Melody Meckfessel and Deepti Srivastava: Visualization, Productivity, Democratization | Turn the Lens #10

>> So I'll just count it down and then we will go. Three, two. Hey, welcome back, everybody. Jeff Frick here from, "Turn the Lens," in the home studio today and I'm really excited to have two people who I've known for a long time. And now they're doing a new startup, they left the big mothership and now are doing some really exciting stuff. And one of the great things is to watch people's careers progression over time. And these are a couple of people that I've watched for. I think, I looked it's 2014 since we first met. Deepti, it's a long time, like legitimate time. So we're really happy to welcome, Melody Meckfessel. She is the co-founder and CEO of Observable. Melody, great to see you.  >> Great to see you, thanks for having me.

>> Absolutely. And, Deepti Srivastava, she is the head of product at Observable. Great to see you as well, Deepti.

>> Great to see you as always, Jeff, thanks for having us.

>> Yeah, so let's jump into it. So observable is all about visualization. We hear about visualization all the time but I'd never heard visualization in the context of helping developers make better software. That's a very different twist from what you hear kind of at your typical big data types of shows. So Melody, why don't we jump in with you? What was kind of the vision? What got you here? Why did you leave the mothership to come and throw yourself into a crazy startup world?

>> Yeah, I've been on the development side my whole career writing software. And I got really interested about five years ago in studying what makes developers productive. So most of the software in the world is written by humans and it will be for the foreseeable future. How do we help empower them, remove the toil? I got really excited about DevOps and how it enables developers. But one thing that was always missing for me is developers we have to write the code. We also have to understand the data that we're interacting with a lot of the time. And as we know data complexity it's not going away anytime soon and everyone's trying to figure out how to manage it. So it's sort of this combination of how do we help developers gain better insights into the code that they're writing?

It's tough to develop. You got to keep up with all the tools that are out there. More developers looked at the latest kind of reports a 100 million developers by 2025, increasing which means that we also need to find ways to collaborate more effectively as developers in the community. And a lot of that can lead to just increasing complexity that we have to manage.

>> Sorry?

>> No, just so like, how do you navigate that? And visualization is, I'm going to make a big claim big bet. Visualization is one of the ways to do that. It is a tool that we as developers can use, taps into our visual system. It enables us to explore and navigate our data and code, to understand our code structures, to understand our code hierarchies and to be able to model relationships. I mean, you talk about big tech in the Valley. There's a lot of hairy dependencies and infrastructure challenges that people have to navigate. Visualization helps us have better insight into that.

>> Yeah.

>> So for me, it was like this, aha, okay. We talk about all these tools, but like, how do we help us have greater understanding to make better decisions?

>> Yeah, I pulled one of your slides from one of the other things that I saw earlier today, more developers plus more collaboration, unfortunately, is more complexity, right? Which...

>> It is.

>> Is also the speed, but we've come to this place where there's so many systems that have all these interdependencies that it's not simple, it is complex. And as you said, it's still people and humans writing these things with all the complexity that that entails.

>> Yeah.

>> Deepti, you've been rocketing up the product line. And again, I could pull up your keynote which I might in the post. So excited to first meet you at that top coder open seat in front of a bunch of high school girls telling them to get into tech. And next thing I know you're rolling out on the Google cloud stage. So again, really fun to watch that progression. I think I was sitting in the third row. I don't know if you heard me cheering and throwing popcorn at you, but that was definitely me. So talk about your point of view on visualization and how this is a real game changer?

>> Yeah, first of all, yes. Thank you for that journey recap. It's been awhile, but yeah. I mean, as you know, like I have two passions in life. One of them is, tech as an enabler for good. And the other one is gender equity in the workplace. And Observable gives me the opportunity to really do both together at the same time, at the same place which is super exciting and we'll get to it. But in terms of data visualization. So I think the interesting thing is my entire career has been in data and around data infrastructure. Like, how do you keep data? How do you make data available? How do you secure data? How do you transfer data? How do you transform data? And the next logical step to that is how do you make any sense of that data, right? And most of the world is coming at it from analysis perspective.

But ultimately, you have to communicate all of that to people, to humans, as Melody said, right? And humans are great in understanding pictures. And so when you look at that sort of journey of data and data complexity, complexity is not going to go away. So how do we make that complexity actually work for us? And how do we make humans empower themselves to make both decisions using data? Like, everybody talks about data driven decisions but what does that really mean, right? There's so much data. How do you actually make sense of it? How do you get insights out of it? And I think visualization was the next logical step. And for me, the aha moment was sort of when I started to look at coronavirus and last year has been just intense for the whole world but there was basically both elections, coronavirus all this kind of stuff.

This is essentially a bunch of data at us. And how do you communicate that data, right? And we've all learned that understanding all of these complexities around exponential growth, right? Which is another way that you model algorithms for developers, for example is something that is applicable in real world. When we talked about the (indistinct) exponential growth, right? But then showing it in terms of pictures it means everybody gets it. You don't have to be an expert in understanding what that is. And so our journey at Observable is really about breaking down silos, right? That exists between the different parts of an enterprise or different job functions, right? To actually collaborate, work together to make decisions faster with all the data that they have. And visualization is really the only way to do that effectively in enterprises. And so that I think is our truly a game changer for us and for the world.

>> Right. So the challenge I just want to throw 'cause you guys are the experts is these things are so complicated. Again, I steal one of Melody's slides from earlier deck and this comes up a lot in terms of kind of like explainable AI and the complexity in the software that's there. This got all these interdependencies and the data sets are so big. So what are the right applications for visualization to take such a large data set of complicated interrelationships to actually put them in a form that I can look at them and see something?

>> So let me speak to that. And I know, Melody has a lot more than she can add to it. But you talk about my product journey, right? Essentially, my passion is to bring game changing products to the market that help people make better creative use of their time rather than managing technology, right? And with Observable, which is essentially a cloud-based product, highly available, always there. The interesting part about this is not, not only the large datasets, but actually most people are making decisions based on manageable data sets but they're just sort of fragmented, right? And so like, if you think about an enterprise there are so many people who are not database experts that are living and breathing database all day. It's like remarkable, right? Product managers do that, business analysts do that, financial analysts do that.

Researchers do that, all of these people, what are they doing? Looking at charts and graphs, right? They're hooking it into all these sort of what would we call competitor products, but we don't think of them as competitors, right? Like all these charting and like visualization libraries.

>> Jeff: Right.

>> And all they're doing is trying to make decisions better. And I think that the next logical step is like, okay, you have all these ways of doing this but what happens when those data sets and those modeling and transformation doesn't fit? Where do you go then? And I think that's where Observable comes in.

>> Yeah, interesting, Melody?

>> Yeah, so I think one of the principles is that Observable offers an environment which is always running, it's compiling the code that you're interacting with real time. So this kind of sweet spot of everyone getting feedback on what you're doing to the data and then the logic in the code, JavaScript, which you're applying to it. And then the level of interactivity that you can bring to a database, we believe is really powerful. So, what typically happens? I tell the story over and over again. You're in an executive leadership role or you're a business organization owner, or you're a developer or a team is trying to make a decision. If you need some level of approval you create this really cool database and you turn it into an image and you put it in a doc or a slide or something.

And everyone who's now looking at that is abstracted away from the logic and the analysis that went into the creation of that database. So what we're doing at Observable is we're bringing interactivity to be able to (mumbles), use sliders and components to analyze the data. To be able to explore the visualization in a way that our intent is that folks are communicating they're asking questions, irrespective of their role, which Deepti mentioned. And they're able to get to a better outcome in terms of interacting with that data. So we have the option for people to connect directly to their production data sources. We have the ability to attach files. If you think about the spreadsheet case. I'm working with data in a spreadsheet and I want to get a great visualization to present the outcome of the analysis. You can use a CSV, you can use all sorts of file formats to make it really easy and lightweight. Whether you're a business analyst or a data scientist to then interact in that notebook to generate that outcome.

>> Great, you had a line in one of the videos I saw getting ready for today. When you talked about kind of comparing visualizations to basically my interpretation was kind of C Prompt, kind of old school ways to interact with a computer was a C Prompt Text, command system before that of course, punch cards and other things, and really kind of equating our visualizations to use that, to show the data versus, again, kind of the traditional way of interacting with text-based systems. But is there some types of analysis that just lend themselves to a more effective, a more easy and more, everyone's always looking for the early wins, right? And the best ways to show successes. Is there some stuff that just works better that people should try with first?

>> First of all, I think one of our missions is to say that all data can be applied to, or visualization can be applied to all data. So I think there aren't any like, tabular data goes into like a certain format like line chart and like non tabular data goes into like a sunburst or something, right?

>> Jeff: Right, right.

>> The point is like any data can be visualized to make it more effective to communicate. And then there is the philosophy that, you talk to Mike or some of the other database experts. Like there is a philosophy on which type of charting or visualization lends itself better to what type of data, right? Like, network graphs versus simple line charts. But I think, again, what we're trying to do is open everybody's eyes around that and say, just try and put your data, and the transformations you do, you can then apply them to simple charts and graphs and line charts and bar charts all the way to like complex sunbursts and network grants, right? We really don't want people to have this belief that there's a ceiling to how much you can code and how much you can communicate with the data. And so to give you an example if you look at other visualization products in the market, a lot of them work with databases and tabular data, as an example.

They all sort of great for what they're meant to do, right? If you want to hook up sort of a database from a table to like a tabular view and create a few line charts and bar charts, that's great. But as soon as you start to mix that data like if you have structured data and you want to mix an unstructured data to it, how do you visualize that? Like, oh my gosh. Like most products of that nature, like hit and limit, right? They're super rigid if you are going beyond what they offer to me, right? And with Observable, because ultimately (indistinct) it's just code, right? It's JavaScript, it's in the browser. So it's available to you anytime. And because Observable, the infrastructure is taught basics and available to you at all times, right? It's highly available. You can actually build any type of chart you want within the system, within our notebooks, basically which is just a conduit, a holder for that code.

And you can express what you want through them, right? You can explore as well as express. So you can do video analysis and exploration within that notebook. You can write pros to explain what you were doing within that notebook. And you can produce the final presentation of the final cool artifact that you put together within that notebook. Right?

>> Right.

>> So the walls and boundaries sort of get broken away and they kind of melt away and you're doing explore, discuss and analyze and present all in one place, which is super powerful.

>> I love it, I love it. I mean, the demo that you've got, again, on one of the, I was cruising around checking out all your stuff where they take, I think it's an earthquake database? And they very quickly build this little model of the earth and then put the water in it and then tilt the earth and pull that public data. It just makes me like, wow, what type of opportunities are there? I was just talking to one of my kids with all these massive publicly available databases that aren't necessarily easy to get to or necessarily easy to figure out what to do with when there's this whole open data initiatives that stuff just seems ripe for a whole bunch of kind of unexplored applications and unexplored, kind of value unlocking in that space.

>> Yeah, it's a great point. To go back to your questions of types of data. We're seeing diversity across all domains. So whether it's biological data or even architecture we're seeing data is being taught early on in school programs, starting from like high school through universities but across a whole range of data sets. And one thing that I know Deepti and I are both excited about is just that community is the center of what's happening in Observable. So I know you and I have talked in the past about the power of open source and open source is really, it's in the DNA of Observable. So you find a live functioning database and you can fork it and you can add your own data and you can start to make it your own.

So you're not starting from scratch and then you can share it and it's out there in the world and someone else can take your version and start to change it. And so really just internalizing that a huge portion of the world's software is either, using open source or built upon it. And this way of developers interacting with each other, where we're teaching and learning from each other constantly is really ingrained in the early kind of community activity we're seeing in Observable. And think about being like a data scientist in the retail space or a developer in the financial services space. And you have a job that you need to get done. And where do you go to find some data visit examples? Of course you can search, but this idea of community to share examples that could be very specific or they could be very general in terms of the type of visual forms that you can use.

That's something that I think we're both really excited about. So if you think about what GitHub has done for software development in terms of bringing people together this idea that diverse backgrounds, diverse domains diverse interest in vertical markets from a student to a data scientist professor, data journalist, coming together around being able to communicate insights from data is, I think we're really inspired by that. And it is a decades long journey to try and help increase data literacy in the world.

>> Right.

>> Oh, yeah.

>> Starting with something so you can do a save as is such a great start, right? That they have those books already out there. So I don't have to start from zero. I mean, that is a huge benefit. And the other thing that was interesting going through that example with the earthquakes and the map, is the demo person really reinforced the fact that it's the data kind of prep and data understanding and really thinking through, how do you want to represent the data and what should it be a bigger thing? Should it move? To kind of this concept where a lot of people ain't discount the prep work before the quote unquote real work begins as kind of a pain in the ass and drudgery. When in fact one might argue in most things that are worthwhile, most of the work happens before game day, and that's really where the winners and the losers are determined before you actually hit, Run.

>> Yeah, I think, sorry, go ahead.

>> I was just going to make one, like, so care about this point. Trust in data. So wherever you are, we really need to be thinking about that as humans as participants in the workplace in the world. And when you interact with something in Observable, it is transparent. You can see the code, you can see the data, you can find out who published it. That idea of transparency to mitigate risk but also to build trust in what the data visualization is expressing is so important. And I think that's one of the principles that when we think about how the product is going to evolve is very, it's like, it's at the top of our list for Observable.

>> Deepti?

>> Yeah, I was just basically, yeah. The same thing, right? Like we've, that's why we work well together. We both been like, excited about this journey, right? Like we both spent a bunch of time in enterprise, right? And enterprise data is the crown jewels. Like you can't touch it because you don't want to mess it up and you don't want anybody to get in there because then you lose the sort of trust around that data. And so with this aspect of transparency of your data and of the transformations that are happening on the data, right? So there's code that's being applied to the data to transform it. And all of that is visible to you, even as a decision maker even if you're not like, if you're an executive and you don't really you aren't in there like munching the code everyday. The fact that this notebook that you look at that has the analysis and the data inside it, right? That you can open up and see just can give you a level of confidence like that generally doesn't exist in one place, right? Because you've taken the static image and put it in a powerful region shown it to your (indistinct) and they cannot trace back, like what happened to it, right?

>> Jeff: Right.

>> A lot of iterations to get to that data. And it's just so simple. You open up a cell and you see the data there.

>> Right.

>> The first time I saw it, I was mind blown to be honest with you. And I also want to touch upon another thing which is related, which is what you were saying, right? That most of the work isn't the analysis, right? The final product is hours upon hours upon hours of multiple people's time, like product managers business analysts, financial analysts, right? Decision maker, the director and all that kind of stuff. And to be able to do that and do it in one place so you don't have to keep stringing things together all the time. Like as someone who has done that, it's just, it's a game changer to be able to do all of that in one place, right? When we have business discussions for ourselves we doubtful with our product I'm always in Observable. And we work on it together, right? We look at sort of our metrics and our targets and our growth and all those kinds of things together in our own products.

And we use that to make business decisions and product decisions every day. That's just how it is, right? And I think that's where the world is going.

>> It's such a fundamental concept of the big data meme, right? Which is, we used to take a sample of old data to try to figure out what happened versus taking all of the data now to try to decide what to do. And it's so different. And in the know and to your point it is happy wherever you report anymore. Sure,. I'll take the summary report but I want to be able to double click to the source and I might want to re configure or you measured variable A, I actually more curious about variable B, which you chose not to run. So I think it's such a big, it's such a big deal to your point because ultimately it's how you present the numbers, is where the value comes but it begs a different question, do you have to teach kind of best practices in visualization? I mean, is things like literally like colors and it's a different type of art necessarily that if I'm just, doing a C prompt commands or JavaScript commands to run analytics, how does that play into this space?

>> So I think I have a perspective and I'm sure Melody has hers, but this was the first question I heard, what was it? We're basically, are we a platform just for experts? Or are we a platform for everyone, right? And the answer very strongly is that we're a platform for everyone, which means we can bring like our expertise of data visualization to the things we offer, right? With the sort of, as you talked about tutorials or with the community built notebooks that we have, right? That all sort of visualize data like differently and show best practices to some extent, right? It's not just about us, it's about our community. And that community is both learning together and building together to showcase how you can visualize different types of data in the world. That example around the public data sets for you for example, right? We also had a set of folks that are part of the community both Observable and external Observable that built these California sort of, air quality smoke maps, if you remember...

>> We'll spend away too much quality time with those things over the last couple of years.

>> And part of the journey for the folks that were doing this was actually exploring how can you visualize this data in a way that, people who are consuming it and they don't have to be like experts on you're time they're just like regular people like me and you that need to figure out if we could go outside or not how can they interpret it faster? Or the best of our ability, right? And so there's a whole series of notebooks that the folks created and live streamed to show that there are these different ways of building this dataset, like coloring it and all that stuff so that it can be accessible to a lot of people. So the answer in my mind is the power of the platform and the products is that it allows different people who don't come from a sort of academic background where there is a certain set of colors and things to do, right? It becomes a tangible thing that I use in my life to get answers.

I don't care what the, like I'm being facetious but like when you're trying to do a job, whether it's for yourself, for your company or for the greater good you just want to like do something and see what happens, right? And see how it's interpreted and make like, make changes on it. And the point that Melody was making about interactivity and transparency is the thing that I think makes Observable so powerful that you can see the changes, you can like interact with somebody else so that they can come and bring their perspective, 'cause you can collaborate on the same seldom the same notebooks and you can evolve them, because we have sort of a code structure. We like fork notebooks, right? So then examples exist for you to customize without a seal.

>> Right. Melody?

>> One of my dreams is that both from a, opening up the space, the approachability and accessibility of it is that any human, right? Can continue on their journey and continue to evolve and expand their expertise in database in data exploration and in the visualization of it. And we hear, right? That when you try and use other tools that are maybe out of the box, you kind of hit this wall. And so it really does come back to, what many of the points that Deepti mentioned around the product which is when you are speaking code when you are able to interact in this way and tinker quickly, right? Like you're not waiting minutes and minutes to find out the results that really speeds up the learning process.

So it's kind of learning is embedded and how the product functions in many ways. And we believe strongly in investing in the power of the community to teach and to help folks learn from each other. So a lot of what we're going to do is, like we're the connectors, there are professors and teachers that are sharing what they've created on Observable to teach other students in database. And they are so generous, right? The community is so generous to share what they're creating. And I think that, that power of the connection in the community, both the creation and explicit teaching about these are good principles and database. And here's some examples that show that we believe will bring, yeah, will just bring so much approachability and access to folks in the world to learn database.

>> Right, that's great. I mean, the democratization to the access to the tools and the ability to operate the tools, right? That's where innovation lives. Give more people more power and more data and let them do more things. So clearly that's a winning formula. I want to shift gears a little bit and say, Melody, why did you decide to build a company culture in the middle of the first pandemic in a 100 years? I mean, Oh my goodness, you started like middle of 2019, right? If I have my dates right. And then Kaboom. So again, a really nice piece that you did for your internal, mainly internal audience, but a bunch of really specific, intentional, thoughtful activities and behaviors that you've put in place to try to build a culture. When you were at Google, you talked a lot about culture. We talked about culture when we were at Moscone. I wonder if you could share some thoughts on, how are you really being thoughtful? Where are you going for guidance and help so that you can be so deliberate and so thoughtful in taking the steps to build not only a good culture for your company, but also a good culture with the bonus burden of we can't get together?

>> Thanks for asking that. And thank you for the kind words. My perspective has always been the technology it's here to help us to enable us to empower us. And we've already talked about what we believe the power of databases to do that. My dream, my goal being in technology is to help as many people as possible come into technology with as diverse backgrounds as possible. And we really have this lens on database as a way to bring people together to communicate and collaborate. And for me, I'm so grateful. I mean, it was a very challenging, new challenges, lots of growth opportunities, building a company in a pandemic. But I have to say, I believe strongly in taking time to have the company represent what you want your community to represent.

And the second part of that is that the values that you have internally I believe have to match the values you want in your platform. And so the opportunity to build Observable both the company and the community the actions that we want to take in the world have to match. And so I was really inspired to do this for those reasons that I want to change the makeup of who's in technology in the world. And I want people to be able to see it because all the research, I mean we've talked about this before. You can't be what you can't see.

>> Right.

>> And so, I believe that so strongly, I think we're building a culture that has openness, flexibility, compassion for each other during this time. And I think really just bringing some empathy to every aspect of our lives. We're all having this conversation right now from our homes. And we don't, I don't take anything for granted in terms of the company culture that we're building in terms of openness. 50% of our leadership team is female, it's women, women in technology, you got to be what you can see. And I think the diversity that we're developing in the company culture is, I'm really proud of that. And I'm really grateful to work with everyone at Observable.

>> But everybody says that then the rubber hits the road. And what impress me in that talk that you gave is you were willing and it makes sense. You're a data-centric individual to say, the data says that it's good to take, to have people work a four day week and not a five day week for a whole bunch of reasons and we're going to do that. And then you had a bunch of, you listed a whole bunch of little things that you guys do. You get birthday sing-alongs and, you just went on and on and on. And my point is, we're laughing, but it's very serious is that it's one thing to say you want to put a culture in, and it's one thing to say you want the culture to reflect your own values in the company. It's a whole different thing to actually think through. What are the physical behaviors? What are the things we put on the calendar? What are the things that we're going to commit time to?

Which means you're taking time away from coding or taking time away from customers, or taking time away from other things, because we think it's important. And ultimately your priorities are demonstrated by where you spend your most valuable resource, which is your time. So again, if you could share some of the fun things you do, maybe some of the more serious things to have a set of behaviors and kind of cultural norms to put those in place so that you can, you talked in one of your things about, talking to your daughter about what happened at work today, or your child that you can say, Hey, and she could say, mom I'm proud. That's a really cool thing, but ultimately you got to put stuff on the calendar you got to make decisions and you got to make commitments.

>> I know. So, yes. Thank you for saying that. You got to do it, you got to do it, right? So a lot of people talk about it. You have to have your actions demonstrate and you have to be consistent in that. So in 2020, we onboarded 16 I think, 17 people in our full remote environment. We had to change our approach. We do a lot of pairing so that new people coming on board can work with other folks. But we also had to adapt along the way. We have no meeting Wednesday so that people can have heads down time.

>> I love that, by the way, that's the best thing. That is awesome. No meeting Wednesday. I love that.

>> It's great. We do social events. We have a full company meeting every week but then we also have what we call a standup where we do just recognition and kudos for each other. And then icebreakers, which, I mean we're all getting to know each other but they're fun events that we do. And we do mentoring sessions. We do co-teaching so people will lead study groups. Every two weeks, we have a culture talk where we dig on something that's important to the company culture, blameless culture, communication. We're in the middle of Black History Month. So we believe strongly. I believe strongly that part of the company should be toward making the world a better place.

So we're celebrating Black History Month with a database contest and giving out prizes. And then we're going to have a meetup later. We're going to do the same thing for Women's History Month a little bit different activities next month. And we also offer time off for people to do pro bono work for volunteer organizations. We are also working to help some non-profits with their database and letting, giving away our paid product for free so that they can get value out of that. And hopefully accelerate whatever policy change or data exploration that they're trying to do with that. But I think it just comes back to like do it.

>> Jeff: Right, right.

>> I don't want to talk about it anymore. I want more leaders and more companies to take action. And there are many ways big and small that they can do that but your values have to be the same internally with what you're trying to do in your platform. For us, it's teaching, which we just talked about. It's empathy and it's creativity. Bringing creative perspectives. And it's so central to like how you think about data and data visualization. So, I mean, I could talk your ear off, but yeah those are some of the things that we've been doing.

>> No, that's good 'cause it's behaviors and action to some of which define culture, right? It's not talking about them, I mean, talking about it's part of it, but that's not where it's at. And Deepti, I'd love to get your kind of point of view. I mean, you were at Oracle before Google and then Google is here. You had a couple of big companies. The ability for you to impact culture directly in the company was not very big, except when you rolled out on stage at the Keynote, that was pretty cool. Yeah. You found other ways, right? (indistinct chattering) But you got to, you're on the board at PBWC. So, you've found other avenues maybe outside of trying to define the culture but now you're at a smaller, a smaller organization. So what gets you excited about the opportunity to have a little bit more direct impact on the company culture?

>> Yeah. Thank you again for saying that. Now, every time you talk about it, then I'm like, Oh, wow. And that has been quite the journey through tech because to your point, I think you've covered it, right? Basically, you just hear Melody speak, like, why wouldn't you want to be part of this? Right? Like that's my thing, is like, it has been a journey, right? I talked about at the beginning sort of my passion for gender equity or just equity in the workplace, to be honest. And technology as an enabler for good. And that Observable miraculously has given me this opportunity to do both at the same time at the same place, right? So I've always wanted, I happened to be sort of, the start of the journey was that I was a developer, right?

A systems developer. Like I was an infrastructure, which is generally known to be like very few women. From a very early part of my career I noticed the difference, right? Like I noticed first sort of, around me and then viscerally. And then I really sort of saw it. Like I saw the glass ceilings, I saw the spikes I saw the sort of rough edges. So one would say I've learned a lot at a very early part of the career journey. So I knew what not to do. And to your point, I've been in very large organizations. So it was really hard to shift culture 'cause honestly culture comes from the top. You have to emulate and believe what you want everybody else to do, right? And other places have a certain type of company culture because they have certain types of leaders, right?

And when I started talking to Melody, initially, well first when I met Melody, the ideas I had were sort of verbalized by her she would talk about culture as a thing that you do, right? And I had always felt that it's something I wanted to do. That's part of my work in PBWC is how do you impact organizations to have better culture? But then I saw her doing it in her organization at Google. And then, when I started talking to her the opportunity to be part of this small team at a very early stage, meant that I could with her as a partner, along with the other leaders, in the team to really, to really emulate, to really intentionally build this culture from the ground up. 'Cause I really truly believed that if you tried you could build a positive nurturing and sort of creative culture that is also sort of a winner in the market, right?

Like you can build a company that can be both sort of really good at what they do but also with a really empathetic and creative sort of outlook, right? Positive outlook. You don't have to do what normally is known in Silicon Valley as a tech company, right? You don't have to have that sort of negative culture. You could actually lead with a positive one. And to be part of it, I joined Observable in May of last year, if you know, like that was the time that a lot of really crazy stuff was happening in the world.

>> Jeff: Right.

>> And to your point to leave the mothership when I joined, I was like, what's going on, basically? How do you onboard into a new team and new people like through the Zoom screen. And honestly, the empathy, like every day that I saw my friends and other people like go through this in their companies every day, I literally would say in the gratitude stand up, like everyday, I would say I'm so thankful to be here. And I meant it because we were being human first, right? We were, Melody and then all of us as a result like the leadership team was making space for each other to be, to feel, and also to do work, right? You as leaders have to provide the focus so that people feel both protected and heard but also able to channel their creativity at work.

Right? 'Cause you have to have that balance of letting people be who they are and also encouraging them to, bring in their positive, productive side. And that's what everything Melody has said. We actually do every day, we practice it. And as a leadership team, we're intentional, right? So when we see other folks down or sort of, it's just really hard. So as we see people going through their sort of ups and downs, we actually intentionally talk about it and try to like boost people up or think of other team events or things to do to change, impact people and change their feelings to be more positive so that they can, 'cause we all, this has been a long haul thing. We all need each other, we all need support. We're not automatons that come to work. And then, the Zoom screenshots and then we're suddenly like human beings, like, some of us have kids, our kids join like our Zoom meetings from time to time and it's okay, right?

>> Right.

>> It's okay. And I think that level of it's okay to be you is powerful 'cause there's a 10% task in my head that sort of goes away where I don't have to worry about, Oh, I was too strong in the way I said it even though I look like this, right? Like, or I was to, sort of, I wasn't corporate enough. Like we aim for being human and making sort of doing work, good work, right? Like that's our aim to do good work to enable people, to enable our community. And anything that we can do to ourselves to help each other is what we, what we think is the right way to build a company from the ground up.

>> Yeah, that's great. I mean, I've been fortunate to do. I've been doing a ton of interviews on leadership when COVID really hit. Living through crisis and the whole theme of whole human and human first and you hire a person because they bring an experience that you hope they can apply to your problem, right? And in the classic cases, you throw them into the HR book and you hope they come out the same on the other side as everybody else, which is such a fail. I mean, it's such a wrong thing. So the whole human and the other word, you take around out of my notebook is intentional. Darren Murph from GitLab who runs their remote work before remote work was cool and they're open source. So all their best practices are published, he talks about, really intentional communications and really intentional in terms of what types of communications go on and what channels?

Or what's the expected return and how do you support self-service? And just both of you have said it directly and indirectly as you need to be intentional and you need to be prescriptive and you need to get out ahead of this thing and not just kind of hope that it happens. If we say all the right things and think the right things. Well, this has been really great to catch up. I know we're coming up against the end of the time but I wonder if you want to share kind of some closing thoughts, both on, kind of the opportunity that you see with visualization especially on the software development side 'cause nobody's talking about that, Melody. I've never heard anyone say that except for you. And then as we know, the vaccines are starting to, the vaccines are starting to roll, which is good. My in-laws got their second one, I think today. So that's good. As you look forward in 2021 what are you excited about?

>> Well, I think we've, for Observable and for data visualization. I think we're really just getting out of the gates and I'm super excited to see where we can take it this year because I think there's a confluence sort of people really understanding that they need visualization in order to communicate and make decisions faster. And the fact that, collaboration and interactivity are just so crucial to getting your work done now because especially in this remote environment. So I think those key tenants that Observable offers between collaboration and interactivity and faster decision making through data transparency are just things that the world has realized they need. Right? And so I think we're really at the crux of the moment where, we just want more people to really get their hands on the tools or the products so that they can like, really accelerate their own data and data insights journey.

And I'm very excited about that. And of course doing it with Melody and our leadership team with this culture is just, I'm actually excited about this, even though like we're been in the pandemic and I'm onboarding a pandemic and all that stuff like in a world of just strive like it's actually been super exciting and empowering if you can believe that, I'm not just saying it. It's been really cool to be part of something that is going, I know is going to be a game changer for the rest of the world, right? The technology and everything around community that we're during now. And my hope for 2021 is that I can see everybody in person. 'Cause I don't even know how tall people are. Like, Mike is really tall and Melody is like my height. And so, I just really want to get back into that. I'm very much a hugger and like a physical person, right? Like body language is my thing. So I can't wait to like have, I can't wait for meetings. In person meetings. I can't believe I'm saying that.

>> They're coming, they're coming. Maybe by school year, I think. Melody?

>> 2021 for us, I'm excited about many different things. The first one that I want to talk about is just the product and engineering and design work that we're doing to open up creating database to diverse skill sets. So get ready for a lot of features to improve collaboration to bring help into the database creation experience to bring insights and just ease to create database. Just like doing development in the industry right now is difficult. It's difficult to do this particular piece of development and we want to make both easier. The second thing that I would highlight is that, this is such an opportunity for the developer community, some 56, and million developers in the world to gain more insight into their coding practices into the systems that they're building to use visualization to make better decisions.

From, should I use this algorithm or this algorithm it turns out you can visualize both and make a better decision coming out of that. And then finally, and last but not least the community investment and engagement that we're making from students to teachers, developers, data scientists that there's this joule not only in the creative process at Observable but there's this power in people coming together to do this work. And I don't know if you're into music or not. I see the Bob Marley, I think it's Bob Marley in the background.

>> It is Bob Marley, yeah.

>> Okay. This idea of riffing and collaborating and creating together that whole process it's fun. There's joy in it. And we really want to.. (laughs)

>> Jeff: I was waiting for the cue, thank you.

>> Oh my gosh, it's joy and we all need that. When we're doing our work, but also just in our lives and how we connect with each other. And so I'm very excited about what we're going to do in 2021 with the community in partnership with them. So lots of good things to look forward to. And I'm very grateful to work with Deepti and every other member of the Observable team.

>> That's why I want to introduce you to Jennifer Dahlke. 'Cause she's got the same line. If it's not fun, I don't want to do it. That's her version of what you just said.

>> Done.

>> Very exciting times. And we'll soon be done with this. With the madness of staying home all the time. But you guys have still been moving the ball forward and it's exciting to see and maybe, we'll get beyond punch cards and, I still laugh that we have QWERTY keyboards that are specifically designed to slow us down. I still can't figure out that kind of part of the whole human computer interaction but great to catch up, congratulations for your success and really enjoyed, again you've got a lot of great content out there. So, for people that want to learn about Observable there's a lot of terrific stuff in terms of what you can do with it but even more important who the people are. And the feeling of the people and the culture of the people really comes through in those videos. So, good for you. And thanks for spending a few minutes with me today.

>> Thank you.

>> Thank you so much, Jeff.

>> All right, she's Melody, she's Deepti. I'm Jeff, you're watching, "Turn the Lens," with Jeff Frick. Thanks for watching, I'll see you next time. Very good. That's a wrap.

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