B2B Revenue Acceleration
B2B Revenue Acceleration

Episode · 3 years ago

14: The Big Data Landscape in a Fast-Changing Economy w/ Tom Mack

ABOUT THIS EPISODE

The data you collect should be speeding you up, not slowing you down.

The only way to make sure this is happening is to leverage the power of the cloud, but how do you keep up with all of the recent trends in this space?

Tom Mack is the RVP of Sales, EMEA at Qubole where he joined four years ago to build out a sales team in the Western United States.  Qubole provides big data as a service, so they understand this landscape well. They focus on allowing automation to handle the life cycle of data clusters so organizations can get insights and yield out of their data as opposed to managing the infrastructure associated with big data technology.

In the time since he joined the team, Tom and his family have moved to London and opened up Qubole’s European sales operation where the team is on track to keep expanding throughout Europe. Tom’s job is to drive sales and create new business opportunities.

Tom joined us for this episode of B2B Revenue Acceleration to talk about the Big Data landscape, different verticals and industries that are benefiting the most from this technology, and differences between the North American and European markets.

You were listening to bb revenue acceleration, a podcast dedicated helping software executive stay on the cutting edge of sales andmarketing in their industry. Let's get into the show. Welcome to be tobe a revenue acceleration. My name is over, I am with you andI'm here today with Tommac from qubold. Are you doing to Daytam, verywell right. How about yourself? I am doing fantastically well. So todaywe want to talk about you, about the big data landscape in a firstchanging economy. That's a big, big topic. Probably at the pig thatis is is very close to your hearts, based on the world that you aredoing at quebold. But before we go into the details, can youplease tell us a little bit more about yourself, your role within q bowland I guess what q bold does as an organization? Sure. So,I joined you all up four years ago in the United States and built outthe sales team in the western US and...

...the management team asked me to openup the European operation. So my family and I moved to London a yearago this time to open up your office and drive and create a business herein Europe focused out of London and we've since then built a team and youare on a track to really expand that business and that opportunity throughout Europe.What q will does is it does provide essentially big data as a service,with the idea of allowing automation to handle the life cycle of clusters so thatorganizations can focus on getting insight and yield out of the data as opposed tomanaging the infrastructure associated with those big data technologies. We're on track for aboutthree hundred customers and growing very well. A couple of million queries executed againstcuble and we're processing PEDA weights of data, close to an exhibited data per monththat we have our clients, but...

...that sounds like a no full lotof data. That so obviously one of the conversation point to then, andthe reason why we want you to have utim, is to discuss about thebig data landscape. And we know that big data as became a game changein most modern industries of other last few years and while the technologies have evolvedand there is a lots of data as well in organization. So I thinkit's fair to say that organization of more and more data they've got one morecomplex data they probably have more and more systems holding the data together. Couldyou please share with us a bit about how the actual big data landscape islooking at the momentum, from yokels pick teeth, but also what do youbelieve all the trends for the future? I think I'd probably start with themajor trend, of is migration of big data workloads to the public cloud.We're seeing a significant number of clients here...

...in Europe already in the cloud orhaving plans to migrate their data workloads to the cloud, and that's for tworeasons. One is that the resources needed for big data are typically quite elastic, so the whole on demand elasticity of the cloud plays very well for that. But there's also this separation of compute and storage, so the object storesof the respective clouds, or that's Azure, Google or Amazon. That's a verycost effective way to store pat of bits of data and then, whichis very inexpensive relative to running it as hdfs and a traditional data center ina traditional data center on an expensive compute or expensive machine. And so whatthat means is that you're able to do in a very cost effective way storeyour data and then con use the elasticity of the cloud and the virtual machinesin those cloud providers to them process that data on them as needed data basis. So it allows you to scale up...

...very quickly and then, with thechanges within the cloud to per second billing, allows you to be very aggressive onthe downscaling. So you're constantly trying to optimize the current cluster based on, you know, the current need. So that's one trend that we see. The other one is that people are more and more interested in streaming analytics, so as data is collected in real time to do as much analytics asas possible, and use cases for that are a lot around ECOMMERCE, pricingoptimization. We see a lot of anomaly detection within streams to understand how thebusiness is actually prefer me, and I guess the third trend that we're seeinga lot is more of enabling of self service analytics, so providing very broadaccess to that organizations but doing it in a very fine grained way as kindof that third trend. Okay, so it's basically doing more for less.So getting the advantage of the public cloud...

...is really around its cust saving.It would believe, and also probably the pain of managing it at a center, because we know that that doesn't is not easy to manage. You needto deal with redundancy and all that sort of things. We also it seems. It seems from the tools of points that you've mentioned that it's about thechange in conception of the data. It's about the change of what we usedata for. How do we think that data to make business decisions. Soit's really do you see also that the transition into the business intelligence, theway people are making decision based on the data they collect? Well, wouldyou say, is the same, but it just got more granularity. NowI think it's very smaller in that use case, but they do have largerdata sets that they want to use to whatever you company is goal is todo, is enable operating markets or, you know, decisions closer to theconsumer. You can allow the organization to do that. And what they're tryingto do is, rather than just basic...

...operation of they that are trying toappend that with other social data and other analytrics or data that they might purchasefrom third party providers to provide a better view of the world so that theyultimately can make better but better business decisions on behalf of the consumer themselves ortheir consumers are there and customers. Does that mean then, that you seenew functions, so marketing for example, or finance so but new function withinorganization asking for more intelligence, asking for more of that data of or requiringto use more big data solution in order to, I guess, create efficiencyor accelerate revenue in down function. Do you see those lanes of business consumingall definitely so. I think that's one of the trends that organizations are tryingto do, is provide a larger data set to be able to or datasets and doing curated data sets, but...

...at a much larger scale for thelines of business and though their internal customers, so that people can make a veryinformed decision, you know, tactical and strategic within an organization. Soit is definitely a situation where both the internal customers are asking for more datasets to be included, which means the infrastructure has to change, and that'swhere products like ours play a role and we typically, in most cases,will sit next to existing investments. But providing that broader access to larger datasets, because it's focused on big data technologies as approves to traditional R DMShas or relational databases and a price datawarehouses. Okay, that makes sense, Ithink. I think we see a lot of that in the market AlSelf. So that's good. A question about the functions and the line ofbusiness and all the people within the organization that comes from all that big dataon in Moll that's intelligence refine intelligence from...

...big data. Do you see anyspecific verity chords of specific industries also that have a small that's requalment f implementingbig detest solution and and also it's kind of a two side equation. Youhave comments. So do you have examples of the kind of resorts they canexpect from implementing big big data solutions? I think one of the trends thatwe see across the company and not just in Europe, for London especially beinga heavy retail environment, there's a lot of mobile application and well documented thatmore and more people are sending and buying to the mobile experience, but that'san iphone, ipad, some sort of device like that of the laptop itself, and so what we see out there is more under of really understanding theuser journey within the applications themselves, a...

...lot of ab testing that goes alongwith that as well, and then really, once they solidify that, executing quicklyon price optimizations based on competitors and competitive an analysis as well. Soit could be across the board. We have several companies that are in thetravel industry that are really focused on obviously maintaining margin, but having a veryaggressive pricing strategy to win that business, and the same thing can be saidon consumer retail as well. So in certain situation rations, you know,with AB testing, some of the metrics that we've seen from one kind inparticular is about a seven percent of lift and revenue as a result of betterdecisions around how content is surfaced within their mobile application. That's wonderful. Sothank you very much for sharing allder that about the big data market and allthings are evolving at the moment. It's very useful tree term. One finalquestion that I've got for you. So we know that qubold organization is growingfast, ending into new region. We...

...ownder some from your introduction that youcame from North America, from San Francisco, I believe to be to be tobe accurate, to London. If I remember correctly, the first timewe met you actually fresh of the plane and we met for a coffee inLondon. So I guess my next question is more it a bit of apersonal question to you and I'd like to I'd like to onner so much isyour experience. So if you can share your experience as an American coming intothe UK and what you've seen as the main differences between the American market?Well, obviously you've been successful and that's the reason why your management team wantedyou to come to Europe and use that experience to push the European market andget that to take off, but from your perspective. So I guess it'smore of a personal question. was on the business question, but I'm alwaysinterested to understand the true jual differences that you've seen the way business is done. So yeah, you get to get to get you with some that's sure. I think, to be fair,...

...when I first started a huble wewere very new and we're very targeted towards specific verticals and then as we grewwe started to expand and what I'm seeing is that we have to do moreof that here. So I think it's I think the answer is kind oftwofold. One is that there's a lot more education that has to happen herebecause the market has changed in the four years I've been with cuble. There'sa lot of people that in companies that are coming out or have been outfor a while and, you know, everybody's mixing marketing messages promising the worldwhen it comes to analytics and big data. So I think the customers are alittle more conservative here in London and in Europe, but they also have, you know, much more to look at these days and really kind ofdo a lot of fetting. So the process is a little bit slower andpeople making a decision for or against because there's much more to look at rightnow and there's a lot to weed through...

...in the actual market itself. Alot of different players out there. So that's one of the challenges that we'veseen. It's we still win business, but it just seems to take alittle bit longer and the education seems to take a little longer. The otherissue, I didn't talk about it in one of the trend conversation that youtalked about up but the pace at which all these open source technologies are movingand evolving and, yeah, promise that goes along with them is substantial.So you know, you have this trend to go from machine learning to deeplearning right now, with all the tensorflow, cares mx that in the different librariesaround the data science world, and those are really challenging to keep upwith, and the decisions how to use those in the most appropriate manner arereally tough as well, and the skill set needed for those is very difficult. So you have to have setting the proper expectations with clients to say thatit's not going to be, you know, a very quick use of these deeplearning technologies. There's a learning curve...

...associated with it and then there's thewhole migration to production that goes along with it as well. So expectation settingsfor results is and setting those properly for clients is something that we're really tryingto be very specific around, given the pace that with technologies and the evolutionof those technologies as well. So that's okay, Great. What's that's good? What's essentially your insight? I'm sure you apology has got to have alot of taking from from the different things that you discussed today, which wedo every single time we ask our guests to give us away or give awayto our least, not to get in touch with them up to get intouch with that company. They want to have a bit more of a conversationwith you as an individual or, if they won't engage with you, todiscuss about your solution. In your case, that would be discussing about cuboard.So toub what is the best way to get in touch with you?Sure best way is just Tom at qubolecom...

...to U Bolcom and is Paya emailand happy to respond and answer any questions that people may have. Best ononderfulthank you very much. Really appreciates your payment inside today. It's great speakingwith you as always. Ready thanks for the time. operatics has redefined themeaning of revenue generation for technology companies worldwide. While the traditional concepts of building andmanaging inside sales teams inhouse has existed for many years, companies are strugglingwith a lack of focus, agility and scale required in today's fast and complexworld of enterprise technology sales. See How operatics can help your company accelerate pipelineat operatics dotnet. You've been listening. To Be Tob revenue acceleration. Toensure that you never miss an episode, subscribe to the show in your favoritepodcast player. Thank you so much for listening. Until next time,.

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