Jonas Christensen 2:51
Ravit Jain, welcome to Leaders of Analytics. It is so good to have you on the show.
Ravit Jain 3:00
Awesome. Thanks, Jonas, for having me on the show. I've heard your podcast. To be honest, I loved it, even the recent episode with Kate or your episode with Kirk Borne. You know, I've learned so much. So, super excited to be here. Thank you for having me on.
Jonas Christensen 3:13
Oh look, Ravit, thank you so much for the support. I love when I get listeners feedback and when I get it from someone like you it means even more. So thank you for that. Now, this is obviously not about me, but all about you. The listeners are dying to hear more about you. So, perhaps you could tell us a bit about yourself and your background and what you do?
Ravit Jain 3:33
Yeah, definitely. So, like you mentioned, obviously, I have my own podcast, which is The Ravit Show. It's a live show on LinkedIn, YouTube, Facebook, and many other platforms and also distributed on Anchor. It's been almost close to one and a half years since I've been hosting this and I've had various CEOs, CTOs, Product Managers, Engineers, who have visited the show and these are from various fields not limited to just data science, but also AI, machine learning engineers. And also I've had different guests from human resource field. So, the basic idea or what I'm trying to say is obviously I don't limit my show to just folks from one field rather I keep it like, it's like a broad spectrum where the audience can learn a lot about these fields and these are experts who definitely share a lot. You know, I come from very different background. To be honest, I come from a finance background. Whereas, did my MBA in finance and also my executive MBA in investment banking. So, I've been often asked by people, ''Why and how did you actually land into data science and AI field?'' and that's very interesting, because I started my first job in something like market research and analytics and I was actually creating reports there. I was making sure that I'm compiling the right primary and secondary data we use to actually go out there and make calls, do extensive research into white papers, other informative articles and get those data extracted and create market research reports. And that's one of the reasons, you know, when I actually understood how important data is to the world right now. How important these reports are two companies, because these were companies which used to actually want these reports. And these reports could be any report on a mobile, on a pen or a paper or on a desktop. It could be into chemical. So, that's where my journey started and I realised that data plays a very important role. And also at the same time, it was something which I really liked doing, to get into specific products and learn about them, about the market and forecast them down the line seven to eight years how will that actually turn out to be. That's where my journey started. I then had an opportunity to come back to my hometown, which is Mumbai though my first job started in Pune, which was near to Mumbai, my hometown. And then I started with Packt Publishing, which is a tech publisher and I worked in various roles there, starting from commissioning a book to content marketing, to making sure the content that goes out to the public, to our audience is right. And then I had a fantastic opportunity towards the end of my journey at Packt, which was a community manager, where I closely worked with their co-authors and made sure that their books are amplified at a global level, making sure that I get into those small communities. For example, if we are actually coming up with a book, which is Transformers for NLP, obviously, I would want to get into communities and would want to reach out to people who are into NLP field and get their insights on this book. And this could be pre-publication or post publication, which is very important for the author to get the right feedback. Obviously, feedbacks kind of make the product very well. It kind of gets the right idea of what the audience needs. So, I used to actually work in different areas and different fields and different authors. So, that kind of gave me fantastic exposure to come closer to various communities and that's one of the reasons I could relate. I could actually bring that to my podcast as well, where I didn't want to limit it to just one topic. But I wanted to make sure that I am actually covering a lot of ground because while working at Packt Publishing, obviously, as a community manager, I got into many communities and many people. So, it gave me an opportunity to not only explore just one field, but reach out to many field experts, subject matter experts. Made some great relationships there and obviously learned about their journey. And that's when I wanted to start my own podcast and get on with it. But, yeah, that's my journey, I would say, which actually played a very important role in how I got into this field. And obviously, I recently had a great gig with ODSC, which is Open Data Science Conference and I made sure I was closely working with speaker team, marketing team, also the community engagement. Though it was a short journey, since I just wanted to do it for a few months. So, explored that as well. I have something on the cards that I will be announcing 2022 Jan. So, just keeping my fingers crossed on that thing. It's a big news, which I will definitely be announcing very soon. But that's been my journey. I am a community person, Jonas. To be honest, I love to help the community. I love to make sure that I am sharing the right resources. You might actually see me sharing a lot of free resources, book recommendations, also projects by people and helping companies also to amplify their products and services through The Ravit Show. I have my own newsletter. I have my show. I have my page. I am an advisor for Love Open Source Community, which was recently started by Aditi Khinvasara, helping her on those lines. And yeah, that's just little about me.
Jonas Christensen 9:06
Yeah, that's a big summary. For me, as someone who spends a bit of time on LinkedIn and follows data science topics, there is no way to avoid Ravit and his content. It is everywhere on LinkedIn. I see it every day and I love it. So, the other thing you talked about there was Packt and your time there. Packt is really a company or book publisher that in my opinion has had a huge positive impact on the data science community because it's such a nascent field and it's such an ever evolving field. It's actually very hard to create books and content that are very contemporary and relevant for the moment, but five years later they're not relevant anymore.
Ravit Jain 9:48
Exactly.
Jonas Christensen 9:50
When you started that role, how did you make sure that you found the right offers, got the right content and distributed it to the right audience?
Ravit Jain 9:59
Yeah. That's a fantastic question, Jonas, because what I feel it is a big task when you say you are a publisher. You need to evolve with the world because there's - If you talk about programming languages as well, what you might have seen, say, seven years back, which was booming is not even there right now. Rather, you will see a completely new programming language out there and people wanting to learn more about it. It's a journey, which takes a lot of research when you talk about building books or finding the right authors, because what happens in the journey is, first thing you need to start with the research and want to make sure what is the right market fit and what people want to learn about. If it's about writing, which is like the go-to language today? Most of the folks are into writing. And if you are wanting to create a product, which is a book, you would want to do a fantastic research on what is the actual problem of the people out there, the programmers out there and what are they wanting to learn? The first step is get into the research, do the right work. First find your right market fit. Understand your audience. How do you want to solve the problem through this product? So it's basically bridging the gap between the business and the audience, the readers, and making sure that you are being the right problem solver for them through research, through finding the right authors, through making sure that you are actually putting out a material which is up to date or at least when you basically - I'll just share the idea how it is done. When you go out and sign author and when the author is on board, obviously, it is very interesting because you are getting into an agreement which is for a product which will be released like nine months later. And you need to be like - Author starts writing a chapter today on say, Introduction to Python, and there is a release after six months. There is a version released that comes in. So, you need to make sure that on the nine month the first chapter has to be changed again, because there is a new version released that has come in. So, those are the things where you need to be very sharp about making sure the right product is going out. You have those type of relationships with the authors, as well. That in these nine months, if things are evolving, we need to evolve simultaneously and we'll be coming out with a fantastic product. It's a big journey, I would say. It's like a long, long journey where you go on with an author for like, six to nine months and then the product is ready almost after a year. A book is out and Packt has more than 6000 books. I might be wrong with the number but it has a lot of textbooks and some are like evergreen books. But as you definitely mentioned, there are books, which has to evolve over time. And I really remember when in my team at least, we used to be in the Packt expert network team and we used to come up with like 50 books. Just one team used to come up with 50 books. Maybe the other team might have like 200 books that they used to release. So, it's close to many products that could come out. I think the field is that big. We're not limiting it to data science, or AI. They also have books in cybersecurity programming and a lot of things. Whatever you see in tech world, they might have a book on it. So yeah,
Jonas Christensen 13:28
Yeah, nice. And it sounds like your spark which led to the interest in data and the data community was really created when you were at Packt. One, is that fair to say and secondly, what was it about this subject and the people you met that lit this spark inside you?
Ravit Jain 13:47
Yeah, I think it's a mix of both. You know, when I was at Packt, obviously, I got an opportunity to work with these authors who were fantastic and have shared, like, - I've learned a lot from them. And it kind of gave me an hope where you know, this field has so much to explore, you need to go out there and do different things. You need to help the community. You can actually build your own community, which I did with The Ravit Show as well. And at the same time, when I started doing that, obviously it motivated me to learn more about data science, about this community and making sure that how can I be of help to this community, even that 1%? If that contribution kind of comes in right, I'll be in a better place to make a good career choice and at the same time, I won't even call it my career. Rather, it's more of a passion for me right now where I can help the community. I'm more responsible towards them. I feel like that and just do the right things for them in terms of even recommending courses or sharing books or helping authors or interviewing CEOs, CDOs and making sure what the new product that they are coming out with. So, it's like a 360 degree circle where I am going around not only from students to the CEOs and CDOs but also making sure that it is a great help to the community in various ways. So, trying my best there. And that's one of the things which encouraged me to do a lot in this field, because I've got a lot of encouragement, motivation from people that are great friends. Obviously friends like Kate Strachnyi, Tom Mills, Danny Ma. These people are fantastic and you have a lot to learn from them. So, once you get into the community, it's more about learning from each other. You have great leaders there where you can, - you know are up for the guidance, who are up for mentorships as well. So yeah, that's how it all began, I feel.
Jonas Christensen 15:41
So, you could have picked investment banking or share trading or any other branch where it's potentially more linked to your degree, but you chose the data community. And you've also said many times that you love the data community. So why was it this thing that you picked to be so passionate about? I don't know if it picked you or you picked it. So, why are you so passionate about this and where did it come from?
Ravit Jain 16:11
Yeah, very interesting question, Jonas. I love learning about finance. I wouldn't say I was never a number guy. I was a number guy and that's one of the reasons I had my background in finance, in investment banking. But then what I really felt was I didn't want to just be into maybe the profit and loss sheets or the balance sheets. Though it's a great job, I wouldn't say that, but I was more of a person where I wanted to be a people's person. I wanted to go out there and talk to people more. I wanted to make sure that I could help in any way where I can have that long term relationship with them. And definitely balance sheets and these things can also make some good long term relationships but I wanted to have a different side to it. When I started with my first job, as I mentioned, it was more on the side where I started realising that data plays a very important role and people want to learn more about it. People want to understand the market very well. And that got me very intrigued in terms of getting into this field and making sure that - how, like, how do I want to structure it? In what ways can I help the community? And to be honest, it did happen, I would say. Though, I chose a path but everything kind of happened all together. When I got into the community, I started helping them with various courses, books. Started with The Ravit Show and you start building a community out there, when you are helping the folks. It's always about more on the side, where you are the Giver. If you are the giver, trust me, it has to come back to you. And then I kind of became the people's person. I love talking to them. Yeah.
Jonas Christensen 17:49
Nice. I like that. ''If you're the giver, it comes back to you''. I like that.
Ravit Jain 17:54
Definitely.
Jonas Christensen 17:55
Now, Ravit, since you are such an expert in this area and you are good at spotting trends, that's been your role and your vocation for a few years now, spotting trends and sort of narrating that information, curating the information, presenting it up to the audience and creating the audience, you have to have a really good finger on the pulse for what's actually happening out there. Because you're creating content, you're publishing books, you're managing conferences and all this stuff. So, I'm interested in getting some insights out of you around the future of data science for our listeners. So, perhaps we start with the question of: What do you think are the most important trends and topics in data today and in the next, say, three years?
Ravit Jain 18:43
It's interesting. This question has been like a sort of debate for many. But what I feel is, you know, I can say there are three trends, which will not diminish for at least next five years or seven years. One is obviously AI plays a very important role. People feel that most of the AI projects kind of fail. But trust me AI is just starting. It's just starting to take off. I've interviewed folks. Folks like Ben Taylor, Kirk Borne. These folks have such interesting insights about AI and how it is just getting started. How things are implementing right now and how things will be automated. I'm not saying that it will replace human in the near future, but at least there will be some interesting things which will be happening. We've seen a lot of things happening in the healthcare system through AI. In the last two years of pandemic, we have literally seen a lot of AI playing a great role. So, AI is something which is very important. In terms of more, you know, getting into data science, I know for a fact that Analytics Engineering is kind of picking up very well. It's more of a role, but when you talk about the trend there, it's around engineering. So, you can also say Data Engineering and Analytics Engineering is kind of the boom in the next three years, which will play a very important role. But Analytics Engineering is something which people are wanting to learn and basically boils down, again, to Analytics, which is always evergreen. Analytics is very important and people know it. It's just that it's named after different roles and stuff. But I feel analytics kind of play a very important role. People love to get into this field. They love to play into the data analytics. There are many sub fields where they want to go and explore their career and they have given lives. So, that's how it will be booming in at least next three to five years. The other part, there are many, I wouldn't say buzzwords, but there are many other fields, which are kind of opening up and are in the early stage, like data mesh or data fabrication. So, these are interesting fields to look out for. You never know what can turn green. So, just stay there and learn more about it. There's MLOps, which is very interesting. It is hot. There are many companies. I have interviewed a lot of folks in MLOps field as well and it's something you should be looking in the near future to learn more about and stay updated, I would say.
Jonas Christensen 21:29
So, there is so much here to stay updated on and keep track of and it's all very technical stuff. There's tools underneath. There is understanding different uses of data and so on. How do you think one can go about that? How do you pick what to work on? Because you can't do it all.
Ravit Jain 21:47
You can't do it all. Yeah, you can't do it all. You just mentioned it very right. These are fields which have massive sub-fields as well. If I talk about AI, there are many sub fields where you can get into and learn about it. So, you know, the best approach I would say for anyone who wants to break into this is first thing just make sure that you are having the passion to get into this field. It is the most important thing because if you want to learn about AI, it's huge. It's never ending. There's so much that you can learn. There's so much that you can implement. There are various courses. There are various videos. There are various, obviously, universities offering courses as well. So, those can be the places where you can start. There are many people who would say that universities want to help, you can just take up the courses. But that completely depends on oneself because I wouldn't recommend someone not visiting the university or someone not taking up a particular pose. I would say, whatever suits you the best. Whatever makes you feel the right way of learning, get into it and do it. But definitely, you can't do it all. So, just pick your right path and just pick your right place, where you want to get into. Talk to the right people who are in the field. I'm not the right person to talk about AI or I'm not the right person to talk about data mesh or data fabrication. You can talk to the experts in the field and learn more about it. Is it just a part of data science in you know? How will be the future of it? They are the experts. So, always reach out. I would say start from obviously understanding your passion but also making sure that the people you are actually talking to, the creators, the experts who are in this field and they will be the right advisors. But I think the most important thing is: Go with your passion.
Jonas Christensen 23:45
Nice. ''Go with your passion''. I like that and I do that myself. So, I can only subscribe to that advice.
Ravit Jain 23:53
Yeah
Jonas Christensen 23:54
Keeps me very busy. But it's a lot more fun than following, say, the money or other things like that, that they can seem shiny and important at the time. Now, Ravit, you're reminding me of a piece of information that I stumbled across when I did some research for this interview and it was a piece of advice from you to people who are wanting to get into the data industry and your advice was for these aspiring data professionals to start networking with others in the industry. Why do you think that is so important and also how should one go about doing that?
Ravit Jain 24:31
Oh, first of all, Jonas, I appreciate your research and I think which is very important to me and very close to me, which is networking. I feel it can get you to places because I myself if you ask me like who was like three years back, I was just a person who was just getting into data science or AI, who was just wanting to learn more about it. Though that's a different story, that you know about things in the field and you know about what's happening but the real insights come from talking and talking to the right people and networking. Like, I mentioned in my previous answer as well, it's more about talking to people, the experts and getting the right insights from them and that can only be done through networking. I started networking with authors, communities, people who are the real creators also people who are creating courses, professors. And that's how I've understood if I am able to talk about even a little, you know, what's happening in the industry today, it's because I network regularly. It's a nonstop process that you need to get into because those insights will help you shape your career. And at the same time, it will also help you in making the right decisions for where you are right now and follow your passion. It is something which is very important. I feel, networking kind of plays a very important role because everyone you talk to has someone who could be of help to you and everyone who talks to you, you could be of help to them. So, it's about you know a guy who knows a guy. So, it's basically just that but it doesn't stop there. It is about more on the side where you can upskill yourself through networking. You can learn more about the whole community. You can get closer, do collaboration opportunities. You can actually collaborate with YouTubers, if you're a YouTuber. You can collaborate with companies. You can collaborate with LinkedIn influencers who are out there and making some amazing strides. So, those are the things which will keep you posted about the happenings in the community and where you're wanting to get into. So, the right questions can make you reach places. It can help you in your career and that can only happen through networking. You need to be out there. You need to attend conferences, events. You need to understand the content that you are interested in and those people who are actually talking about it, engage with them, talk about it. And that will get you definitely a spotlight. It will take a lot of time. I'm not saying that start networking today and you might see results like just in a month or so. It will take some time. But if you are there diligently, the results will definitely show.
Jonas Christensen 27:19
Yeah, and I might share a bit of my own learning with this, Ravit, because I think it's such an important topic. So, a lot of people in data science, including myself, by the way, are typically more introverted types and networking, potentially daunting and even a little bit, in some cases, people think it might be like a fake connection. I think as soon as you change that mindset and go ''I just want to learn about this person'' and connect with them and see what happens, let serendipity take its course, it becomes a lot easier. And networking is so important for opportunities to come up. When you think about how you learn things, it's often from a teacher, not a notebook or textbook. You might do both but if you speak to the teacher straightaway, you can shortcut hours of reading and this is what networking can do as well. I can only subscribe to what Ravit is saying and he's built this global data community of people who network. So, I recommend for all listeners to really check it out. I, myself have signed up to Ravit's Slack channel and it's a lot of stuff that's happening in there. Lots of information being shared. I've noticed that they're not just anybody in there, Ravit. They're some of the leading faces of the industry. So, you've built a community of people who are willing to share but also have some real gusto in their background. Now, you have interviewed and worked with hundreds of experts in the data industry. So, I'm interested in hearing from you. What are the traits that make those leaders stand out from the rest in your opinion?
Ravit Jain 29:02
I feel - First of all, you've made fantastic points here, Jonas, in terms of networking as well. Like, about the whole introvert and extrovert game. About people being - You know, in this field, I've seen a lot of people who are introvert and then once they start opening up, there are opportunities that they land on and there are so many things that kind of bring in. For now, at least I can say, Jonas, you are not an introvert. You are a good extrovert. You have your own podcast. You talk to people, which definitely doesn't make you an introvert, but maybe you're working on it and you're just getting through the line and wanting to learn more and being out there. So, in terms of the leadership, I would say it's on the side that first thing they are not introverts. They are out there to help people. They have the created mindset where they have chosen their niche very well and they're worked on it. They are kind of gaining a lot of knowledge every day into it. They don't call themselves the experts, though if they speak about a certain subject which they are into, it can change the whole ballgame altogether in that field and people can be influenced very well. But to become that influencer or to become that person who can have a great say in a field, you need to work a lot in that field and you need to be constantly updated. You need to make sure that you are choosing your niche very well. You're choosing your audience very well. It doesn't work where a person comes in and says that, ''Okay, I can talk about analytics at a large''. Like, about everything in analytics. There might be places where a person would say that, ''Okay, this is not my thing in analytics but these are my places where I have found my niche and I know a lot of things. I've worked into it'' and that's a simple example of understanding that - Choose your niche very well. Just master in there. Learn everyday and go out there and talk about it confidently and things will change and there's always so much learning. There's always so much of controversy that will also happen. So, you need to be up for that as well. There might be people who would not want to take your opinion at all. They might criticise you but if you have done your homework very well, if you have those right pieces which you can fit in the puzzle and say, ''This is the reason why I say these things kind of work'', I think people kind of like that because you have a certain exposure. You have a certain experience. You are wanting to share and that when you are coming up with a theory which might actually help them in that particular field and that's what leaders do. They are very sure about what they are doing, what they are building. Even if they are coming up with a product and services, they're very confident about it, that there are competitors out there who have a similar product but what kind of makes a difference for them is very important. And they come out very confidently that ''These other reasons, which makes it different'' and which will actually help the customers, the consumers, the audience, to make them feel confident about it and makes their life easy.
Jonas Christensen 32:15
So, what I'm really hearing is a lot of these people are, what I would call, servant leaders. So, they're providing a service and from that they are really building up implicit leadership because they're getting the tribe together and bringing them along on the road to wherever the destination is that we're going, which is also what I think you're doing, Ravit, a great job at, with giving us all this content in the community. Now, a phrase that I see a lot when I see your content is ''Growing together is the motto''. That is your motto, Ravit. What does that sentence mean to you?
Ravit Jain 32:50
It is very close to me because what I feel is a community or a leader or a person in a field, not only in this data science or AI but in any field, if you don't have a mindset which is growing together, if you don't have that motto in your mind that, ''I have an audience and I want them to grow'' - I will just give you a small example of a teacher. Ateacher comes in the first grade and has a mindset where a teacher says that ''All my forks by end of the year, all my students need to go to grade two'' and that is about growing. So, if they don't have that mindset, they will never grow. So, that is where I actually take the whole quote, which is, like, ''Growing together as the motto''. If I am growing in this field, I definitely want the people who are following The Ravit Show, who are in the community to make sure that they upskill themselves in every way if they are following a little content that I am trying to provide to them in any way. Even if they visit my show and, you know, I have invested like 45 minutes of their time on a live show, I want them - And that's one of the reasons why my show is live as well, where they can actually ask questions. And I do put it as a podcast, where they can ask questions and I can easily answer them. So, it's more on the side where I can get community closer to the experts and ask questions and get the real insights and that kind of helps them to grow. In turn, also helps me to grow because I'm building an audience which is helping me and making me more responsible on the lines where I can grow more in this space. I can say that ''Okay, there are people who trust me''. Who feel that ''Okay, Ravit, does share some credible stuff we can follow''. So, they are growing. So, that's how close the motors to me. Growing together is the motto. Yeah.
Jonas Christensen 34:48
Nice and I do think the way you do it with your show is actually a little bit unique and quite valuable. I've watched a few of them. I haven't watched all of them because there's quite a lot and just seeing the way that the audience interact throughout the show is quite interesting. And I think so valuable to that individual to be able to ask a contextually based question in the moment and interact with someone that they might not follow or read their books, or what have you, for quite a long time. And when you've read someone's book and you can then ask contextual questions around that content, really it forms a very deep conversation very quickly. And I think a lot of the audience you do have on your show are also published authors. I think that's pretty common. Is that fair to say?
Ravit Jain 35:32
There are many authors. I keep it a mix, like where I have at least or like more than 40 companies I've worked with already in last one and a half year, and there have been many CEOs, CTOs as well, who have come and shared their journey. They have shared knowledge about their particular field and also talked about their products that they have build. And so yeah, a mixed crowd, I would say. Though, authors, - At least in 2022 what I'm planning is to have a lot of professors from Harvard, Stanford on the show and share the insights with the audience. So, just planning on those lines. Yeah.
Jonas Christensen 36:12
Yeah, I'd say audience check out Ravit's show is definitely worth your time. Now, Ravit, I have two questions left for you today. The first one is one I always ask of guests on Leaders of Analytics.
Ravit Jain 36:26
Yeah.
Jonas Christensen 36:26
And I call it ''Pay it forward''. The question is: Who would you like to see as the next guest of Leaders of analytics and why?
Ravit Jain 36:35
Okay. Very interesting. In field of analytics, I know, David Mariani, who's the CEO and co-founder at AtScale. You should definitely have him on the show to learn more about how they are bridging the gap between AI and BI through the semantic layer. It will be something which you would love to learn more about and he talks a lot around AI, BI and analytics all together. So, he could be one person. The second would be - Actually I have many names in this field. But okay, I will stick to John Thompson. He is the author of ''Building Analytics Teams''. He talks a lot around analytics and definitely will be a great participant for the show. Yeah.
Jonas Christensen 37:21
Brilliant. I personally I'm building an analytics team and I'm trying to put more AI into my BI at the moment. Perfect for me personally, but of course, also for the listeners. Thank you for those recommendations. Now, Ravit, where can people find more about you and get a hold of your content?
Ravit Jain 37:40
Okay. There are many places. I would say LinkedIn is number one. I have my own page, The Ravit Show, where I share content. I share about the upcoming events. You can find me on Slack, Telegram, Instagram. Yeah, I think I've covered the ground. But LinkedIn is my first place. Feel free to reach out to me. Just put a message in there and I'd be happy to respond to you guys. Yeah.
Jonas Christensen 38:06
Yeah, definitely do it, audience, I highly recommend that.
Ravit Jain 38:11
Thank you,
Jonas Christensen 38:12
Ravit Jain, thank you so much for being on Leaders of Analytics today. It has been such a pleasure to listen to your story and your insights and get some real, valuable tips on how to actually network with people and peers in the industry. So, we will be very grateful for the content that we've created today. But also continue to be very grateful for the content that you put out into the field and through your channels. So, thank you so much for serving our community so well.
Ravit Jain 38:42
Thank you very much for having me, Jonas. You're doing a fantastic job for the leaders out there, for all the analytics community and I know how much it takes to build a podcast because I really appreciate the work that you are doing. Because I am in that same place. I know going out doing an outreach, preparing questions, asking them,executing, getting into different fields, asking various questions, researching about the guest, it takes a lot. So, I would definitely urge the audience to actually put it out there, put the word out as much as possible for Jonas. And thank you very much for having me, again.
