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Take control of your career! Join Donal Bourke as he shares how he doubled his salary by using Alteryx for cloud optimization, facilitating his transition into a financial operations role. Donal discusses the importance of curiosity and offers valuable tips for breaking into Financial Ops, all while expressing his passion and dedication to his work.






Ep 160 (YT thumb).png


Episode Transcription

Ep 160 From Finance to Analytics

[00:00:00] Megan Dibble: Welcome to Alter Everything, a podcast about data science and analytics culture. I'm Megan Dibble, and today I'm talking with Donald Burke, a cloud optimization consultant at NetApp. In this episode, WeChat about the financial operations field, how Donald uses Alteryx for cloud spend optimization, and his passion for helping others transition their careers to analytics.

Let's get started.

Hey Donald, it's great to have you on our podcast today. Could you give a quick introduction to yourself for our listeners? 

[00:00:34] Donal Bourke: Sure thing. Thanks a million for having me. Big fan of the show. I am Donald Burke. I am based in Leeds in the UK, in the north of England, as my accent betrays. I'm actually from across the IRC.

I'm from from Cork in Ireland, and I work as a cost optimization consultant. So effectively my job is to. Help customers save money on their cloud bill. So I look at numbers and I talk to people. I work for SPOT by NetApp. They're a company that look at visibility, automation, and continuous optimization for customers, clients, and their cloud operations.

Outside of work, I wrote really slowly and not very far. I play hurling and gillick football, not very well, but we've got four small kids. So anything to get me outta the house is, is a bonus. So yeah, that's me. 

[00:01:24] Megan Dibble: Awesome. I'd love to just start off with how did you get started using Alteryx in your job? 

[00:01:30] Donal Bourke: I love the tool.

I love the love the application, massive fan. I was introduced to it by chance back in 2018 when I started working as a revenue analyst for a US drug distributor. So we had to calculate a rebate based on 20 million lines of data. And obviously all accountants love Excel first, but 20 million lines is too big, so Right.

Alteryx was a tool tool for us. We were using Alteryx to pull in these, these raw files, do our calculations and manipulations on it to calculate this rebate. The beauty of it was that we had a really strong Alteryx team based in London who we could refer to and, and get some guidance on, but because we were slightly removed in core.

And this was in the days when it was in office and you could ask someone a question. We just had to figure some elements out of ourselves. And that helped kind of up level me in terms of the, the tooling and how it actually worked. It wasn't just press a button and it spits at the number. And then from using Alteryx, I really, really enjoyed it 'cause I can't code, but I can understand the numbers and see what the transformations are doing along the way.

Within in 2020, the finance function in cork was mid redundant and had a cold hard look at what I was doing day to day, what did I enjoy, what did I not enjoy as much? And the Alteryx piece and the analytics element was a massive part of it. So. I wasn't quite sure what I was gonna do next, but I definitely wanted Alteryx to be at the center of it, so I looked for something in the analytic space to leverage those skills.

[00:03:06] Megan Dibble: That's great. We definitely hear on the podcast from people who have broken Excel or we've just hit their limit with Excel. And it's amazing how much more you can do in designer still without having to code. I think it's really empowering to so many people who might not be a data scientist or a trained data analyst, but it's just, it's super exciting to talk to all these people who have changed career paths because of Alteryx.

You also mentioned earlier when we were talking about this, that you liked the ability to build repeatable processes in Alteryx. Could you touch on that a little bit? 

[00:03:44] Donal Bourke: Yeah, sure. The role that I ended up doing after finance was in sourcing analytics, and this is where the repeatable process piece really came to light because I was only in the job a month or two when one of the team was out sick and I was asked to run the reporting cycle.

And for context, in sourcing analytics, what we do is we review the company's spend and we try and maximize the value for the business from from the dollars they're spending. So we're looking at all their. pos, there are requisitions, all, all that, that spend information trying to deliver insights. And when I looked at the process, I was there, I saw a lot of Excel sheets, a lot of pivot tables, and a lot of manual in entry and kind of having to get your hand hands on the numbers.

So I downloaded my 30 day free trial of designer and I put the, the monthly process into that. So then what it did was unknowns to myself. I was building the proof of concept four. The investment in the license because the business or, or BU hadn't been using that. So we used that then as the frame to set a central hub of data that we could enrich further, drive further insights from as well.

So it, it was really quite comforting in a way to have a tool that I'd used before and build a different use case for it and pushing that across. Also then I got the opportunity to use more tableau. So there are some of the visualization on top of it. 'cause Alteryx, you can either go deep in the machine learning and the coding and the python element of it, or you can go more towards the end user and try and tell a story and, and paint a pretty picture with all these ETL hard graph that you've done underneath.

So we built some cool Tableau dashboards on top to help drive the insight. So it's pretty cool. Use case. 

[00:05:29] Megan Dibble: Very cool, and I love that you did that first use case just in this 30 day trial that it was such a quick time to value for you. It's really fun. Yeah. So I'd love if you could tell us about the field that you're in now in FinOps or financial operations.

So what is financial operations and how did you shift into that from having more of an accounting background? 

[00:05:51] Donal Bourke: FinOps or, or financial operations for context, everything in the IT space is ops. Um, so it's SecOps, DevOps, dev, SecOps. So OPS is just the finance portion of it. Trying to wrangle an element of the IT spend.

The kind of textbook definition is that it's the operational framework and cultural practice to maximize your cloud bill and your investment in cloud. But, but it's just about every dollar you spend on the cloud, you wanna get the most value out of that. And because FinOps bys nature, it means that a lot of the responsibility is decentralized.

So historically for for your infrastructure, you would've had a CapEx budget. You would've want to buy a bunch of servers for your data center. So it'll cost a couple hundred grand. So you'd have to raise a CapEx requirement. That would go through all the finance approvals up to the CFO to sign off. You get your servers and you put 'em in your data center.

Now, in this new world of cloud, you've got your engineers and your architects writing lines of code, and they could be based anywhere. They could be writing anything. That's where FinOps comes in. It's trying to bring visibility and accountability to the edge of the organization so that the engineers and architects, when they're tasked with making sure stuff runs, it's kind of look and see, is it being done in the most optimal way?

You don't just want to give them a list of things to do or put them on a naughty list. You wanna understand why they've built something in such a way, and is there maybe a way to do it in a more, more effective manner? Also the, the beauty of kind of ops is there's a lot of stakeholder engagement in it compared to accounting.

You're locked in a dark room and you do your month end or your quarter end and closes and your poster journals, and you don't hear anymore about it and it's retroactive. So this is what we did last month, what we did last quarter. But with ops, it's more forward looking. So you're chatting to engineers and architects and you're like, what's in your dev or your staging environments?

What are the applications coming down the line? You're getting a real understanding of trying to influence how those building blocks are put in place down the line. So it's pretty cool to try to influence forward as opposed to to retrospective. The biggest thing with FinOps is when you think of a financing and analytics, from a HR perspective, you're generally in one vertical, so everyone's in the bands according to that vertical.

Whereas in FinOps, you've managed to break across into that it vertical. Whereas the band or whatever you like to call it might be the same or lower. The pay is actually better. So I always say I don't, I don't care what they call me, it's what comes through the pitching at the of the month. So you're leveraging a lot of the skills that that people in analytics and in accounting and in finance have.

But just having that in that IT sphere, so it is, is pretty cool. 

[00:08:39] Megan Dibble: That's very cool and it definitely caught my attention when you had first reached out that you said you were able to double your salary within four years of making the switch. 

[00:08:48] Donal Bourke: Yeah, and plus doing something I like. I enjoyed accounting and don't, don't get me wrong, it's an noble profession.

Someone has to balance the books. I enjoy this so much more because of you can see the material and impact that it's having on the business, and you're building that trust and that relationship as opposed to being what's my number at the end of the month. So it's, it's a different collaboration and like I say, the fact that it pays better, that, that's why it even show up at the end of the day.

[00:09:14] Megan Dibble: Yeah, definitely. And what you were saying about the field that you're really helping the company get the most value out of the software that you're helping optimize things. I know that's a huge thing for companies right now. Everybody's reevaluating their software spend. We're just in a season where that's very important.

So seems like just an even more important field to me, and it's interesting to hear more about it. I'm curious what you would say you enjoy most about it. 

[00:09:39] Donal Bourke: I love the fact that it's evolving all the time. For example, some of the services like the Kubernetes and the serverless piece within VIN Cloud computing is only around four or five years with this explosion of AI and these NVIDIA chips and the services that will come out around them.

While everyone's rushing to build the application, there'll always be a case for the people to report on what's going on in terms of how much is this stuff? How much did this AI experiment cost us? Are we gonna run it all the time? Are we going to reduce our cadence of, of that running? So trying to put the intelligence and the analytics around what's happening here.

So with that evolving mentality, it, it is really rewarding. And also the fact that. FinOps discipline is only relatively new with, I think the foundation was established maybe five or six years ago. So because a lot of people are figuring this stuff out themselves, there's an element of everyone kind of fumbling along together and sharing best practice.

It's a rising tide lifts all boats. Mentality. Whereas when you think about accounting and finance, the IAS standards, FRS, all the, all these sort of things have been around since near the dawn of time. It's an entirely different framework for the people working there as well. It's real growth mindset and that mentality, and you always have to be keeping up to date with, with trends and what's going on, and having that curiosity is, 

[00:11:02] Megan Dibble: yeah, 

[00:11:02] Donal Bourke: is a key part of it all.

[00:11:04] Megan Dibble: I love that about analytics as well, that it's changing. There's always something new to learn. I find it super interesting. So let's shift into how are you using Alteryx for cloud optimization for your customers now? 

[00:11:16] Donal Bourke: Yes, I've, I've been lucky enough to prove the value of Alteryx within this business as well.

Unfortunately enough, someone else on my team has heard of it before. I'm not pitching to a, to an entirely new audience. So the two of us have like co-development sessions where we look at two kind of tracks. One of them is the internal impact. So within our tooling that we've got, for me as a cost specialist and the my other peers that support customers.

How can we make our internal tooling more effective to deliver more value to our customers quicker? So a lot of our tooling might bring data to a point, and what we're trying to do then is that last mile data delivery. So if you think about your Amazon truck that pulls out, so it gets to the depo will be so far, but getting it to your door.

Is where the real value is in that instant benefit. That's what we're trying to deliver. And then roll it out at scale so that everyone else in the team delivers from that quicker type of value. And what we do then is we can build out those proof of concepts, feed it back to our internal development team.

Who evolved the tooling to give a better end product to the rest of the team. So that's one piece which I really like that process improvement, streamlining of what we're doing day to day. The, the second element then is the external impact. So it's looking at the cloud bill and the information that's available there and trying to develop better reporting.

So that we can demonstrate to our customers the value of our service, and also have more strategic conversations with them. Because the cloud is a concept. Anytime anyone spins up a machine is what they call it. I don't know how to spin up a machine or, or what it technically it involves, I think it's like some person writing code somewhere.

Sure. But every machine generate some wizard over there. Y yeah. Someone way, way smarter than me writes, writes, sir, a couple of lines and it generates a billing line for every hour. There's 730 hours in a billing, and if you've got a thousand machines, the source data is thousands of lines long and millions of lines wide.

So it's a lot to get your hands around. Altrix has good connectivity to like the S3 buckets, which is the storage book of where this data is held. So we're, we're looking at that information, trying to pull out some insights to have those strategic conversations with customers, and therefore that makes.

Job easier when we're trying to optimize what they're doing. 'cause we're looking at that data from that granular, granular level. 

[00:13:45] Megan Dibble: Yeah, that sounds like a massive volume of data for sure. 

[00:13:48] Donal Bourke: That's, that's per customer per month as well. E, even Alteryx, you can see it churning and spinning trying to do some of this stuff.

There's a lot there. 

[00:13:55] Megan Dibble: Sure. Yeah. Don't even think about trying to use Excel for that. 

[00:13:58] Donal Bourke: No. 

[00:13:59] Megan Dibble: Just quit right away. 

[00:14:00] Donal Bourke: Yeah. Eventually you'd like everything. You need to be able to bring it down and condense it down into a pivot table. But it's a long journey from right, from farm to fork all the way down here.

[00:14:11] Megan Dibble: That's great. Okay. Now we're truly shifting gears to something that you're passionate about. You create YouTube videos, so I'd love to hear about how you got started with that and like what your vision is for creating content. 

[00:14:25] Donal Bourke: I've always had, uh, I dunno if entrepreneurial spirit or hair-brained idea vein is, is the way to way to think about it.

Like at one point I wanted to start a company making scones, Donnie Scones. I was looking at doing log cabins in our, on our farm at home. But there's a lot of barriers to entry to doing something like that. So whereas YouTube is like, we're already on Zoom or Riverside or whatever it is, and so there, there's no real barrier to getting started and the content, because FinOps is so new.

When I stumbled across this was like. I wish I'd known about this years ago. I would've started on this path. So I'm trying to create content, aim that people like myself five years ago are an accountant or working in finance or analytics and they're not quite sure they want to use numbers, but they haven't found their sweet spot to see where they can drive most value.

So that's, that's I'm aim this, that, and the YouTube videos and poster button Spotify as well. Not nearly as polished as something like this, but all, all I'm aiming to do is get slightly better with every upload. So that iterative improvement and, and FinOps is quite the same. No one has it all figured out 'cause it's always changing.

So you're just improving and evolving every single time and that, that's what we aim to do with YouTube. 

[00:15:40] Megan Dibble: And I think for listeners out there that are looking to get started in some way creating content. About what they do professionally. You know, creating content for like yourself five years ago is such a great place to start and can be so helpful to people who are just starting out.

And sometimes you don't even realize, sometimes people will leave a comment and say, wow, this is great, or I hadn't heard of this. And then sometimes you hear about it like a year later. Sometimes you're never hear, but. I think it's really cool that you're able to share your experience and help others find that same path.

And you mentioned that you're passionate about helping others make the career switch that you did. So I think that's really cool 

[00:16:22] Donal Bourke: because it is such a growing field and the migration to cloud. While there is some talk about repatriation, people moving data back off the cloud, back back on prem. There's still a masses of data there as well that needs to be paid for and that needs to be optimized.

And I suppose all this feeds into the, there's a discipline called Green Ops as well, which is around sustainability. So you're looking at the CO2 footprint of running all these machines. So the more people that are aware of it and practicing the discipline, the better architecture and infrastructure decisions that could be made and, and might make a global positive impact as well.

Information is power after all. 

[00:17:01] Megan Dibble: We'll definitely link some of your videos in our show notes so listeners can check it out. And just for on the show right now, what is some of your advice that you give to others looking to move into analytics, looking to make a similar switch as you, 

[00:17:15] Donal Bourke: it's all about really just getting started.

It's that mindset shift. So it's about finding a data problem within your business or, or something that you're struggling with yourself on a day to day. Why is this export taking so long? Where are these data fields coming from? Rather than accepting something as it is, maybe think put a lens on in terms of what can make my job more effective.

I always like to think you give the laziest man the hardest job or woman, and they'll find a way to do it quicker or more effectively. It's not necessarily shortcut because the end product is the same, but it's looking for those efficiencies. What I found really useful in terms of Alteryx specific was the weekly challenges within the community because I, like most people, I probably use a small corner of the tools that are available within Alteryx, and sometimes I feel like I'm using a sledgehammer to crack a walnut 'cause I'm like, there are all these amazing tools and capabilities that I'm not even nearly aware of.

The weekly challenges allows you to broaden your scope, which is a really good way of thinking about it, and it might bring more of those data problems into your purview. Solving the problem will be one element of it, but a very big piece of it, and some good advice I got was to be able to tell the story at the end of it.

So being able to visualize it or communicated in a concise, effective way is a really important skill because no one cares about all the data wrangling that you did to. Normalize your different data sets from different sources. Yep. They wanna know, so what, what does this actually tell me? There's, and I know you guys covered it a, a couple of weeks ago you did, did a storytelling kind of episode, which, which pointed at this, there's a really good book as well, storytelling with data or data depending on which side of the Atlantic you're on, which been really good.

It's quite a pretty book and you can just tap through it and find different recommendations on how to show what you're doing. If someone is looking to be more specific and break into maybe ops, the, the area that I'm in, the FinOps Foundation is an organization set up to kinda holds a framework around the discipline itself.

There's some really good resources on there to learn a bit more, and the information is a lot more articulate than I am. And there's also a, a recently launched free introduction to FinOps training course. So it would give someone an opportunity to just dip your toe. It'll take about an hour. You can pick a different perspective and one of them is finance or leadership or it.

To get that lens on what FinOps is about for the sake of an hour, an hour and a half, it's definitely worth checking out to see if it's something you wanna go further on and that it's about building up your practical experience within FinOps, like most people working in organization that use the cloud.

So it's just a case of finding that IT business partner or someone in the IT department and asking what cloud are we using? Do you have any idea of how much we're spending on that per month? Because chances are they're spending about 20 to 30% more than they properly should. And it's like anything but just having a little bit of knowledge, you can do a lot of damage.

So the low hanging fruit within FinOps is quite easy to attain. So by just getting those base pieces in place, you can start getting some savings on the board, which might. Free up some more of your time to look in that space. And you could craft your own FinOps role within your existing organization without having to do any sort of certification.

You're still working with the same people and you, you know, the business. So you have that context as well, which is very important. So yeah, the world is your oyster and if you go to your employer, they're paying you anyways. So we say I can maybe save us. Save us some money on your cloud bill. They're not going to say no.

[00:20:55] Megan Dibble: Definitely. Yeah. I love what you mentioned earlier about just finding the data problems that already exist at your current company, no matter what your role is, if you're not in that analytics field yet. That's how I got into data. I got my interest into data I was in. More of a manufacturing setting, but anytime some kind of data problem would pop up, I got really interested and I loved learning different technologies, learning SQL or Tableau.

And so I think that's an awesome piece of advice for people looking to break into data. You know, there's ways that you can make an impact with where you already are. And then, yeah, I appreciate you sharing a bunch of resources, a bunch of free resources for people to upskill and build that foundation.

[00:21:40] Donal Bourke: Because it's, you kind of have to kiss a few frogs before you find your own product. And yeah, maybe like the process improvement side, maybe you prefer the stakeholder engagement piece. And it's, it's just crafting that role and finding what sits with your skillset, so you'll always find a way. 

[00:21:56] Megan Dibble: Well, Donald, thank you so much for joining us today.

It was awesome to have you on our podcast. 

[00:22:00] Donal Bourke: Thank you so much, Megan. Really enjoyed it. 

[00:22:03] Megan Dibble: Thanks for listening to find a link to Donald's YouTube channel and other resources related to this episode. Head over to our show notes on See you next time.

This episode was produced by Megan Dibble (@MeganDibble), Mike Cusic (@mikecusic), and Matt Rotundo (@AlteryxMatt). Special thanks to @andyuttley for the theme music track, and @mikecusic for our album artwork.