE 26:53 Yeah, definitely. My DJ Patil story. MARIEM 26:54 I love that when you and I were briefly chatting before, if anything, this is another proof of why branding is important and the types of connections and amazing experiences that you can come across, basically. But let me make sure to give you time for telling us how people can follow you and the things that are upcoming. KATE 27:13 Oh, yeah. Thank you so much. People can follow me on LinkedIn, or if you want to follow me on YouTube, it's DATAcated. I am trying to create more video content for that platform. You can also go to datacated.com. I have a community of my own called The DATAcated Circle, where I have some courses. We're actually adding an Alteryx course. Hopefully, when people hear this, we're already on our way to including that course in The DATAcated Circle. I'm also writing a book called ColorWise that is set to launch either late in 2022 or early 2023. It's all about using color intentionally and properly for data visualization and data storytelling. So you'll probably find that on Amazon. But besides that, yeah, I think LinkedIn is the best place to connect to chat. Feel free to reach out. MADDIE 28:02 Thanks for listening. For links to all of the resources mentioned in this episode, check out our show notes at community.alteryx.com/podcast. Catch you next time.

This episode was produced by Maddie Johannsen (@MaddieJ), and Mike Cusic (@mikecusic). Special thanks to @andyuttley for the theme music track, and @mikecusic for our album artwork.

Alter Everything

Episode Guide

115: Building your data analytics brand

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This episode was produced by Maddie Johannsen (@MaddieJ), and Mike Cusic (@mikecusic). Special thanks to @andyuttley for the theme music track, and @mikecusic for our album artwork.