The Soccer Field Data Base

Cool Technology and the Intelligent Enterprise 
The Soccer Field Data Base 

Hello again! As always, I appreciate your reading my blog. If you’re just tuning in, you might want to start at the beginning. Go ahead. We’ll all be here when you catch up. And this investigation about cool technology is heating upStay curious and stay with me. Let’s see where this takes us. 

As a born and raised Chicagoan, the closer I get to the Wisconsin state line, the more anxious I getYeah, I like beer, brats, and cheese. But I like it imported. As far as I’m concerned, the Linden L stop in Wilmette is as far north as any true Chicagoan needs to go.  
I wanted to interview Rita Davies from Discover Financial for this blog, but when I found out they’re located in Riverwoods  halfway to Dairyland  I nearly gave up. 
So I gave her a call, and even though Rita was crazy busy, she offered to do a phone interviewI was tempted, but I know from experience that I can get a better read on a people when we meet in person 
Then suddenly she remembered her twin boys were having a soccer match in Skokie, and she could meet me at the field. This was too good to pass up. A genuine suburban soccer mom talking about data intelligence during her middle-schoolers soccer match? Yep, that’s exactly the kind of interview I like to do. 
So, I took the Skokie swift to Dempster and walked about a half mile to the field. While there was a cluster of soccer moms (and quite a few dads too), she was easy to spot because of the twin boys. I approached her minivan and introduced myself, and she seemed glad I could make it. She wore a jogging suit, but as she pulled her hair back into a ponytail, I could tell from the elegant earrings that she had rushed there from work. She introduced me to her twin cherubs, Lucas and Jacob, but I knew Id never be able to tell them apart. 
“It’s easy,” she insisted, “Jacob never pulls up his knee socks.” It was her turn to bring the juice boxes, so I helped unload the cooler and the folding chairs and we headed for the field. “So, you want to know about the exciting world of data intelligence?” she asked. 
I’m told you’re the expert.” 
Maybe. I live two lives. One minute I’m sorting through terabytes of data and the next ... Jacob, tie your shoe. Your shoe! Both shoes! So, what do you want to know?” 
“Well, Rajesh told me a lot about Big Data and theoretically, all of this information is supposed to make our lives simpler, but it seems to me that simplifying things is very difficult.” 
Yeah, but we’re getting better at it  we have it down to a science. 
“Okay, how does it work?” 
The first thing you need is a place to store your data  a database. Let’s suppose this park is a database and everything in it is a piece of data. The trees are data, the trash cans are data, the parents are data, the kids are data, everything is data. The first thing a data scientist needs to do is sort it all out. The cars are in the parking lot, the parents are on the sidelines, the kids are on the bench, and so on. Good so far?” 
“Yeah,” I said choosing the perfect spot for our chairs, “so far so good.” 
“Next you have to determine whats useful and what isn’t. You see the guys over there playing basketball? 
Yeah.” 
They have nothing to do with the soccer match, so we ignore themthey’re irrelevant data.” Then she cupped her hands to her mouth and yelled, “Barb, tell Coach Moffitt that Eric is still sick.” Then quietly she says, “Damn anti-vaxxers will kill us all. Eric would be missing data. Sometimes you have to find the missing data or extrapolate or something to make up for it. Then you have to determine the quality of the data. Some kids are bigger, and some kids are faster … No hitting, Lucas! No hands in soccer! You have to merge and purge your data. Some kids are on the bench and some are on the field. 
Now you start making rules about the data. No more than 11 on the field. One is the goalie. Maybe you start with three midfielders and later go with four. Too many on the field, you break a rule. Not enough on the field, you have to add more. And you have to watch for data breaches and data theft. A dog runs on the field or some kid like Jacob starts daydreaming and wanders off. Seriously, he does that. In the middle of the game he wanders away. And not just onceit’s like all the time. So, you have to constantly monitor the data and set benchmarks. You have to watch the clock, keep track of the penalties, and keep the score. Then you have to represent all of that data in an understandable format. It’s a report, or a graph, or a dashboard, or a spreadsheet, or a score card. By the way, who’s got the scorecard tonight? David? David can’t keep score; no one can read his writing.” Then back to me, “Seriously, would you have a doctor fill out a score sheet? Really? Anyway, thats a massive oversimplification of what data intelligence is all about.” 
“You’re kind of intense, I said. 
“Occupational hazardEverything looks like data to me. I love the job. It’s a great challenge. I get to use my brain, but it’s hard to turn it off sometimes.” 
At that point I felt a little bad. This was supposed to be quality time with the kids, and I was making her think more about work. I had to admire her thoughIt may be a cliché, but she’s the quintessential multitasking super mom, and that’s not easy. Nonetheless, I decided it might be best to let her focus on the game for a while, so I sat quietly and watched. 
Finally, she turned to me and said, “No kids?” 
“You can tell?” 
“Pretty much. You know nothing about soccer?” 
“I know as much about soccer as I do ballet, and iain’t much. Looks like a lot of running around to me.”  
See, if I could really apply data intelligence to it, it would all make perfect sense to you. 
“Yeah, but it seems to me all of those rules and sorting just make it more complicated. 
Yeah, but the idea is to create a predictable routine system that will make all of the complexity simple. Think about the credit card business. Suppose you buy something at Walmart and charge it to a credit card. We have to take that information and bill Walmart a processing fee. Then we have to take all of the other Walmart purchases and direct them to the individual accounts of the customers. Then for each customer, we have to gather all of the information about all of the purchases they’ve made at all of the merchants. Then we have to calculate the interest and fees, and we have to create bills for all of the customers and all of the merchants. Then we have to settle that up with the banks and put that on the next statement. 
“So, it’s complicated.” 
“But as long as we have a routine predictable system in place, it’s reasonably simple in the end. In factwe even begin to anticipate things that aren’t routine like corporate reporting, foreign currency, taxes, defaults, returns, bankruptcies, and on and on. For example, you know what happens when people die?” 
“They go to heaven?” 
“No. 
“Well, some do.” 
“No, I mean do you have any idea what credit card companies do if someone dies with a balance on their card? We have a system for that.” 
“I’m not allowed to talk about that.” 
“What do you mean?” 
“I told Rajesh I wouldn’t talk to you about dead people or time travelers. 
Dead people or time travelers?” 
“Well, it’s more like historical figures and time travel.” 
Oh ... my sister-in-law works at the Bristol Renaissance FaireShe dresses up in a corset and throws herself in a mud pit or something. Is that what you mean? 
“She mud-wrestles in a corset? Well, that sounds challenging.” 
“Yeah. You into role play? Have you been to the Ren Faire? 
NoI’m not into that. Besides, it’s in Wisconsin and don’t do Wisconsin. Anyway, just have a friend who does this great podcast about this interesting guy she met. And who knows, he might be an escapee from the Ren Faire. That would make total sense. I think he’s kind of weird, but you have to listen the podcast to know what I’m talking about. 
Right about then the clock ran out and the game was over. I have no idea who won. The parents began to chat, and I helped put the chairs back in the van. I’d planned to take the kids to Oberweis for ice cream, but Jacob had wandered off again and by the time he was found it was getting late.  
I thanked Rita for her time and information, and she said it was fun as she made sure the kids were buckled in. “I’m late. Gotta go,” she said out of the van window. Then as she pulled outI noticed a bumper sticker on the van. It was da Vinci’s Vitruvian Man againAn ad for the Ren Faire perhaps? It was very weird that it kept popping up. 
As I walked back toward the L, I wondered if Kay goes to the Ren Faire, and if she does, had she ever been mud-wrestling in a corset? I must ask her that. In my next blog, I’ll tell you about the fascinating guy I met on my trip home from the soccer match. In the meantime, if you want to hear more about her time-travelling friend, have a listen to Charlotte’s show on Apple Podcast. 

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Tony 
Blogger Extraordinaire  

DISCLAIMER: The Searching for Salaì podcast and the “Cool Technology and the Intelligent Enterprise” blog series are works of fiction. Names, characters, businesses, places, events, locales, and incidents are either the products of the author’s imagination or used in a fictitious manner. Any resemblance to actual persons, living or dead, or actual events is purely coincidental. 


[DESCRIPTION] 
Tony discovers that data intelligence provides clarity and critical context for innovative decisioning making for both business leaders and the everyday man. 

[KEYWORDS] 
SAP Leonardo podcast, Innovation, Digital Transformation, Intelligent Enterprise, Analytics, Big Data, Blockchain, The Cloud, Design Thinking, The Internet of Things (IoT), Machine Learning, Data Intelligence, Digital Renaissance, Leonardo da Vinci, Searching for Salaì, Cool Technology

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