Some Professors put together IKEA-inspired instructional booklets for their algorithms and data-structures lectures. The idea was to make easy-to-understand explanations by removing words, and only using images. Ideally, this would allow them to be understood regardless of their native language or culture.
This is a pretty cool idea, or at least I thought so. My youngest son said, "I don't particularly understand IKEA directions or algorithms .... so this is basically the worst of both worlds for me." Finally, we agree about something!
Hopefully, you find it helpful. If not, there's always Wikipedia.
Data is the fastest-growing commodity, and is today’s “wild west” and the battlefield of today’s tech titans. We talk about AI as this gold rush, but data is the underpinning of it all.
A staggering 328.77 million terabytes of data are created daily, which means around 120 zettabytes of data will be generated this year.
Rapid growth means little time to create adequate rules. Everyone’s jumping to own more data than the next and to protect that data from prying eyes.
As a great example of this, I often warn people to keep their intellectual property off of ChatGPT or other hosted language models.
I also see it trading, but it’s pervasive in every industry and our personal lives as well.
Collecting basic data and using basic analytics used to be enough ... but not anymore. The game is changing.
For example, traders used to focus on price data ... but there has been an influx of firms using alternative data sets and extraordinary hardware and software investments to find an edge. If you’re using the same data sources as your competitors and competing on the same set of beliefs, it’s hard to find a sustainable edge.
Understanding the game others are playing (and the rules of that game) is important. However, that’s only table stakes.
Figuring out where you can find extra insight, or where you can make the invisible visible, creates a moat between you and your competition and lets you play your own game.
Here is a quick high-level video about Data as fuel for your business. Check it out.
It is interesting to think about what’s driving the new world (of trading, technology, AI, etc.), which often involves identifying what drove the old world.
History has a way of repeating itself. Even when it doesn’t repeat itself, it often rhymes.
With that said, the key to unlocking the pathway to the new world often comes from a new or alternative data set that lets you approach the problem, challenge, or opportunity from a different perspective.
Before e-mails, fax machines were amazing. Before cars, people were happy with horses and buggies.
These comparisons help explain the importance of data in today’s new world economics.
Petroleum has played a pivotal role in human advancement since the Industrial Revolution. It fueled (and still fuels) our creativity, technology advancements, and a variety of derivative byproducts. There are direct competitors to fossil fuels that are gaining steam, but I think it’s more interesting to compare petroleum to data due to their parallels in effect on innovation.
Pumping crude oil out of the ground and transforming it into a finished product is not a simple process. Yet, it is relatively easy for someone to understand the process at a high level. You have to locate a reservoir, drill, capture the resource, and then refine it to the desired product – heating oil, gasoline, asphalt, plastics, etc.
The same is true for data.
You've got to figure out what data you might have, how it might be useful, you have to figure out how to refine it, clean it, fix it, curate it, transform it into something useful, and then how to deliver it to the people that need it in their business. And even if you've done this, you then have to make people aware that it's there, that it's changing, or how they might use it. For people who do it well, it's an incredible edge. – Howard Getson
In a sense, data fuels the information economy much like oil fuels the industrial economy. The amount of power someone has can be correlated to their control of and access to these resources. Likewise, things that diminish or constrain access or use of these resources can lead to extreme consequences.
Why Data Is Better Than Oil
The analogy works, but it’s just that, an analogy, and the more you analyze it, the more it falls apart. Unlike the finite resource that is oil, data is all around us and increasing at an exponential rate, so the game is a little different:
Data is a renewable resource. It’s durable, it’s reusable, and it’s being produced faster than we can process it.
Because it’s not a scarce resource, there’s no urge to hoard it – you can use it, transform it, and share it knowing that it won’t diminish.
Data becomes more valuable the more you use it.
As the world’s oil reserves dwindle, and renewable resources grow in popularity and effectiveness, the relative value of oil drops. It’s unlikely that will happen to data.
Also, while data transport is important, it’s not expensive the way oil is. It can be transported and replicated at light speed.
Using alternative data gives traders an advantage, but it doesn’t always have to be confidential or hard-to-find information. Traders now have access to vast amounts of structured and unstructured data. A significant source that many overlook is the data produced through their own process or the metadata from their own trades or transactions.
In the very near future, I expect these systems to be able to go out and search for different sources of information. It's almost like the algorithm becomes an omnivore. Instead of simply looking at market data or transactional data, or even metadata, it starts to look for connections or feedback loops that are profitable in sources of data that the human would never have thought of. – Howard Getson
In a word of caution, there are two common mistakes people make when making data-driven decisions. First, people often become slaves to the data, losing focus on the bigger picture. It’s the same mistake people make with AI. Both are tools, not the end goal. Second, even the most insightful data can’t predict black swans. It’s important to exercise caution. Prepare for the unexpected.
The future of data is bright, but it’s also littered with potential challenges. Privacy concerns and data misuse are hot-button topics, as are fake news and the ability of systems to generate misleading data. In addition, as we gain access to more data, our ability to separate signal from noise becomes more important.
I think one of the biggest problems facing our youth - and really all of us - is how much information is thrust at us every waking moment of the day. No previous generation has had this much access to data. As a result, many are actually less informed than in the past. Soundbites become the entire news story, and nuance gets lost in the echo chambers.
The question becomes, how do you capitalize on data without becoming a victim of it?
I love statistics. But I also recognize how easy it is to be tricked by data.
Here is an example illustrating how factually accurate statistics can be misleading without proper context.
Take a quick look at this chart showing Robotics funding in July 2023.
If you look at that chart, you might conclude that Pittsburgh is a Mecca of innovation in robotics. Carnegie Mellon is there. That makes sense, right?
However, there's an immediate red flag ... it's only for the month of July 2023.
So the question becomes ... why?
Turns out, that entire number is essentially the result of a single check to Stack AV to recapitulate what was Argo. Argo is a Ford and VW-backed autonomous vehicle startup, and Stack AV is the founders' new self-driving startup.
One significant move skewed the scale so strongly that it trumped major countries' expenditures that month.
There's often an issue about not having enough data to be statistically significant. Another common issue is confusing coincidence with causality.
This isn't meant to undermine the effect of one data point on a chart. For example, think about Taylor Swift's impact on the economy. Taylor's Eras Tour has already netted more than $100M but also reportedly has had a $5B impact on the economy.
Cincinnati reported that Taylor Swift's Concert Tour brought $90M to their city in two days. Her 60,000 attendees pushed the city's hotels to 98% occupancy rates. Beyond that, her concert-goers also consumed the city's restaurants, bars, tourism, and retail.
Here is a different example of accurate data leading to an unusual conclusion, At a Genius Network meeting this week, the creator of OsteoStrong and the X3 bar spoke about people's misconceptions about fitness and workouts. One point, in particular, caught my attention. He claimed that most people only get stronger as a direct result of their workouts about ten times in their lives. This isn't true of competitive athletes or weightlifters - but the average gym goer. Why? His logic was you only get stronger when you take your muscle to failure, past its previous limits. Most people rarely work out to exhaustion and don't keep track of their best. They often stop one rep - or even half a rep - before there's a meaningful improvement.
A good lesson for life.
As entrepreneurs, we've all seen people get the "one big break" or the "one domino" that led to success. The goal is often to be good enough that you only have to get lucky once.
While one data point can ruin a statistic, it can also change your life. The power of an inflection point.
Figuring out how to leverage new capabilities to achieve what you want is a master skill. It is a big part of what I do. Consequently, many of my conversations revolve around new technologies and how to utilize them. Likewise, I frequently write about these types of topics in blog posts. However, I often incorporate these discussions as brief segments at the conclusion of articles on broader subjects or specific technologies.
Recently, I created a video that consolidates many of my high-level thoughts about this. Take a look.
Adapting To New Technologies
The future is scary to people who have gotten comfortable in the present. They hope the future looks like the past because, if that happens, they already have it solved.
But that's not typically how life happens.
I often say, "Standing still is moving backward," and "You're either growing or dying."
So, when I hear people pushing back against new technologies, I cringe a little.
Smart people find a way to take advantage of promising new technologies rather than avoid them.
To use a surfing metaphor, it is easier (and more fun) to ride a wave than it is to resist it.
A skilled surfer doesn't try to catch every wave. Likewise, knowing you want or need to ride doesn't mean you should blindly do it. It is OK to skip a smaller wave to ride a bigger one (or to wait for a smarter or safer starting point).
When adapting to new technologies, I think there's a 4-step model you should follow.
Improve
Innovate
Redefine
Transform
It's almost like Maslow's hierarchy of needs ... you have to deal with things like food and shelter before you can deal with affiliation or self-actualization.
The Improve phase is the most important because this is when you take what you already do and make it better. Doing this first increases productivity and revenue in your business and buys time and space for you to focus on what comes next. It's also a way to show that you're making progress in the right direction, increasing capabilities, and building confidence (which is the fuel you need to continue making progress).
Next, many try and jump straight to transformation ... but that's a mistake.
Transform is the big hairy, audacious goal that you want to make possible. It's the mountain top you're trying to climb. It's helpful to know what that is. But, when trying to climb the mountain, you still have to take the steps in front of you.
The first step on the mountain is to Innovate. It's about what you could do, and what you should do – instead of what you're already doing.
Redefine is where you start climbing the mountain and adding new capabilities to your arsenal. You're now at a stage where you can imagine a bigger future and grow your vision to match your new capabilities. In a sense, you're playing the same game, but at a different level and with different expectations.
When you finally make it to Transform, you are playing a new game (often on a different playing field) and you're likely influencing not just your company but other companies. At this point, it's common for former competitors to come to you with ideas and money, looking to collaborate.
Another key mistake entrepreneurs make is they pivot to something completely new. When you're charting a path up a new mountain, you will find unstable ground or insurmountable peaks. At that point, many people give up and look for something new. They start wandering in different directions. That's a lot of wasted movement.
My rule at Capitalogix is "This or something better." When we reach a roadblock, we're allowed to go around it, but only if it's an improvement on our current goals.
This framework is the underpinning of two other frameworks I've shared before. In the spirit of getting it all in one place, I want to share those as well.
Understanding human behavior and what stays the same is the secret to technology adoption at scale - because it's not the best technology that wins, it's the most popular ... and you can "win the game" with fantastic usage of unadopted technology. Earlier, I mentioned you don't have to ride every wave. You just have to skillfully ride the waves you choose. This framework is meant to help you do that. It helps you turn thoughts into things and explains how ideas scale with respect to capabilities, audience, and monetization.
While the Technology Adoption Model Framework stages are important, the ultimate takeaway is that you don't have to predict what's coming, only how human nature works in response to the capabilities in front of them.
It's a bit cliche, but to paraphrase Wayne Gretzky, you have to skate to where you think the puck will be (or, at least, lean in the right direction).
Desire fuels commerce. As money fuels progress, the desire grows ... and so does the money funding that path. As such, the path forward is relatively easy to imagine.
Each stage is really about the opportunity to scale desire and adoption.
It isn't really about building the technology. Instead, it is about supporting the desire.
If you understand what is coming, you don't have to build it, but you can figure out where you want to build something that will make that more likely or benefit from it.
This model is fractal. It works on many levels of magnification or iteration. What first looks like a product is later seen as a prototype for something bigger.
For example, as a Product transforms into a Platform, it becomes almost like an industry of its own. Consequently, it becomes the seed for a new set of Capabilities, Prototypes, and Products.
SpaceX's goal to get to Mars feels like their North Star right now ... but once it's achieved, it becomes the foundation for new goals.
This Framework helps you validate capabilities before sinking resources into them.
In the video, I walk you through several examples of companies, their innovations, and how they fit into each stage. I even used Capitalogix as an example.
I'm also attaching a fillable PDF of the form we used so that you can run through this with your business as well.
Both of the above frameworks are high-level approaches to help you understand the path forward. They're strategic. The following is more tactical and best used in team discussions.
Taking Your First Steps
Innovation Activity Centers are the underpinning of each stage. They're the framework within the framework that ensures you're equipped to take decisive action. And drive your journey toward transformation.
While the stages and seasons of your business change, the activity centers and foci within your business don't have to. That's what allows you to stay steadfast in ever-changing currents.
Each of these activity centers requires a different type of person working on it, different KPIs, and different timelines.
I shot a video going into more detail on these activity centers as well.
Conclusion
Understanding these models makes it easier to understand and anticipate the capabilities, constraints, and milestones that define the path forward (regardless of how the world changes). They're a path towards technology adoption - though there are others.
We are making lots of progress refining these models, which are the basis for our plans to expand our Amplified Intelligence Platform. I look forward to improving it and sharing it with you all again.
Ultimately, frameworks aren't important if you aren't using them, and imperfect action beats perfect planning if you never act - but I hope you use these frameworks to help clear the path as you walk it.
Feel free to reach out if you have any questions or comments about the idea (or how to implement it).
It is easy to keep up – until you pause or slow down.
Being an Early Adopter was a big part of my identity. At this point in my life, I am still early with respect to new technologies, but I feel like I'm losing touch with a lot of today's culture.
Perhaps this started over a decade ago? I remember finding my sons' slang and music off-putting.
As an aside, my youngest son, Zach, went through a phase where it felt like he used the verbal tic ... "Dude" in every other sentence. Parenting trick – I broke his habit by screaming "FOOPDEEDOO!!" every time he said it, regardless of when it happened, where we were, or who we were with.
If it's crazy and it works ... it's not crazy. He certainly stopped saying "dude".
OK, back to the point. I realize that the Top 40 is basically a list of 40 songs that I don't know (and feel like I only randomly know some of the artists). Meanwhile, my staff laughingly refer to my favorite stations on SiriusXM radio as old-man music.
To make the point further, my research assistant asked me if I knew about Bad Bunny. To me, it sounded like a Disney cartoon for Halloween. But, apparently, he is a Grammy-winning recording artist who won "Album of the Year" for music that I had never heard.
It didn't take long to get to the list of top Spotify artists. For the record, I do know most of those artists – but admittedly few of their songs.
But as I said, listening to the Top 40 is getting harder for me. Where's the rock (or songs with discernable melodies)?!
Meanwhile, I'm about to start a new art exhibit. I call it "Jen Sleeps At Pop Concerts"
So far, we've got Taylor Swift, Coldplay, Beyoncé, Ariana Grande, Bob Seger, the Eagles, and the Rolling Stones. In case you're curious, she did not fall asleep at John Legend, Queen, or Ed Sheeran.
While there are certainly still fears about recessions, downturns, and more, nonetheless, it's good to see some growth. To understand more about the market-cap-to-GDP ratio, check out this link.
Unsurprisingly, the U.S. and China dominate the list, accounting for over 50% of the global market themselves. Even less surprisingly, emerging markets saw the most growth last year.
Visual Capitalist points out that U.S. stocks have often outperformed other wealthy nations over the past several decades.
If an investor put $100 in the S&P 500 in 1990, this investment would have grown to about $2,000 in 2023, or four-fold the returns earned in other developed countries.
The U.S. has been the leader in this space for as long as I can remember, but as emerging countries start to gain their footing, it's likely our percentage of the pie will decrease. Hopefully, the pie gets bigger as that happens.
My son attended Russell Brunson's annual Clickfunnels conference. They produce some of the most accessible marketing content we've found.
Me and Russell at the Cowboys V. Texans Game in 2016
When attending a conference, the main goal is to extract one key insight and an actionable item to boost your business ... even if you're well-versed in the subject.
After events, we conduct debriefing sessions to distill our most significant takeaways and get alignment.
This year's central theme was integrating disparate elements (in this case, "funnels") into a cohesive system and cyclical approach to drive sustainable growth. Russell made a compelling point: many so-called "businesses" are really just a string of promotions. According to his definition, a true business requires recurring revenue and continuity.
Aspiring entrepreneurs often impulsively shift from one idea or product to the next. They hastily launch their ventures, make a modest profit, and swiftly move on to the next endeavor, trying to stay on top of trends. Unfortunately, they neglect product development and fail to maintain their existing promotions in their haste to get to "next." Consequently, their businesses become incredibly fragile, susceptible to external shocks such as the unexpected disruptions of events like COVID-19, sudden market crashes, or social media platform crackdowns, which can ultimately lead to their demise
Like most great lessons, it's fractal. If you've been paying attention, you'll see how we've shared this idea before. So, I want to tell the same story from those other perspectives.
Selling Picks and Shovels
Most of us have heard the old adage about selling picks and shovels during the gold rush.
During a gold rush, many people rush to the goldfields to strike it rich by finding valuable gold nuggets. However, most gold rush participants do not find gold.
Often, the people who make the most money are the ones selling picks and shovels (goods and services) to the speculators. Said a different way, profits often flow to people who provide the systems and infrastructure that enable others to dream of a bigger and better future.
It's not sexy, but it's reduced risk, consistent demand, and a long-term perspective. When the mine dries up, you move on to the next mine and patiently stack your gold nuggets.
And, there's a plethora of opportunity that isn't selling picks and shovels. You can build temporary lodgings, open a bar, and of course, you can't forget the world's oldest profession ... trading.
Leveraging AI
It's easy to compare the AI race to the gold rush, but it's much more than that. Both the AI race and the gold rush generated significant hype and excitement. In both cases, there's a sense of a potentially life-changing opportunity, which attracts a herd of energized early movers looking for their big break. Just as gold prospecting was a risky and uncertain endeavor with no guarantee of success, the AI race is characterized by uncertainty and fear. Many are afraid, not just of losing their jobs, but of how to best use the technology.
As a result, you see a sea of people adopting every new app they can find, all to continue treading water in their business.
This occurs because people forget that AI is simply a tool – not the goal. They get blinded by the bright shiny objects, those glitters of gold near the top, that they don't do the hard work to find the bigger nuggets below the ground. All those tools are great, just like the promotions Russell mentioned. However, they're often distractions from building or buying something custom to your needs and focused on your bigger future.
To raise the stakes a bit, one of the biggest difference between the AI race and the gold rush, is the lasting impact. While the gold rush did lead to some lasting economic and infrastructural changes in certain areas, the AI race is going to significantly transform entire industries, economies, and societies over the long term.
The Capitalogix Advantage: A Solid Platform For Success
In our office, we think of this idea as the difference between a capability, a prototype, a product, and a platform. Building a platform (and a community) is how you become an institution and a game-changer.
When you start with that mindset, you can be the picks and shovels, you can be the hotels and hospitals, but you can also be the miner looking for the next big thing. That's what Capitalogix does for ourselves and our joint venture partners.
Continuity and recurring revenue create the bandwidth for innovation and ideation.
We have developed a fault-tolerant infrastructure because we have experienced fires, floods, Internet failures, the Snowpocalypse, bad data, missing data, and human error … not to mention Trump Tweets or COVID-19. That means our tools are built on a solid infrastructure supported by extensive experience.
And, while we've pivoted since inception, our vision and our "why" haven't. Joint ventures and new technologies are steps on our journey to our vision, not short-term promotions and distractions.
It's a small distinction with a massive impact.
When you're exploring the Wild West, whether it's in a gold rush, an AI boom, or in the world of e-commerce, your chances of success rise rapidly with a goal, a why, and a plan.
We talk a lot about automation – but tend to focus on the less tangible robots. Meaning, we talk about algorithms and AI, quantum computing, and how entrepreneurs can benefit from these new technologies.
However, a significant segment of automation is industrial (and often robotic process automation). Henry Ford and the assembly line revolutionized the world when they took the time to make a car from over 12 hours to just over 90 minutes.
It's interesting to think about more classic automation, and how different it is today from 1913 ... Of course, the level of machinery has grown exponentially, but so have the processes and the capabilities we expect. I flashback to Kanban and Toyota and what that did not only for the automobile industry ... but for corporations and small businesses around the globe.
New industries are also creating new jobs. With that said, recognize that people are increasingly resistant to doing the work we tend to automate. That is part of why it got automated in the first place. Another reason is that birth rates are dropping globally, and we always strive to do more with less.
Think about countries like Japan - which rely heavily on manufacturing ... but are seeing their already small populations decline. What do they do when their plants sit empty due to labor shortages?
Or, what about agriculture? We've already seen an exodus of youth who don't want to be involved in farming due to the long hours and grueling work... How do you keep up with the production necessary to feed the world?
We often think about robotics as taking our jobs, but the reality underpinning today (and the paradigm that will drive the future) is that automation sustains industries.
When labor can't keep up with demand, robotics fills the gap, whether it occurs in manufacturing, agriculture, or medicine.
As robotics get more capable, it won't be long before that's robotic surgeons are a normal part of a hospital's medical suite.
The same is true for AI. It will supplement gaps in countless industries.
These technologies are coming to your industry. It's inevitable. If you fight it, you'll feel strife and stress about the changing workforce. If you get ahead of it, you'll find endless opportunities to pursue your passions. As society shifts, I hope we see an influx of entrepreneurs to help drive the next era of innovation.
What do you think will happen?
P.S. Do you get my weekly round-up of links and thoughts on AI, exponential technologies, markets, and other interesting stuff? Or my new AI-curated newsletter? I believe you'll find them useful and fun. Happy to add you or anyone else you want to get it. Click here for the sign-up link.
Riding The Data Wave - Data Is Becoming a New Asset Class
Data is the fastest-growing commodity, and is today’s “wild west” and the battlefield of today’s tech titans. We talk about AI as this gold rush, but data is the underpinning of it all.
A staggering 328.77 million terabytes of data are created daily, which means around 120 zettabytes of data will be generated this year.
Video is still growing rapidly, but so is IoT, with more than 15% annual growth. There are now almost 20 billion connected devices.
Alphabet, Amazon, Apple, Facebook, and Microsoft all have unprecedented amounts of data (and power).
Rapid growth means little time to create adequate rules. Everyone’s jumping to own more data than the next and to protect that data from prying eyes.
As a great example of this, I often warn people to keep their intellectual property off of ChatGPT or other hosted language models.
I also see it trading, but it’s pervasive in every industry and our personal lives as well.
Collecting basic data and using basic analytics used to be enough ... but not anymore. The game is changing.
For example, traders used to focus on price data ... but there has been an influx of firms using alternative data sets and extraordinary hardware and software investments to find an edge. If you’re using the same data sources as your competitors and competing on the same set of beliefs, it’s hard to find a sustainable edge.
Understanding the game others are playing (and the rules of that game) is important. However, that’s only table stakes.
Figuring out where you can find extra insight, or where you can make the invisible visible, creates a moat between you and your competition and lets you play your own game.
Here is a quick high-level video about Data as fuel for your business. Check it out.
It is interesting to think about what’s driving the new world (of trading, technology, AI, etc.), which often involves identifying what drove the old world.
History has a way of repeating itself. Even when it doesn’t repeat itself, it often rhymes.
With that said, the key to unlocking the pathway to the new world often comes from a new or alternative data set that lets you approach the problem, challenge, or opportunity from a different perspective.
Before e-mails, fax machines were amazing. Before cars, people were happy with horses and buggies.
These comparisons help explain the importance of data in today’s new world economics.
gapingvoid
Data as the New Oil
Petroleum has played a pivotal role in human advancement since the Industrial Revolution. It fueled (and still fuels) our creativity, technology advancements, and a variety of derivative byproducts. There are direct competitors to fossil fuels that are gaining steam, but I think it’s more interesting to compare petroleum to data due to their parallels in effect on innovation.
Pumping crude oil out of the ground and transforming it into a finished product is not a simple process. Yet, it is relatively easy for someone to understand the process at a high level. You have to locate a reservoir, drill, capture the resource, and then refine it to the desired product – heating oil, gasoline, asphalt, plastics, etc.
The same is true for data.
In a sense, data fuels the information economy much like oil fuels the industrial economy. The amount of power someone has can be correlated to their control of and access to these resources. Likewise, things that diminish or constrain access or use of these resources can lead to extreme consequences.
Why Data Is Better Than Oil
The analogy works, but it’s just that, an analogy, and the more you analyze it, the more it falls apart. Unlike the finite resource that is oil, data is all around us and increasing at an exponential rate, so the game is a little different:
Using alternative data gives traders an advantage, but it doesn’t always have to be confidential or hard-to-find information. Traders now have access to vast amounts of structured and unstructured data. A significant source that many overlook is the data produced through their own process or the metadata from their own trades or transactions.
In a word of caution, there are two common mistakes people make when making data-driven decisions. First, people often become slaves to the data, losing focus on the bigger picture. It’s the same mistake people make with AI. Both are tools, not the end goal. Second, even the most insightful data can’t predict black swans. It’s important to exercise caution. Prepare for the unexpected.
The future of data is bright, but it’s also littered with potential challenges. Privacy concerns and data misuse are hot-button topics, as are fake news and the ability of systems to generate misleading data. In addition, as we gain access to more data, our ability to separate signal from noise becomes more important.
I think one of the biggest problems facing our youth - and really all of us - is how much information is thrust at us every waking moment of the day. No previous generation has had this much access to data. As a result, many are actually less informed than in the past. Soundbites become the entire news story, and nuance gets lost in the echo chambers.
The question becomes, how do you capitalize on data without becoming a victim of it?
Food for thought!
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