This is a special guest interview with Jason Tan, host of The Analytics Show
Jason is Founder of Data Driven Analytics and the The Analytics Show, Data Driven Analytics, based in Brisbane, Australia, specializes in Digital Transformation through Data and Analytics.
In this episode, Eric discusses the impact the cloud has on day-to-day data operations, and how businesses will be affected if they don’t make the jump.
Transcript may contain transcription errors
Jason Tan: Welcome to the podcast of data and analytics in business who are learned from the leading industry experts using data and analytics to solve the problems and create values in practice. We’ll also learn where the industry is heading to and how data and analytics will shape the industry in the future. Most importantly, how they are preparing the pieces for digital transformation and disruption in the future. I’m your host, Jason Tan and thank you for listening.
Jason Tan: In this episode we have Eric Axelrod. Eric is the President and Chief Architect for DRGR. He is also the founder of Cloud Data Summit. Eric will discuss about the analytic in the cloud as well as the Cloud Data Summit web conference that he will be running. Eric will share with us some of the technology trend that he has seen that is currently happening in United state as well as the adoption of the cloud technology. I hope you find some of this discussion from Eric will be useful for your next car project and as usual, please feel free to drop us a message or Eric a message if you have any questions. Hi Eric, welcome to the analytics. So podcast, thank you so much for coming to our cell. I have been really excited to have you on board. You’re the first American that we have on the cells, so I’m really, really excited to hear what you guys can share with us, what you guys American are doing over there in terms of the data and the analytics.
Eric Axelrod: Well I might be the first, but hopefully I’m not the last. thank you very much. This is Eric Axelrod, founder and president of Cloud D ata Summit and of Digger. A little bit about my background is that we have been working on the ground doing data analytics implementations and strategic consulting and all sorts of things like that for about 20 years. So, so yeah, thank you. Thank you for having me.
Jason Tan: No problem. My president. So it looks like you are from my research. You are also an advisor for a few company like guests on lemon group, 10 X Factory advisory Clough and alpha site. Can you please share with us what are the roles that you play in, in some of these company What are you helping them
Eric Axelrod: Yeah, I mean, so the short answer is they’re all startup advisory roles. Some of them are focused on data and it’s kind of on an as needed basis, but a lot of it is really more about business strategy. you know, it’s about marketing, it’s about go to market strategies and a lot of the types of things that an advisor on an advisory board would do. Those are the types of things that I do for those organizations. And you know, one of the, one of the, the cool things about being in BI, something that we’ve talked about before is that, you know, we get exposure to a lot of different verticals and a lot of different business processes. So it’s not like, you know, if you’re a person working in shipping and receiving, you know, you, you know that business function intimately because you do it every day.
Eric Axelrod: We don’t necessarily know that as well as they do. But we get to learn a lot about shipping and receiving and a lot about receivable and a lot about, you know, inventory management and a lot about core financials. And ERP and you know, you name it. Right. And so that’s one of the great things about having a background in BIS, kind of having that exposure to all of those different business units. Right. And so I think that’s one of the things that really makes it possible for people like us to transition into those types of advisory roles. Because you know, we do have a lot of reasonably deep experience at a lot of different companies, different industries and different verticals and different business functions.
Jason Tan: That is great. It looks like you do a lot of things and you’re wearing so many hats at any given point of time. So I’ll, all of these things that you are doing w what is your main focus or your major focus at this stage
Eric Axelrod: So right now our major focus is cloud data summit. So we’ll talk about that in a little bit. But you know, a cloud data summit is coming up very soon and we are, you know, very focused on making sure that that’s a success.
Jason Tan: Yeah, absolutely. I do want to about the cloud data summit, but before I go on, I do want to hear a little bit more about the dig the consulting company that we run. Can you please tell us a little bit more about what sort of problem you solve for the client and is there any particular industry that you focus on
Eric Axelrod: Yeah, so as far as industry, the answer is really no. As far as the focus, we’ve worked at a lot of different ones. We’ve done a lot with manufacturing and consumer products and food and logistics and you know, and finance and insurance. And like we could just go on down the list with all of the kind of industries that we’ve touched in, in regards to the types of projects that we do. They are kind of all over the map. We do, we do, have a, have a focus on, on data warehousing. We do specialize in a few tools like Tablo, Talend, snowflake, and a few others. But you know, we’ve obviously we’ve, you know, if it’s a database that you’ve ever heard of, we’ve probably worked with it before on multiple occasions. So we do a lot of that. We’ve also done a lot of large scale Tableau implementations for very large companies doing a lot of scale outs and a lot of multi-node clusters and things like that.
Eric Axelrod: And in, in recent years, one of the big, you know, demands that’s been coming up is to do cloud data warehouse migrations as more and more companies are getting off of their, their on premise private cloud, legacy database, you know, the world’s platforms. There’s been a lot of demand to do that for snowflake, for big query, for as, as your SQL data warehouse for red shift and in those types of things. Right. we also do a few other things. For example, we do have a done for you dashboards in a few different verticals like supply chain and like, you know, some core business functions like around accounts receivable and finance and things like that. And we actually do have a turnkey supply chain, analytics platform that we recently rolled out that allows us to do a lot of things very, very quickly in regards to actually dealing parcels and freight.
Eric Axelrod: for a lot of different organizations. And we did also recently roll out a data science as a service platform for smaller companies. And you know, we’re, we’re gonna get into a little bit more kind of about what makes this possible later, but we’re really, what this means is the power and the flexibility of the cloud. You know, I’ve really driven down the cost of entry, the barrier to entry for getting in and doing data and analytics and data science. And so this is something that we have packaged up and we are offering to small companies at for less than the price that they can hire a data scientist, they can get our entire team plus all of the technology. So that’s kind of a really revolutionary thing that that only really became possible in the last couple of years as those prices have been coming down for all of these, you know, platforms.
Jason Tan: Do you believe that part of the reason that the prize become possible Is it because of the shifting and availability of the co competing, making all of these possible because you no longer have to have a range of a team that is tasked to manage the server, et cetera, but rather you can just focus on what in a manner which is the reality.
Eric Axelrod: Yeah, the management is a really big part of it because you know, going in in the old world with your, you know, your on premise databases, I mean you really couldn’t do much without a DBA. It’s like you have to, I have to at least have one database administrator on staff. Right. And in a lot of the older tools too, you also needed a society admin for your BI tool. Like if you’re running Cognos or big business objects or something like that, there’s reasonably high maintenance tools that you can’t just let run on their own because they do kind of run into problems and so you need it like at least that. Plus the tools are, are rather expensive as well. And the infrastructure to run those tools. And deal with the backups and everything is very expensive. And so the cloud being that these are managed platforms removes almost all of that because of the things like backups are done for you, right
Eric Axelrod: You don’t need a, you don’t need a person to go do that, monitor that, make sure it works, it’s always backed up. And then you know, you don’t typically need or you know, especially if you’re a smaller organization, you probably don’t really need a DBA to be able to keep the lights on. you might need one maybe to do some tuning or things get complicated, but you don’t need a full time person to do that. And so there’s, there’s kind of a lot of, a lot of, you know, advantages for being able to do that. And then the other side of it is the infrastructure scale and actually being able to have elastic compute and elastic storage because you’ll never ever run out of space. You’ll never run out of CPU threads that you can use to run your, do you use to run your thing. And those were all constraints that they used to have. On the legacy platforms that are, you know, those are now practically gone. And so that’s really what makes this possible and really makes it, you know, in reach for a company of pretty much any size to be able to get into a pretty robust, data science platform.
Jason Tan: Yeah, I agree. I think a lot of people don’t realize that is the data science and D O so the cow is not necessarily just for the big enterprise, but the reality is because of the cloud now it becomes so much more assessable and I reckon the medium size of the enterprise should also take advantage of it. Now, I do want to ask you to give a bit of context to the audience. If you don’t mind sharing. So who are the companies that you work with and condition Please give us some example of some of the works that you have done for your clients.
Eric Axelrod: Absolutely. So, just to name, name a few, there’s a lot that we can’t name, but the ones that we have, that we have worked with. We’ve got, we have reinsurance group of America, American rail car post holdings, post foods Aclara and a whole host of other companies that we, you know, some of which we have nondisclosure agreements with that we, you know, can’t talk about at this time. You know, like I said, we’ve been doing this for a long time and a lot of different verticals. We’ve done a lot of work and a lot of different companies with supply chain logistics, whether it’s freight or parcel. We’ve done a lot of work with optimizing, manufacturing plants. We’ve done a lot of work with it, with industrial internet of things, with productivity modeling, with people and with process, whether we’re talking about manufacturing or whether we’re talking about a mobile workforce or, or whatever. You know, we’ve, we’ve done a lot of that. We’ve done a fair amount with securities trading, with FX rate forecasting with risk modeling for you know, things like in the insurance business and cashflow forecasting for you know, just about any organizations. So those are just kind of really touching on a lot of the different things that we’ve done in a lot of different industries, whether it’s getting, whether it’s manufacturing or whether it’s financial services or you know, you name it, right.
Jason Tan: Supply chain seems to be one of the core focus. And you have done a lot of works in this area in the past and also early on you touch on that you were rolling up turn key supply chain analytics platform, Chengdu. Tell us a little bit more about this platform and what does it do and how can people use it to have their company to create value with the supply chain
Eric Axelrod: The short answer is that what we’re able to do is ingest data in real time coming from the wild out from the ecosystem. So if you have a shipping carriers or parcel carriers and you have trucks or trains or packages or whatever that are moving through physical space, as those things are hitting their various points where we are ingesting that data, you know, we’re ingesting all of those messages that all of the, that all of the shipping carriers send whenever the, whenever the, items move and we’re, you know, we’re, we’re sucking all of that data in and then we’re merging that with a lot of the data that’s going to be generated on the shipping side and the receiving side. And this is going to be what is actually in that package or what’s on that, you know, what’s on that rail car or whatever.
Eric Axelrod: What’s the value of the thing What is it insured for Where’s it going When’s it supposed to be there All of these different data points, right And then as we’re ingesting all of that data, it really gives, organizations, a 360 degree view of their supply chain. So they know when are things shipping, you know, when or when are they going to be here When do we need to ship something if we haven’t shipped it yet You know, and where it’s something that we maybe haven’t ordered in our, in our queue to be able to, you know, to be able to analyze is this something that we really need to rush and we need to get out right now because maybe it’s less expensive or maybe it’s going to get there faster. You know, if we ship it now versus if we ship it five days from now, maybe we’re going to be less likely to have a weather event.
Eric Axelrod: You know, maybe it is something that is in a season where you do traditionally have delays and that’s something that we can forecast, you know, that we can forecast for, you know, for, for the customer, by looking at historical trends and figuring out, proactively how much lead time do you really need to give these things if you want them to get there. And then how efficiently do you want to be able to get them there. So there’s a lot of different things that we, that we do cover in that space. But like I mentioned, it’s a, it’s a turnkey platform that you can just snap into an existing environment and you know, and start sending the data in and then, you know, what we have dashboards and all sorts of different, you know, for all sorts of different use cases in the supply chain and our business to be able to you know, turn it on quickly.
Jason Tan: Right. So it sounds like you could do quite a bunch of things. I suppose the question then I have follow up on that is how flexible can the client, Incruse and new model that is specific to their business needs and also to the art, they are business where they can plug in the analytic model in order to further pushing for that. Is that something that it could feel for this person
Eric Axelrod: Yeah, and that’s exactly why we designed it was because all of the turnkey platforms that have been out there previously, they don’t really, well, most of them are not very customizable or they’re not customizable at all. To be able to deal with a lot of the, a lot of the corner cases and is the case with a lot of business functions. Supply chain is really one of those that I almost want to say that no two companies really quite do it the same way, especially as we get into, you know, to bigger organizations. I mean a lot of the core of the way that, you know, you put a pallet onto a truck and then move it across the world, that part is functionally the same. But a lot of the other integrations that they’ll have and a lot of the other data points, you know, that they’re sending to be able to do this almost every organization is different. Right. And so this is really a core tenant to what to what we’re doing is making sure that if there is, you know, some other batch of data points that come in it related to a thing that it’s something that we can accommodate and you know, make it available very quickly to the end user rather than having to go back to, you know, a vendor of a transportation management system or something like that and ask him for, you know, platform customizations.
Jason Tan: That is great. I think this is something really exciting and especially a, one of the area that I really focus a lot, which is about embedding the analogy into the business operation. So in a lot of the works that I have seen or have done in the past, a lot of time people are just building the model and are building their analogy in sailor where people are taking the data, building the do the analysis, come up the result. And often those visa still have to be re integrated and also have to be action by someone else before it get pushed back to the business operation. Whereas what this turnkey platform that is doing is it is able to build a whole team, embedding the analogy as part of the business operation and not automate the whole process or reached out people doing this sort of thing. I think it makes a lot of sense in the supply chain or in the manufacturing. Do you think this sort of thing is possible in financial industry, financial service industry I have seen, and I’ve done quite a few of those, but I’ll be keen to hear your thoughts in this area in terms of viewing the analogy the into the business operation.
Eric Axelrod: I mean, and not only is it possible in the financial service industry, it’s something that every industry needs to be doing. It doesn’t matter what industry you’re in because you’ve been doing analytics for a long time yourself. You know, you see this a lot in a lot of organizations that have been doing it for 20 or 30 years that have actually had a official BI teams or data warehousing teams or analytics teams or whatever they called them. And you know, the way that it used to be done in the 1980s through the early two thousands was all of the teams were, were very siloed by design and they, you know, they, they conducted projects, they’ve rent a very rigid requirements basis where they would go to the business user and say, okay, business user, I need you to write me a document that explains every possible thing that you need this to do, which by the way, the business you can never do and produce me this document and then I’m going to give this to my dev team and we’re going to put it in their queue and then you know, you’re going to go and have to go get some money out of your budget and then pay my team for it.
Eric Axelrod: Right. And that whole process, I’ve always argued that that was a fundamentally flawed process because it’s not something that like the person who’s actually doing the work that’s actually analyzing the data and building the reports is very, very far from it. You know, they’re very far from being able to look at that and interpret is this useful Is this correct you know, and so it creates a lot of friction in the sense that, you know, if you’ve got that process where ed developer build something in that model and they hand it back over to the business user and the business user says this isn’t what I wanted at all, or it just doesn’t work very well or it’s incredibly slow or whatever the problem is with it. Right. And so what’s been really happening over, over about the last five years, it’s really been getting a lot of momentum is the way that organizations are structured cross-functionally for analytics.
Eric Axelrod: You know where you’re going to have somebody. It’s either this, it’s, and sometimes it’s the same person. And I think in a lot of cases it works well if you have somebody that is actually the business process owner that is very tune with their data, which they should be a lot of cases that that person is a great report writer. They’re a great dashboard developer, you know, because they’re the ones who understand it. And as long as you put a good tool in their hands that’s fast. And that allows them to explore their data, they’re going to be able to do it better than anybody else will. And it’s also massively faster because you know, whenever you have kind of that siloed model in practice, there’s plenty of companies that they might, they might have a six month backlog, you know, for their dev team.
Eric Axelrod: And so you’re going to put in a request, you’re going to see the first version of it six months from now, you know And so by the time you’ve put in the request and you get something turned around, there’s a good chance that you don’t even need that thing anymore. And that’s really a big reason why, you know, for lack of a better term, why companies still use Excel because it’s just too painful and time consuming for them to actually go to their BI team or to go to their dev team and say, Hey, I need you to create this thing for me. Because they know it’s going to take too long. It’s just going to be too painful until they’re like, well, we’ll just do it in Excel. You know, we’re just going to download it. We’ll just do it ourselves and then we’re never going to tell anybody about it. And then, you know, they just kind of, the business just kind of accepts that as a way of doing business. I mean that’s kind of really the long answer for, for kind of why all organizations should be putting analytics much closer to the business.
Jason Tan: Yeah, I agree. I agree. Especially if they can even automate the entire park so that the business fine line who are providing the service, they could just use some of those result, to do their job. That is probably better. And I suppose the challenges that I have seen in the traditional organization is that the challenge that they have got is to be able to modify the core system to be able to modify the enterprise system that I have got a, which is often going to be very time consuming and also very difficult to do because they don’t necessarily have the authority that they necessarily have the capacity and the ability to modify the call system to be able to push the anatomic result back to the core system. I feel like that is probably the biggest challenge as opposed to the newer company on a start up, like Amazon, Uber or Airbnb where they actually build a system from scratch. And because of that, they know the system in an hour at the same time to have the ability to be able to do anything and everything that they want to deal within the system that they built as part of their business. the business because of that is so much easier to be able to push that analytic result back that will eventually also reach to the end user and the consumer. Do you think that is the case
Eric Axelrod: I think that is the Holy grail that all organizations are kind of striving for in the sense that they can really have automated analytics, not just where you’re ingesting the data automatically, which is what we’ve been doing for a long time. Or generating automated dashboards, which we’ve been doing for a long time. But the idea to say that, okay, there’s this one important event or, or sequence of events or intersection of things that happened and we need to trigger something. Something needs to happen whenever this, whenever we see this trend or whatever, right. So maybe we need to send somebody an email or maybe we need to, you know, maybe we need to fire an event into an ERP system. Or maybe if we’re talking about a freight, you know, maybe the thing that we need to do is go into a workflow management system and create a task automatically for, you know, somebody in the customer service department that says, Hey, I need you to go follow up in this order.
Eric Axelrod: You know, maybe because, because it’s delayed me and them, it could be just as easy as that. You know, it was supposed to ship today. It hasn’t shipped yet. Go check on it. Very basic things like that. So I do think that that is kind of the you know, that’s the thing that, that I think organizations thought that they were getting, that they were kind of being sold from day one. You know, from again, 20, 30, 40 years ago whenever they were first putting in data platforms. That’s kind of, I think what they thought they were going to get and not many organizations have actually been able to accomplish that. I think for, for a lot of reasons historically, but we are a much closer to being able to do that now than we ever were. Even if you’re running on legacy ERP systems or, or things like that, the ability for, you know, companies that do have continuous integration, continuous delivery, they’re able to make quick deployments and quick changes and be able to build it.
Eric Axelrod: Like, you know, even if you’re running SAP, you know, you should be able to get on our bopper or something like that or, or an eye doc developer or somebody in that organization and say, okay, we’re going to be, we’re going to create a listener for this thing. Right And then on the other end we’re going to have a, somebody fire an event at this thing so we can then go build some automation on the SAP side to be able to say, okay, you know, XYZ events happen. Now we need to go build an automation in order to be able to do that. So, or a lot closer I think than ever for a lot of reasons. A big reason of that is, is embracing agile development. But what, we’re really closer now than ever for a lot of companies really being able to do a lot of automation. And again, it doesn’t really matter whether you’re an enterprise with a bunch of legacy infrastructure in place or whether you are a new startup. Obviously it’s a lot easier for your startup, you know, because your, you know, your applications are simpler and you have fewer of them, but you know, but it’s something that is, you know, attainable for all parties.
Jason Tan: I agree. And I also think that the idea of the API and also the ability to be API this day is making this a lot more easier and possible because now you will be able to connect all the systems together without modifying the core system as well. And because of that, things are much easier. The question is then is just about figuring out the sequence of the event and how to get this API out to connect to each other. I absolutely about this topic forever, but I do have to move on and learn a bit more about, definitely in the state and a few other things that I want to ask you about. So let’s move on on that and we’ll talk about that. We have a separate but Gaza on that topic a lot. So, the question that I’ll have for you, max, is, where do you see the market is heading now Like in terms for the analytic, what is happening in the States
Eric Axelrod: Yeah, so we kinda touched on it a little bit before, but I think that where we are right now is doing analytics in the cloud. And I say analytics very broadly when we’re talking about ingestion, we’re talking about reporting, we’re talking about data storage and being able to, you know, have cloud databases and all of these things. This is I think the most fundamental shift that has happened in the industry since MPP databases were invented in 1983 we’re currently undergoing this and you know, a number of these tools, like for example, red shift has been around since around 2012 and that’s really the first kind of elastic cloud database that was really kind of made for the cloud. And since then we know we’ve had a few other great contenders like snowflake and big query and as their SQL data warehouse for example, that are making the really, really, really changed the game.
Eric Axelrod: I mean, it’s really hard to understate how much impact that these have on the industry, but also on, on a company’s ability to be able to execute on a, on a BI project. And you know, and this also goes when we’re talking about middleware and we’re talking about data pipelines and we’re talking about microservice API APIs, I mean, all of these things, not, not only do you have the endless scale in the sense of, you know, even if you’re just consuming third party API APIs, as long as those API APIs are running on, you know, on one of these micro services platforms, you’re theoretically unlimited to how many connections you can have and how much data volume you can process, right And so it doesn’t really matter whether you’re sending it or receiving it or whether you’re running machine learning algorithms on an or whatever it is that you’re doing.
Eric Axelrod: This really makes it possible for you to get rid of all those prior constraints. And so, and so what makes us really possible as the infrastructure service platform as a service. So we’re talking about Amazon web services, we’re talking about Microsoft as your Google cloud. You know, these types of things really change the game with how you deploy applications and say, you know, in the old days you used to have a data center in your building somewhere and that data center, you know, would have a finite number of servers in them. And if you wanted to add servers, you had to go through a big long procurement process to get more hardware and then you had to rack it and spin it up and get the applications and so on. And it was a very long and expensive process to do. You know, if you were to add capacity to your data center and then if you want to, you know, you’re saying, Hey, we don’t need this capacity anymore.
Eric Axelrod: Well guess what You’re stuck with it there. There’s nothing, you know, you can’t just sell your servers on demand and then, you know, come back and buy them later. And so you know, that that’s what really kind of makes this possible is the ability to be able to run on these infrastructure platform as a service where you can spin up a server and then you can run it for a few minutes, a few hours, and then you can get rid of it. You don’t need that server anymore. It’s not doing anything. You don’t need to pay for it to sit there and be idle. So those are the things that really completely, completely change the game for how companies are deploying this. And it’s really, really hard to understate, I think, how impactful this is. Because I mean, not only does it affect how you budget for and how you procure technology, whether it’s hardware or software or whatever, but it also has a really big impact on your ability to process workloads.
Eric Axelrod: You know, which again, like we were kinda like we were, we were talking about in regards to we did, we talk about from it from an analytics point of view, somebody, you know, you have a new requirement, right So, so let’s say the CEO comes down and says, Hey, I need you to figure out where we know where we are exposed in raw materials. And this was a, this was a, a real example that we dealt with recently, for example, where the CEO came down and said, you know, we need to get on an earnings call for our next call and we need to tell them how the drought is affecting our food supply, right And so they needed to be able to go open up there if I need to be able to analyze their procurement data and figure out what food materials, you know, so like when we’re talking about corn, we’re talking about wheat, soybeans, and all of these things.
Eric Axelrod: Where are we buying them from How much are we paying them from What vendors are we getting them from and all of these things, right And ultimately be able to say, okay, if we’re going to have a drought, where is this going to affect us geographically Right And then ultimately kind of be able to figure out, okay, if we have to shift from the central U S to the Southern U S because of these conditions, what’s what, you know, what’s that going to affect our ability to get this material Right And then so the whole point is, is that this is a brand new thing that they hadn’t previously thought of before, right This wasn’t anything that the organization had planned for the idea of doing this wasn’t even on their radar. And so the CEO comes down and you basically have a relatively short amount of time to come up with this answer and present it to them so they can go get on the earnings call and talk about it.
Eric Axelrod: Right And so one of the things might be impossible to do in the old world because you already have an overworked database server you already have, you know, you already have a data model that’s defined and changing it as you know, and adding things to it was kind of hard because of the way you’ve structured your organization and your tool that you’re using. But if you’re running on a cloud platform, this becomes a lot more trivial. You know, you can go in here and say, okay, we have this new thing that came down from, you know, this is a new data analytics need that we have and we can run this without impacting anything else and we can run it as fast as we need to run it. So, you know, if we look at that and go, wow, this is going to take a week to run and we have to turn everything off to do it, that’s very, very possible that that’s the case in the old world.
Eric Axelrod: Well, in the new world with cloud technologies, you don’t, you can just say, okay, we’re, we’re just going to basically spin up a separate environment just for this one little use case and we can run that and we can throw as much resources as we need to do that. So you don’t have to, company determines that this is a super important problem and they need, they have to have an answer for this by this earnings call. That’s a very attainable thing to do versus in the old way there was a lot of cases, there’s just no practical way to do that. NATO, especially not in that time constraint. If they had known about it a year in advance, they could have planned for it. But you know, they didn’t know that that question was going to be asked. Right. And so their capacity wasn’t built out for that.
Eric Axelrod: And you know, and what, what’s always happened in the legacy platforms isn’t that somebody comes out with a really hard question like that. And a lot of times the answer is we just can’t do it or we just can’t do it in any reasonable amount of time that’s going to help you. And so if it is a transient event, like a drought for example, or a flood or something like that, that’s going to be gone after a while. Sir, we can go back and weekends, we can build a new model for droughts, but by the time the model’s done, the drought’s over and it doesn’t matter anymore. Right And so this is really what our modern cloud platforms allow us to do is we don’t have to worry about doing that agile architect or the D, we don’t have to worry about doing that old architecture. We can do it agile, we can spin up resources as we need it and we can kind of move from there.
Jason Tan: That is spot on. I, I really think that the, the car analogy and the whole idea infrastructure and platform as a service really driving down the cost of entry. And I think what that means also is a lot of the small and medium size of the business there can actually afford the same tech stack. Like the fortune 500. They can afford all these thing like the ASX 200 and is, is it really the matter of like utilizing this platform and this oddest thing that would never possible before. I really think that the medium size of enterprise should explore much on, on this one. from the experience and the claim that you serve, where do you think the organization, in terms of that the whole car adoption for data and analytic
Eric Axelrod: I think overall it’s still adoption wise, it’s still in its infancy. I mean there are a number of organizations that have already made the move and a lot of organizations kind of grew up, grew up in the cloud. They’ve kind of always been in the cloud. And so obviously they’re, they’ve been running on these platforms for a number of years. But then there’s a lot of other, or a lot of other more traditional enterprise organizations that are just really kind of starting to explore it. They’ve kind of been doing proof of concepts. They’ve been know, evaluating other technologies and those types of things. And so that’s kind of really the short answer is they’re dabbling in it. Some of them have already started these initiatives, but I think right now we’re kind of at the foothills of what is about to be a, are, are really, really big technological explosion that’s gonna.
Eric Axelrod: And then it’s going to last for a long time because I mean, in order for all of these companies to get everything moved over, it’s probably going to be decades honestly. But that doesn’t mean that they can’t start quickly. And so one of the great things that we see, and I mean it has its pros and its cons, but a number of companies have implemented what we call the concept of the tier two data warehouse strategy. And so what that means is that they have their existing legacy data warehouse, which made, or maybe it’s an Oracle, maybe it’s on Terra data, maybe it’s some SQL server DB two or whatever, and it’s running, you know, they’re running Cognos on it or they’re running business objects and they’re running MicroStrategy or one of the, you know, one of the, the legacy players on top of it.
Eric Axelrod: And whenever they go and move to the cloud, they are not going to make any changes to that legacy environment. So they’re not going to turn it off and they’re not going to make any model changes or anything like that. What they’re going to do is deploy a cloud database kind of alongside the existing one. So maybe that means they’ll build some ETL jobs to source from their existing data warehouse and move it to the cloud data warehouse. Or maybe they’ll just go back to their same source systems and then pull that same data again or modify some of their existing ETL jobs that they already have and drop that in the cloud data warehouse as well. And they’re going to, they’ll run these side by side and the cloud one Mo won’t necessarily have the whole scope of data in it, but they’ll pick some strategic areas and say, okay, we’re gonna, you know, we really want sales data in our cloud data warehouse because that’s the thing that’s, you know, that’s important.
Eric Axelrod: And then they’ll deploy a modern analytics tool on top of that, like Tableau or click or, or spot fire or power BI or one of those. And that becomes kind of their new technology stack. And then what they’ll do is kind of slowly transitioned their workforce from using their old tools over to using their new tools. And the ideal world is that at some point that legacy environment’s going to go away. And I th, and I can absolutely argue that it probably should go away in practice though. I don’t know that I’ve actually seen the old one go away. They’re just kind of reducing the workloads on it as they move more people off. But there are a number of kind of like core processes, especially around like financial planning and analysis and things like that that are in a lot of cases kind of married to their old platforms.
Eric Axelrod: And so I think realistically that’s probably going to be the, the kind of the state as it happens for a while where they’re going to keep, they’re going to keep both of these around, but there’s going to be a very distinct change where people are predominantly moving their workloads over. And this is one of the arguments that you’ll hear as well from, from the vendors. I’ve, I’ve heard a lot of this recently where, you know, where some of the new vendors are like, wow, we know we’re stealing X number of, you know, percent of customers from this other company that we’ve done in the last quarter. Or you know, there’s a lot of that going around. Right and that’s true, but then you’ll, the legacy vendors come out and they’re not stealing any customers from us. But, and this is kind of where the reality is, is that most companies are kind of deploying these in parallel.
Eric Axelrod: But what that means is that they’re not buying more things about buying more servers or they’re not buying bigger servers from the old vendors. They’re buying those from the new vendors and the old ones are going to stay around until they can eventually, you know, retire those. But then all of the, all the new stuff is going to be running in the cloud platforms and you know, and so this is something that’s happening now and I don’t really see that changing at any point in the future. And then, you know, as more time passes and as they’re able to move more, more subject matter into their cloud platform, they will continue to shift more and more people over to it, you know, which will increase the adoption of that platform and decreased utilization of their old ones.
Jason Tan: I think there’s a really good idea and also it is a really good way to ease the people into the cloud platform rather than trying to drop every single thing and then convince people to move to the cloud is a good idea. It is a good way to test the water and is people in there and as they are getting from Milia people will take a lot more initiative and gradually, wanting to move into the cloud and a is is a good way if we use the concept of MVP, I think that is fit per Valley.
Eric Axelrod: That’s exactly what it is. Well, and I think you brought up a great point too, because as you’re doing that, the way that you used to have to do that in the old world, if you run, are you running your own data center If we wanted to do an MVP or a proof of concept of a new technology platform, we would have to buy the hardware and you know, and it’s a lot and run it and then you know, manage all of the things about it, all of the backups and all of the high availability and all of that stuff. Right And so it’s very expensive just to do proof of concepts the way that it used to be. You know And now with these, you know, with these cloud platforms, you can just literally turn them on and turn them off. There’s no existing procurement that you have to do.
Eric Axelrod: There’s no existing hardware, existing servers that you need to do this. You can just literally go onto, you know, one of the cloud platforms, find the thing that you want and then just turn it on. That’s literally all there is. And if you decide it doesn’t work for you, you turn it off and you don’t ever use it again. So that’s really kind of the most, I mean, it doesn’t really get any more agile than that, you know, as far as being able to quickly try things, deploy them, test them, you know, and then iterate
Jason Tan: spot on. That’s the real definition of agile. So what would be one advice you would give to the organization who wants to move their analytic into the platform
Eric Axelrod: So this is going to sound very self serving, but you really need to get the help of an expert to plan your infrastructure. And there’s a bunch of reasons for that. And big ones are companies that make poor architecture choices whenever they go do move to the cloud. One of the biggest problems that I’ve seen is that organizations don’t really understand what they’re getting into and they will do what we call a lift and shift where, okay, if we’re running a virtual machine or a bare metal server or something on our old environment, we’re just gonna move that entire thing into the cloud as is. And generally that works as long as you’re kind of moving all of the pieces with it that need to go with it. The problem is that most often whenever you’re doing that, you’re going to increase your costs substantially because if you’re just running a virtual machine, so you know, let’s say if we have a server that is 128 gigs of Ram and it’s 64 CPOs and it’s a busy thing, if it’s an on premise server, it’s a sunk cost and you’ve got your, your sits up staff keeping it online and then as soon as you move that into the cloud, now you’re paying a lot of money to keep that thing on every single month.
Eric Axelrod: Right And so that’s a big mistake. And so one of the big things that they need to, you know, really focus on, whenever you do that lift in shift, you’re almost always a bad idea. Not always, but almost always. And you know, you really kind of need to be looking at whenever you deploy new things to the cloud, really look for elastic platforms, things that will scale up and scale down kind of on demand. So you’re not paying for this big, you know, huge thing to run in the cloud all the time. Another really big problem that we see in real deployments is kind of what I like to call the the drinking straw infrastructure. So what they’ll do is they’ll move a piece, like for example, a data warehouse to the cloud and then they’ll, they’ll leave all of the rest of their infrastructure on prem or private cloud or, or whatever, whatever vendor it’s with.
Eric Axelrod: And the network pipe is just not nearly, nearly, nearly big enough to be able to get the data from point a to point B. And they’re trying to kind of run these side by side. And it’s never gonna work because the, you know, if you were to look at it from a technical point of view and say, you know what, we can get as much upstream bandwidth as we need. But from a practical point of view, usually it doesn’t work out like that. You know, you’re going to have, you’re going to have bottlenecks and eh, you know, and you need to make sure that you plan for that because there are likely going to be bottlenecks and you need to know where they are and you need to be able to figure out, you know, if this is going to impact our business process. So for example, if you know, for a government to remove or move our data warehouse into the cloud and it’s something that is really, really tightly integrated with our ERP system.
Eric Axelrod: While we might need to move our ERP to the cloud as well at about the same time, because the idea that we’re going to be ingesting, you know, a billion records a day out of our ERP and putting it into the cloud, it just might not be practical to do, you know, if you don’t move them both. So those are some big ones. And then the other side of that, another big one with the drinking straw is not necessarily network. A lot of time it is a database constraint where, you know, if you’re running on an existing database server, that’s just a busy server because you’ve been had all your stuff on it for a long time. If you’re trying to do big data pulls out of it all, in a lot of cases you are not going to be able to do that or you’re not gonna be able to, to run those queries fast enough or you’re not going able to get the data out of those databases fast enough, not, it’s not necessarily a network problem and it’s going to be a database bottleneck basically.
Eric Axelrod: You know And so all of these things are going to be a pretty big impacts on how you actually moved to the cloud. And, and both of these things, you know, when we’re talking about lift and shift or drinking straw, those could really be perceived as failures because of latency or because the not up to date as much as we think it would be or whatever. So what the real advice comes down to is, you know, not only do you want to, you know, get the help of an expert you, but you do need to get serious about it. So definitely test it. Definitely do a proof of concept. But also like whenever you go in, you really need to plan that you’re going to have a lot of your stuff running in the cloud. And I think that almost every company is going to be running production data platforms within the next five years. And that won’t, that won’t be necessarily all other data platforms, but almost every company is going to have a production system in the cloud in the next five years. A lot of them already do. But even though for the ones that don’t, I mean, they’re looking at it now, they’re, they’re budgeting, they’re making those moves and so, it’s happening very quickly.
Jason Tan: That is great advice. That’s great advice from the past experience and also feedback that I received. It seems a lot of organization have end up getting a larger bill after moving to the cloud. So my question for you then is what do you think are the key contributor to these and what can they do to avoid it
Eric Axelrod: So just like we were talking about a minute ago with infrastructure planning, that’s probably one of the big ones because they’re really, they’re not taking a holistic look at their infrastructure and figuring out what we need to move and how we need to move it and basically need to make sure that you do that infrastructure planning and don’t ignore those legacy systems as a blocker to this project because chances are that they are a blocker and you need to figure out how to get around that before you really go all in and put a timeframe and a budget around this and start, start moving it. Because pretty much any legacy system, no matter what it is, if it’s a non premise system, you’re going to have something like that that’s going to be a problem and you need to know what it is before you start.
Eric Axelrod: Testing is another big one. So every organization needs to get in here before you go all in on anything. Be agile, start, do a small POC with something, test it, reassess. If it doesn’t work, try something else. There’s gotta be something out there that’s going to work for whatever you’re trying to do. You just have to find it before you go on and on like a waterfall project and try to try to get it done and say, Oh we know we have four weeks to get this thing done. Well you might not be able to depending on how that’s going to work. Right. You know, so you need to test, figure out how, you know, figure out what it’s really gonna take and then go from there. Be agile. In addition to testing. The kind of, the next big piece that you can do to avoid this is making sure that you are scaling your card infrastructure.
Eric Axelrod: And so what this really means is take advantage of your elastic infrastructure. So if it’s, if it’s an application or a database that you can scale up and down on demand based upon its workload, you need to do it. Because if you don’t do it, that’s going to be one of the big things. And that’s probably the biggest thing that contributes to a big cloud bill. Because you know, like I mentioned before, you forklift your entire legacy Oracle database or something like that under the cloud and it’s a finite number of CPS and a fixed fixed amount of Ram and a fixed amount of storage. Those are the things that are to chew into your costs. You know, you need to be scaling that up and down as your workloads change, you know And then another thing too is that if it’s not doing anything, turn it off.
Eric Axelrod: And a lot of databases, like for example snowflake does this automatically, but if you’re not using something like that and you have like a multi-node thing, you know, and we’re not, we don’t have a workload running against it right now. Turn that process off, you know, turn, turn that server off. And this is especially applicable for analytics because the workloads are very spiky, like I like to call them, especially whenever you’re talking about from like a dashboard point of view. So if somebody is using a dashboard tool live against the database, though, those are not anywhere near continuous workloads. It’s not like an ERP system or something where you can look at the server and say, Oh, it’s always at 80% CPU. It’s always never like that. It’s going to be, it’s on, it’s off, it’s on, it’s off. Right. And so what that means is that you know on on, on legacy infrastructure, you’re always paying for your maximum capacity.
Eric Axelrod: So whatever, whatever that upper limit is, you’re paying for that 24 seven three 65 and with, and you don’t want to be doing that in the cloud because you’re just throwing money away if you’re doing that. So you want to make sure that as your workloads decrease, whenever it’s not busy, that you’re scaling your servers to deal with that. So that’s probably the biggest one to be able to do that. And then in order to be able to actually make that happen, you need to be monitoring your infrastructure, which is a thing that a lot of organizations don’t really do proactively. And so you can’t just deploy it and assume everything’s fine. You know, you need to be keeping a really close eye on what’s doing what and how much is it costing us. And so you can make those decisions before, you know, a whole quarter has passed and then you’ve got an enormous bill and you go, wow, you know, we should, we really should have been watching this.
Eric Axelrod: Well you basically need to be watching it all the time. And then another big piece to this is, and this is especially applicable whenever we’re talking about infrastructure that scales, that’s elastic infrastructure. Somebody needs to be in control of the rules and who turns those knobs. So the whole point of this is that, you know, we can turn a dial and make it faster and we can turn it the other way and make it slower, make it bigger, make it smaller or whatever. And there needs to be very clear guidance and a very clear SOP around who has control of that and or under what conditions do they change those things. Because again, that’s another one of the big ones. If anybody could kind of do whatever they want to, whenever they want to, you’re probably, you know, everybody’s gonna be like, wow, this is so much faster.
Eric Axelrod: You know, we love this platform, let’s just make it faster and faster. They’ll just keep turning that knob up and then eventually you’re going to get a bill for $100,000. You’re going go, wow, what happened here Right. You know So somebody kind of needs to be in control of that and deciding how urgent are these things. And just because we can make them faster, it doesn’t necessarily make mean that we’re willing to pay for that. Right And so that’s where that, that those SLPs come in to figure out who and under what conditions are we going to do this You know And then as we talked about all these things, you know, we’re like, okay, the, the cloud might be more expensive in some, some circumstances because of all these things that we talked about, but you cannot ignore the total cost of ownership. And that’s a very, very deep discussion that, you know, we can’t go into all of the details here, but on the TCO, one of the big things that you’ll find in a lot of legacy it departments is that they’re CIS ops people that are keeping the lights on.
Eric Axelrod: They’re usually drastically understaffed. Oh I’m sorry. Rather they’re, they’re drastically overstaffed compared to what they need to be able to run on the cloud. And we’ve seen a number of companies, actually the larger ones recently that, they have actually reallocated 50 to 75% of their SIS ops people because they don’t need them to do that anymore because all of that’s managed for them and it’s actually, it’s managed better in the cloud than they were ever able to manage it themselves. Cause we’re, we’re moving over to new platforms that do a lot of the stuff for you rather than having to, you know, go in there and babysit databases all day long, for example. And so that’s a big thing, you know, so, so even in the end you might look at it and go, wow, our database is twice as expensive as it was. Well, what happens if you cut your head count by three quarters and some, you know, some of them over to some other business unit.
Eric Axelrod: Another big factor in that is like I mentioned earlier in the example where you’re trying to do an ad hoc process, like we’re trying to forecast what effect a drought has on our supply chain. In a lot of organizations they just cannot do that in their, in their old environments. Like, you know, if you, if you came to them and said, Hey can you do this And you know, they would say there’s, there’s no way we can do this in the next, you know, 30 days, 60 days, whatever. So you’ve got to be, you know, kind of put a price tag on what that is because you will be able to do that in the new environment. There’s, there’s going to be no practical limit on the infrastructure side that’s going to be a bottleneck there. Right. So what’s the value of you being able to do that thing now that you couldn’t do before
Eric Axelrod: And then, so that’s one of those things is on the, on the analytics side. And we’re also talking about just on the core maintenance side, there’s a lot of really bad stuff that happens. For example, like just companies just hitting SLA. So if you, if you have, do you say, Hey, our data needs to be up to date by 6:00 AM when our first people get in and start, you know, start doing their job. So many companies can’t do that. They cannot hit the resumes consistently. And so there’s a cost for not being able to do that. Right. And the other side of that is there’s also a lot of very, very basic things like taking backups. There was another company that we worked with recently, they hadn’t successfully taken a production backup of their database of their production database in like six months. If they had a crash, they would have lost so much data.
Eric Axelrod: They knew that they hadn’t taken a backup, but the reason that they are a successful backup, but the reason they hadn’t done that is because the database was overloaded and they didn’t have budget to make it bigger and the Pineland was going to be too long. So in the meantime they’re just running with no backups. Right. And so that’s going to, you know, a lot of stuff like that happens in the wild and so you really kind of need to assess, you know, what’s the value of either having this thing or not having this thing. Whenever you really figure that total cost of ownership of moving to the cloud, I think the point that you’d touch on the total cost of ownership is really good one. And I suspect that not a lot of are taking that
Jason Tan: into the account when they are assessing the cause. And thanks. I think that’s really great. thanks for raising that point. I feel like we have learned enough and quite a bit of the narrative works that you do and now what is happening that and what you see in the work that you do. In the state. And I feel that we kept talking about it forever, but I really want to move on to talk about visa co that assignment that you are starting. So yeah. Can you please tell us about the call data summit and why did you start it
Eric Axelrod: Absolutely. So with cloud data summit, I mean, the short answer is to why I started it is all of the things that we kind of just talked about. But a big one of those though is hype, right So there’s a lot of vendors out there that are selling different things that are, you know, different cloud data technologies, whether it’s, you know, AWS or Google cloud or Azure, or whether it is a vendor that’s selling a database or a BI tool or a data pipeline tool or something like that. Right And there’s so much hype and there’s a lot. And frankly, there are a lot of new tools out on the market that, not a lot of people have used. And so whenever you are a, you know, whenever you’re in the position or if you’re, you know, if you’re a chief data officer or a chief analytics officer or something like that and you’re looking at this for your technology, there’s really not a lot of good places where you can get unbiased information.
Eric Axelrod: And there’s also not a lot of other conferences that are really spending a lot of time talking about this stuff. You know, most of the others are really hyper focused on data science. Algorithms are on machine learning or on open source technology or something like that. And so we’re, we’re really trying to fill that gap where you can really learn about a lot of the ins and outs of these cloud technologies and see what other companies have done. You know, a lot on the a lot on the infrastructure side and kinda like I mentioned, you know, there’s, there’s just a lot of these technologies are relatively new and there’s just not, there’s not a lot of knowledge out in the ecosystem. It’s not like, for example, like if you, if you need an Oracle DBA or PLC equal program or something like that, they’re kind of a dime a dozen.
Eric Axelrod: You can get them all over the place, right But if you need somebody who’s experienced at tuning Redshift, those are going to be harder to find. Right And so this is one of the things that we want to, you know, that we want to make sure that we can do a lot more education on and make sure that there’s a good pipeline for people to be able to learn how these things work. It is hard for a lot of organizations to deploy and manage good infrastructure because of a lack of expertise in this. And so this is really kind of the core focus for what we’re doing here. And then there’s that. It’s, it’s really, like I mentioned, such a transformational technology. I think this is, you know, this is the transformational technology of our era. And so I think it’s very, very important to be on the forefront of that, you know, and really kind of lead the industry.
Eric Axelrod: That’s kind of one angle four for what we did it. And in what a lot of people don’t, don’t know is that a cloud data summit is a 1% online conference. And so this is really a lot to do with the future of work, the future of collaboration, the future of communication, the, for example, web conferencing. This is drastically changing how people work on a day to day basis. And I think this is one of the, one of the reasons why, for example, you know, zoom just IPO, right And just a few months ago, and this is one of the reasons why zoom has had such explosive growth and also why they’re valued such that they are, they have a very high valuation. And, and this is really the reason why, is because the world is shifting very, very, very quickly to be able to be a lot more accepting of having remote workers and remote collaboration than they ever were before.
Eric Axelrod: And this whole, web-based competencies are really just starting. There are, I mean we are not the first, there have been others. Amazon web services actually just did a big one. about two months ago. They did a big, a big global, a virtual conference. And there, there have been a few others at one of the other big ones in our spaces, the Tableau fringe festival, which has been going on for I want to say four years or something like that. And it’s a big, you know, big 24 hour event. And there have been a number of other ones that have been, you know, happening in various various subjects and different verticals. And this is something that I think is going to be huge in the next few years. And there’s a number of reasons but one of the big reasons is you’re removing a lot of the barriers to entry cause there’s so much of the cost that’s baked into going to conferences is travel and it’s time off because of travel.
Eric Axelrod: And so you know, if I’m going to go to a traditional brick and mortar conference and it’s, even if it’s a three day conference, I’m out for five days, you know, and I, I am, I’m staying in a hotel for at least three days, maybe four days, maybe five days, depending on what my schedule looks like. I have to fly. And then I have two days that I’m traveling where I’m not going to really do any work at all. Not any real productive work. Right. So all of this stuff goes away whenever we do, you know, whenever we do online conferences and so this is where I think that this is going to be absolutely transformative to the industry. And it also, as you’re doing this, the barriers to entry price wise drastically decreased because you don’t have to pay for everybody to fly and stay and all of those things.
Eric Axelrod: And then you also don’t have to pay for a convention center and all of these other big brick and mortar costs that you have to incur to, to be able to do that. So this is going to be a really, really, really big industry, not just in the beyond beyond BI and analytics but across a lot of different verticals. Just the ability to be able to, you know, have that full conference experience online. I think it’s going to be massively transformational to the industry. And you know, I mentioned about zoom. Another one of the big things that I think is really impacting this is a, you know, everybody talking about Uber IPO, I’m sorry, the Uber IPO, the, the, we work IPO and there’ve been a lot of pundents I guess I should say, right, that are talking about, you know, there’s a, Oh we work so over valued.
Eric Axelrod: They’re a real estate company. They’re not a tech. I think a lot of the people who are saying that are kind of missing the point because I think what we work is when we talk about remote work, the way that the, like the way that people are going to be working, and this is already happening, this has been happening for a while, but I think the way that a lot of people are going to be working more and more in the very near future is instead of you driving into an office that’s the central, you know, the central corporate headquarters, wherever, wherever you work, especially if it’s a long drive, you’re going to be going to a nearest coworking facility. You’re going to be going to where we work or our local coworking space or something like that. And that’s where you’re going to work from.
Eric Axelrod: And then you’re going to use tools like zoom for example, right To be able to connect into your office and actually, you know, collaborate with the rest of your people. And so the reason I bring this up is because what we’re doing here is really going to have a really, really dramatic effect on how I’m going to say I’m really everything and I want to talk about like city planning, talking about local transit. You know, we’re talking about, I think this is could very well have a negative impact on transit companies like Uber city buses, subways and things like that because all of those are really designed to haul people into the city center and out of the city center and move from hub to hub. And a lot of that I think is going to go away, as we start doing a lot of this remote work and remote collaboration. So yeah, I think that what we’re, we’re really kind of on the cutting edge here of how people are going to be working, on a day to day basis in the very near future.
Jason Tan: I think the point that you raised about the, we work is really a good one because of the way that we have planned a city. It is just impossible for people to come here for forever and especially like two or three hours each way. I think that just ridiculous and now with the we work seems to be really playing opposition is so well on, on that area rather than just the whole coworking space that could work for absolutely rather than 40 enterprise. The other thing that I, I really like about what you talk about is the CDs, the cloud data summit because of the doing it over the web conference, it now basically means that a lot of people can attend the conference so the organization no longer have to choose just a selected few because of the conduct fly and the hot towers had troub, but perhaps the whole team can, can even go to, and they can even do it in the office hour. I think that’s really, really exciting. Please on what is a jazz, so what people can expect, what can they expect when attending the cloud data summit
Eric Axelrod: So, I mean, obviously we, we already kind of touched on a few of the other points, but I think the really the most important thing to talk about is that it’s really, it’s just like attending a traditional conference without the travel and without having to stay in a hotel and all of those things. And I say that, well, so we, for example, of course we have sessions and this is something that online companies has been doing for awhile, where you kind of dial in and you can watch your session kind of like a webinar. But that’s not what carb data summit is. We also have the ability to do one-on-one networking just like you would if you were meeting somebody in person. And then also the ability to meet face to face with people in group settings. And so for example, we have group lunches, we have group happy hours, we have networking that’s carved off in between sessions.
Eric Axelrod: So as soon as the session ends, just like you would kind of shuffle out into the hallway and you know, go get coffee. You do that here too. And you meet with people while you’re doing that. And another great thing that you can do, you can create your own breakout sessions. So if you’re in here, and maybe this is not a topic that you care that much about, whoever’s talking right now, you can create your own rakeout and say, Hey, let’s go talk about this. I mean, you know this specific database technology, you go create your own table and then other people can see that you created that and they can go join you and you can talk live about that topic. Right. That’s something that’s really, really fascinating, you know, with how we’re actually able to do this. And again, just like you do it a real conference, you know, a brick and mortar, you know, if you’re in there you’re like, wow, this speaker’s just really boring. I don’t really, I just don’t really want to hear about this. Or I already know about the subject. You’re going to go out into the hallway and maybe work on something else. But you can also set up at a table and you can discuss something with another group of people. And do the exact same thing here. So
Jason Tan: a webinar, this is beyond what be nowhere that could, apart from listening to to some of those great speaker, presenting, but they can actually also do the things that they do like at a conference and they can even set up their own.
Eric Axelrod: Absolutely. And so I think that that, this is really why this, this is groundbreaking because, because you could, you know, because anybody can do this for one and anybody, you know, the barrier to entry as far as getting in is so much, so much lower. So like, you know, kinda like you mentioned before, you know, you’re, you’re, you’re, you’re an organization who’s looking at sending people to conferences as well. If you’re going to a brick and mortar, it’s going to be probably a minimum of $3,000 to get in for one person, right Because you have to pay for all of those, all of those ancillaries, you know, and then so if you can cloud data something, you can send six people for that price, even if the person is, the person’s an intern or even if the person is, you know, an individual contributor or something like that, they can easily get in and in participant as anybody else can. So you can have somebody, again who’s, you know, who’s an intern, if they want to talk about some new technology that they found that they want to talk about implementing in your organization, they can go create their own round table and say, Hey, I want to talk to people that implemented Kafka. Right. And you can discuss that. So this, it’s definitely not, not a webinar. It’s far, far, far more than a webinar or really any other, you know, online conference that you’ve ever been to.
Jason Tan: That’s great. And, what would they, what would happen after the conference finished
Eric Axelrod: for each day we do, we do have a happy hour carved out on the schedule. So after all the kind of official sessions is over, everybody will be able to kind of conclude that day, either be able to conclude that day and then you know, meet up just like they would at a regular session. And then after the actual, after the whole conference is over, we’re actually forming a new online mastermind beta community. And so anybody that gets in on a VIP ticket is going to, is going to get a couple of of access to the community and where this is where you can, you know, continue, collaborate continuously after the conference is over. And the reason we wanted to do this is, this is something that has always kind of been a pet peeve for me and going to a traditional conferences that you, you know, you’ll meet some great people, you’ll have great chats with them while you’re there about whatever, you know you’re trying to implement or whatever.
Eric Axelrod: And then the conference is over, you go home and then you never talk again. You know, you might message them occasionally, but you know, like that whole kind of experience has gone. And so what we’re doing here is making sure that this conference experiences is kind of continuous. So you know, if you did find a lot of really knowledgeable people outside of your organization that you can lean on and you can use them for, for expertise, or if you really want to get their input on whatever, that you can continue to do that after the conference is over and you kind of have that continuous communication pipeline open to be able to talk to those people. This is great.
Jason Tan: This is, seems like that is a lot, a lot of value on the money and is much more bigger than just attending a conference. But rather you can have a heavier takeout session is not a webinar. You can have your those normal conference section that you networking with our people. And apart from that, you can even have the online mastermind community that allows you to continuously talking to people that you meet at a conference. I really think that is a great value. You do you have any to put in code for follow my listener in the pot guys I think they will benefit a lot from this one, especially if they can get those. Speak to some of the great speaker which I’m going to ask you about. But yeah,
Eric Axelrod: we absolutely do. We’ll give you a code that you can drop in your, in the comments in the video and then, yeah. And then, all of your listeners can use it.
Jason Tan: Thank you. I thank you so much for that one. Can you tell us about some of the speaker that you have got at the cloud data summit I would be interested to find out.
Eric Axelrod: Yeah. So we have a J not a genre on, she has the head of AI at Microsoft. We have Scott clan, Daniel who is the chief data scientist at Legg Mason and a Harvard AI instructor. We have a Curt Cagle who is the AI contributor for cognitive world and not Forbes AI contributor. We have Ben Lynn stet who is the industry trailblazer and the inventor of the data vault methodology. And we have a Jawad Satara AJ who is the chief data officer at so much community care. And Daniel O’Connor, who is the product master data guru at aware. And Daniel’s actually really interesting. He’s, he’s led some very, very large, product management system implementations that he’s gonna talk about a little bit. And then, and you know, that’s just kind of fucking out. I’m also going to be doing a keynote on kind of some of the same ideas that we’re talking about here. And then, and then we’ve, we’ve got a few other instructors. If you want to see about everybody come to our website, you can kind of see the full rundown of all of the speakers and all of the, on all of the, all of the agenda items,
Jason Tan: some great big name of the guest, Liz, you have got there. And I’m sure I will make sure that dropping the, website, of the co that assignment in the podcast and also the website so people can check it out. what is the vision you have for cloud data, Sammy
Eric Axelrod: So when we talk about the cloud, I mean the real vision is to educate the huge wave of companies who are moving to the cloud in the next few years. cause I can kind of, like I mentioned before, there’s really not a lot of focus on kind of on the infrastructure side of the cloud and the infrastructure side of, of data. Right And so we, we, you know, we want to be, you know, we want to be in that space. And then, you know, kind of the, the other side of it as we’re talking about with the infrastructure and the fact that w, you know, that this is web-based is that we want to make it, you know, we want to be able to make, to make it big and be able to reach a lot of people. And, you know, so the, one of the, the incredible part about doing this is that we can actually scale this much, much, much larger than you can ever really do with a physical conference.
Eric Axelrod: practically, you know, the biggest conferences out there, a whole, you know, 30,000, 50,000 people, you know, in, in any vertical or any type of conference. And it’s very hard to do, to have, you know, buildings that are that size and be able to deal with the logistics of getting everybody in there and housing them and all of that. It’s very expensive. It’s very time consuming and all of that. And it is time inefficient, because of all the travel and all of those things like that. And so those are, those are really big things that we want to be able to address. And you know, like we mentioned before, really lower that barrier to entry for anybody that wants to be able to get in, they should be able to get in. And, and so yeah, that’s, that’s the, that’s the real idea of what we want to do on, the fact that we’re able to do this online.
Jason Tan: I think that’s really exciting. I think people should definitely join the cloud data summit and a heavily listen of what everyone else is doing around the world. And I’m really hope it goes well and I’m sure it will go well. Thank you so much for that one. And Eric, I want to ask you one last question. What are your free but reading materials or what are the things, where are the places that you go to for learning from others
Eric Axelrod: So I’m one of the people. I have a pretty severe attention deficit problem. I don’t read books for pleasure. I don’t really, I don’t read a whole lot for prep, for, for pleasure. I actually have a really hard time processing, long form text, even long, long blog articles. If it’s more than like a thousand words, I’m out. You know, it’s not something that I can, my brain doesn’t process, it doesn’t comprehend it. So the thing that, that I love doing is podcasts. and things that I can consume kind of while I’m working on something else, something that I can listen to. And so a lot of the audio type things that I listened to are, I love listening to conference replace for one, which is a great one. There’s a, there’s a lot of, a lot of tech conferences that have posted either some or all of their content on YouTube or another, you know, or another format.
Eric Axelrod: And you can just listen to those replays kind of on demand. And there’s also a lot of great ones. And I think a lot of these kind of really fall into what I would call, you know, human psychology. One of the ones that I like a lot is the salesman podcast, a Joe Rogan podcast, and then anything as far as interviews with Oren Klaff, author pitch, anything Chris Voss, author of never split the difference. And then anything from Scott Adams, the creative billboard, a lot of that stuff is just fascinating to me because it’s a really touches on human psychology and how it affects the way that we make decisions. So that’s a lot of the stuff that I, that I, that I consume. And, and then I also have a lot of off favorite blogs that are a lot more industry centric. So I like CB insights a lot, which is a little bit outside of, you know, the traditional data things that we work on.
Eric Axelrod: But it’s very, it’s a lot of very relevant because they do a lot of deep dives into industry disruptors and startups that are really going to take over spaces in the middle. A lot of the other, a lot of the other more mainstream, I guess, publications in our space, like the CIO magazine information week seven w data, Katy nuggets and so on. And I, and I also love Saster. Jason Lemkin is a great author of a lot of this material. It really has, it focuses a lot on startups and a lot of specifically lot on SAS startup.
Jason Tan: It does. Thank you so much for sharing some of those, material and also the sauce for where you learn things. I’m pretty sure people like me would be interested to check it out. And, I like to end this one by thanking you so much for coming onto the podcast. Really great talking to you. Thank you, Eric.
Eric Axelrod: Thank you very much Jason. And, and for anybody that wants to check out cloud data summit, it [email protected] And I think Jason is going to put some links in the, in the video.
Jason Tan: Thank you. Have a good day.