Leonella and Edward Bass

SUMMARY KEYWORDS

data, sql, system, report, industrial, palo alto networks, talk, assets, people, work, cmms, good, legionella, industrial iot, programmers, run, professionals, pencil, years, changing

00:00

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01:04

Welcome to the Industrial Talk podcast with Scott Mackenzie. Scott is a passionate industry professional dedicated to transferring cutting-edge industry focused innovations and trends while highlighting the men and women who keep the world moving. So put on your hard hat, grab your work boots. And let's get

01:22

once again thank you very much for joining Industrial Talk and thank you for your continued support of a platform that is dedicated to industrial professionals all around the world. I say it all the time. You are bold, brave, you dare greatly. You are changing lives and therefore you are changing the world hang out with these individuals that are going to be on the podcast and you will be changing the world without a doubt. We are at a crew hunt insights it is in where we were in Tennessee someplace now we're in Nashville, Tennessee, at the Gaylord, which is an incredible did you guys get lost? Oh my god. Yes. That is if there's one thing you'll get lost here at the gala, but you're getting lost in a beautiful, beautiful location. All right, we have two in the seat. Leon, Ella VAs and Edward bass, they are with data efficiency solutions. Let's get cracking. Hi, Neil, it. Thanks so much. Thanks. Yeah, it just takes a little while. But that's all good. Good conference.

02:22

Yeah. So far. Good to see some people that I'm

02:27

Oh, yeah. For? Yeah. Have you seen people that you just only knew but from from zoom.

02:34

From zoom? Oh, no, actually, we haven't done a whole lot of zoom.

02:39

Well, I think you need to do that just because you need to be part of the Zoom crowd. Why wouldn't you be a part of the Zoom crowd? All right. For the listeners out there. We're gonna start with you. Legionella. Give us a little background of who you are.

02:52

Well, I'm from Venezuela, and I go a graduate of minors mechanical engineering in there. And I spent five years working on Jacobs Engineering. And then ever and I, my husband and I

03:13

both have the bass last name

03:16

the bass team. So we open a business these year and now we are a federal contract. Well, we love sequel we like a lot. The product we like someone to make this connection work with the system. Yeah, we are nerd biking and things like

03:36

that. Did you ever have an opportunity? Well, no. How long have you been in the country? Eight years, eight years. Then that does log a van or minivan still exist down in Venezuela.

03:49

Waiting like that?

03:51

Those are oil companies. Oh, goodness no. What about polar bear up here to reporting polar bear. Edward that's a tough act to follow. Give us a little background.

04:10

Well yeah, I actually I worked for maintenance connection for about just shy of eight years and I used to be the customer support person and I used to just do the first I just did the basic you know support helping them helping the customer and loved it and then they moved they rolled me into the reports which was more SQL oriented and just fell in love with it did after the first couple years I was just doing support and then the last last five I was just doing primarily SQL and reporting so I got to know that the back end and from the front to the back and love to help the people get the reports what they're trying to get out of the system. And then from there, Jacobs Engineering poached me for for the last five years, and and then we ended up opening up We're on business. And I was able to help help them do quite a bit with SQL.

05:05

So explain to the listeners what you're talking about. What does that mean? What? What's that service that is being provided?

05:13

Well, we do we do standardization for your data. We do migrations, we, we actually have this. Oh, yeah, it's, it's, it's super fun. Like, we know, we know, we know maintenance connection, like the back of our hands, like we were super good at it. And we're very good at mapping the fields over from one place to another and, and actually, we put in this place, we put in, actually asset condition condition assessments and full asset risk, which maintenance connection, they were doing it for the medical industry, but we actually found a way to do full condition of likely to failure and condition, consequence of failure and putting full risk inside of maintenance connection. And not there's not that many people that know it's possible. And even I'm supposed to be talking to people from maintenance connection about it, because we we've got something amazing. Amazing.

06:09

Okay, Legionella explained to us. I mean, take us through the process, let's say I come to you or knock on your door I what am I asking? What am I asking help with? What's my problem? Help me with that into my head. What is it? Wait

06:30

your data? You mean? Yeah. Well, I will have to see your system, and I will have to see the

06:36

data. So you go in, you're saying okay, what system do you have, okay, I've got this legacy system, whatever it might be. And then I have data over here, that's in a spread, whatever. So you have to see where where it resides?

06:48

Yes. We, we like to focus to in the standardization, what are the goals, and then guide you to get those goals achieved, right? We see where are opportunities of improvement, and advise you what you should do, and maybe offer you some products that could help you to find your goals.

07:17

So with that said, and I'm still I'm, maybe it's me, because I'm dance, which it is. What, what is the problem that I come to you for resolution? What am I what am I saying? And what am I saying, hey, what do I need? I got this system? What am I? What am I doing? Well,

07:38

it's really about finding out what what they're trying to get out of the system. So I

07:43

have to define that, let's say I want to get this data out. That is that sort of a use case where I would contact you or what

07:52

Yeah, yeah. Like, a lot of people they want like different KPIs, they, they, they want to start validating the the use of that data, while we're using the system, and we, you know, these these benchmarks, they're looking for certain benchmarks and, and we like to get in there and find out where the data points that they're looking for how they're using the system, and making sure that they are, they are actually getting the right parts of their data. And we actually, when we go in, and we look into their databases, we get to actually find out a lot more where they're using data. And sometimes we can, you know, give them ideas to add to what they're already looking for, you know, like the all of the stakeholders, they want to decide, you know, what we're trying to get to, you know,

08:46

are you are you system agnostic? Can you do this with any system,

08:51

there's absolutely, it's all, it's all. It's all based on SQL, the root is SQL. And we have all kinds of different versions of SQL. Now we got PL SQL, which is Oracle, we got t SQL, which is the Microsoft SQL, but it all goes down, it's a compiler dollar just talks down to SQL, but it's just really, it's just a different dialect, all of these different versions of SQL, it's just a different dialect. And all of these databases all run on SQL, a version of SQL. So no mastering SQL, it masters everything really with a database.

09:25

So normally, when I have a system, you know, I have a system, and that system has theoretically a coded dashboard. And I'm supposed to be able to see that, but I want to get more out of it. Is that what I'm asking? Am I saying hey, I got this dashboard, but I know that there's more data that I'm collecting. There's more information that I'm pulling, and I want to get more out of this is that where and then be able to realize the information in the data and then be able to do my data and Linux,

10:00

yes, we actually do QA QC to the data to, we verify that that is correct. We can do massive update. And is depending on it's looking for the client, and the most of the time is cost, everything is surrounding the cause. Right? So they want to know, the proactive cause the reactive cost, so yes, exactly. So because all the decisions that you're going to take is going to be depending of the proactive and reactive actions that they have in, in, in the production.

10:40

The, there's also the reality of, of just, I have multiple legacy systems, I have an ERP over here, I have an asset performance management system, I have the CRM, which never gets updated properly, whatever it I just got, I've got data everywhere. Can you normalize that? Can you bring it all together? And being able to do that?

11:01

Yes. And yeah, so we, we do a standardizations. And when we have like different systems, we try to get one feel from the system that is gonna match all the time with the other fields. So when you do a report, when they, you can actually match up those data from different systems, because there are people that are using different systems. They are using API or some time they are using API, but but there are so many, many factors, really, but yeah.

11:36

Many factors come up in in so many businesses with a legacy system here and a legacy system there. And then they just sort of pull it together. And oh, yeah, by the way, there's a spreadsheet over there that nobody ever wants to touch.

11:49

And that is why we are trying to come to all together like the assets because the main factor here are the assets in the CMMS, of course. So we want to know the cause and the cause in proactive reactive. So we want to know, all the data and the data be secure, and get the very accurate reports to for the client. Because sometimes they have report but they have to trust,

12:19

right, you have to trust it. I know, it would seem to me that it would only it's, it's great when it all works well. But you have to validate that because if that's not the case, then I don't trust the report, I'm not trusting with that data. And so

12:38

you know what, with a really good standardization and really good reporting, you, you can actually the things that are become untrustworthy, they really pop out, you know, when when you when you're running reports on a regular basis, and you have it set up to to in you have all of these data points set to work a certain way, when you run these reports, they you get huge spikes in some places. And that's also places where we come in and go, Hey, what happened? They want to know what happened here. And we we dive in, we can find out real fast with

13:09

SQL. Somebody just sort of pencil with it. But yeah, exactly.

13:13

We find a pencil and stuff all the time.

13:18

Sad, but it's a reality.

13:19

That's another thing too, because a lot of times the owners, the people running their CMMS, they'll say, Hey, I know my guys are pencil whipping in these departments. And that actually is also very helpful. I mean, sometimes we can find the pencil whipping without being told. But when we're told, then we can actually find some really good keys.

13:39

That's a tough, that's a that's a cultural thing. Right? And it's it deals with a system that maybe is difficult to navigate. I don't know, whatever the reason is, or there's just not a commitment to, you know, accurate accuracy. Yeah. How do we change that?

14:00

I think if we let people know, why, why is very important, because, you know, first of all, why are people pencil thing and pencil their pencils? Because they don't they don't think there's any valid reasons, doing value. Exactly. And maybe letting people know the value. You know, and maybe letting them have a voice. those end users are very important. They're the most important. They're the ones putting in the data, and, and having them to be able to have a voice to what is valuable. That I think that would also help too, because it's I don't know, it would bring more ownership. Really.

14:41

It would seem to me that if if, if I would nail down that data, make it accurate, and reveal that data in a way in a form that allows me to make better decisions quickly. It would just seem to me that'd be the way to go. So and is a must. Yeah, it's

15:02

a team effort to be you, you got to have everybody working together, everybody on the same path, really, because we can't, I mean, we're amazing at what we do. But we can't just come in and make it magic. You know, we need to have the pizza stakeholders involved, all the way all the way down to the people putting the who's ever putting in the data. Everybody needs to be a big team, and working together in order for us to get some really good quality. Because with quality data, we can start doing good predictions.

15:35

Do you also take on the role of data cleaning? Yeah, like scrubbing it? Looking at it? Oh, here it is. I've got it. What's, what's a typical rule of thumb? You go back since the beginning of time, or do you go back five years or three years? How far back do you go? And you try to clean that data? Right.

15:57

Particularly I like, oh, because I like to go there. Apple, with Apple, from the beginning to them. Yeah. Because how I know, oh, they will last five years. And now how we are doing now let's just update everything. Let's just do a standardization to everything that is me, particularly. And

16:21

this is a good dynamic that we have. Yes. Because I'm not always like that. Yeah. Because sometimes, you know, she'll be on that side. And I'm on the other side, like, no, no, because I because I do, it depends on this scenario, because I do feel like moments of time of change also shows Hey, I did this revision. So you know, it's funny, because her and I go back and forth, you know, sometimes that I'll be on that side, and she'll be on the other side. And like, Yeah, let's just clean it all up. And then I don't know, it's just depends. And we kind of argue that's heavy lifting. Yeah, it is heavy lifting. Yeah. But the great thing is with SQL, you, you're actually able to run loops, when you're cleaning up the same data, and you get the same pattern. And that's what's so cool about SQL, you can actually run a loop and you can step away from it. So some of the times, it's really doesn't, it does take a long time, I

17:12

was just gonna say if I can just,

17:14

you can write the code. And because we're kind of like in a little niche here, because we're really we're programmers, really, but what we've done is we've decided to not go into the programming world, which makes us accessible, whereas the programmers are really not accessible to some of these people using these products. You know, so we're staying right here. And we're like, Hey, we're able to do this stuff. And we can do with just as crazy good stuff, as the programmers can do. You know,

17:41

do you have how long would it take to go all the way back? What's the longest it's taken for you to scrub the data? Well, um, when you don't have to name the client or anything like that, it was

17:55

not the first thing they do is map map everything while I'm going from to like, what I have and where I go and write where I want to update to. And then I just grind this grip and leave it there. Leave it there and just do every other stuff. And then okay, this finish. Okay, I already finished. I don't know. We even have done like, I don't know, 100 pounds? For girls. Yeah. Yeah.

18:23

How long did it take you? Well, is

18:26

this group that takes me time can take me for being sure and testing on the stuff I don't know, five hours to do this grip, and then just leave their system work by itself. That's a loop loop this will

18:41

take for the computer to process

18:44

day, depending sometimes days.

18:47

Well, I was just gonna say no.

18:49

Yeah, it could be a weekend. I live in Florida weekend. And then taking all the time how many our lives and sometimes

18:56

for free, great refresh, refresh, refresh? Well, we

18:59

don't have to do refresh. It's pretty cool. Because a lot of times we'll like, you know, when the heavier ones because, you know, this is a working. This is in production. And a lot of people really don't like messing with production. So we'll do it outside hours. Yeah, yeah, we'll do it outside hours on the weekends or something like that, whatever, whenever they're not working in it. So it doesn't bog down the system. But

19:20

how do you QC it? Oh,

19:22

it's very easy. It's, we can pull it out and put it in an Excel do VLOOKUP concatenate all the columns. Compare it to each other? Oh, it's it's we've got some great quick systems now. Awesome. It's a lot of fun. It's super nerdy.

19:37

It's just like, oh, my gosh, V look. Oh, yeah, that brings but I used to like spreadsheets. Well,

19:43

you know about primary key. Oh, yeah. Yeah. We make primary keys out of like 10 columns.

19:53

geeky, geeky, geeky. Lunella. How do they get a hold of you? But they want to talk to you and they say hey, she stalking my dog.

20:01

Oh, just well, email me or to Lunella buzz that

20:12

helps build LLC

20:14

that. Yeah. Oh, my phone number 661-593-6768 Good work.

20:21

Yeah, but how do we get a hold of Edward bass at data E S? llc.com. Our website's data es llc.com. My number 615-938-6767. It's certainly one number. That's

20:34

right. I like the fact that you got that URL.

20:37

Yeah, it's pretty cool, right? That's pretty good. We're trying to stay high tech.

20:44

Oh, good. Well, you guys were absolutely wonderful. Thank you very much for saying yes. And being on the podcast. Thank you so much. All right, listeners, we're gonna wrap it up on the other side, we're gonna have all the contact information for Team data efficiency solutions out on Industrial Talk. So if you're not, you need them. You need these Sherpas to help you with your data? Yes, I agree. They're there. They're Industrial Talk approved. All right. We're gonna wrap it up on the inside. Stay tuned, we will be right back. You're listening to the Industrial Talk Podcast Network.

21:21

You need to reach out to these two incredible professionals, Leo nella, as well as Edward, both last name vas. So don't forget about that go out to Industrial Talk. Find out more data analytics, there's gold in the data there is you need to find great Sherpas like these two professionals to help you on that journey. It is a must. Because there is there's gold there, then we want you to succeed. We want you to make a big splash data. Right there goes to reach out. Just real talk. All right. Again, this is a platform for you. You need to be a part of this platform. It is specifically to help, collaborate, educate and innovate with other like minded professionals. get that message out. Your message needs to be told it just does. So get out to Industrial Talk and find out more, click on a button or two. All right, be bold, be brave dare greatly hang out with these two professionals changed the world. We're gonna have another great conversation coming from this event shortly.