Mastering Generative AI from Scratch

Chapter 1 – Seeing the Invisible | What is Data? The Data We Use Every Day

Ivy’s first steps into the world of data

Ivy stood in front of the glass door, badge still clipped crookedly to her lanyard, eyes darting nervously as the automated lock clicked open. Her first official day at the digital marketing firm had begun. Inside, it was all whiteboards full of arrows, colorful charts on wide screens, and people tapping rapidly at their keyboards with a strange mix of urgency and ease.

"Morning!" someone chirped. It was Derek, the senior she was assigned to shadow. Friendly but not overbearing. Calm eyes that had clearly seen a hundred campaigns come and go.

"You’re just in time," he said, gesturing toward the meeting room. "Come sit in. Campaign review’s starting."

The room was buzzing. The creative team was discussing Instagram story engagement, someone from analytics mentioned “bounce rate volatility,” and a strategist was explaining A/B test results. Ivy tried to follow, but the words all felt like puzzle pieces from ten different boxes.

She scribbled down phrases like CTR spike, impressions vs. reach, and conversion funnel leak. But they looked more like spell incantations than anything she truly understood.

After the meeting, sensing her overwhelmed silence, Derek nudged a coffee cup her way. “You okay?”

“I think I understood... about seven percent of that,” Ivy admitted with a half-laugh. “Everyone kept talking about ‘the data’—as if it's some... invisible colleague.”

Derek smiled. “That’s actually a great way to think about it. Data is our invisible teammate. It sees everything. It remembers everything. You just have to learn its language.”

They sat near the office pantry, warm mugs in hand. Derek leaned back.

“Think about this morning. You woke up, checked your phone, right?”

“Of course,” Ivy nodded. “Notifications, a couple of Reels…oh, and I ordered coffee through an app.”

“There you go. That’s data. Every scroll, every tap, every purchase—it all leaves a trail. Facebook knows you like dog videos. Your coffee app knows you prefer oat milk. Even Google Maps knows when you’re usually stuck in traffic.”

Ivy blinked. “Wait... so I’ve basically been leaking data all over the place?”

“In a way,” Derek chuckled. “But everyone does. And marketers like us, especially in social media, swim in that sea.”

Later that day, Derek walked her around the office, pointing things out like a guide in a digital jungle.

The creative team was brainstorming for a new Facebook campaign. “We’re testing carousels versus short-form videos,” someone said. “Videos are getting 40% more engagement last month.”

The analytics team had dashboards full of graphs. “These spikes? They’re from our weekend push. Traffic surged when we posted Reels.”

The client team was dissecting comments and reactions. “We noticed a pattern—anytime we use yellow in a visual, click-through goes up.”

Everywhere Ivy turned, there were patterns, numbers, behavior trails. Data wasn’t just something in reports—it was flowing through every conversation.

“So…” Ivy hesitated, trying to put it together, “this is all... Big Data?”

“Yep,” Derek replied. “And to handle Big Data, you need to understand what makes it so ‘big’. We usually talk about the 4Vs.”

“Let me guess—Volume, because there’s a lot of it?”

“Exactly. Like our last campaign—one post pulled in over 300,000 impressions in 24 hours.”

“And... Variety?”

“We're not just looking at numbers. It's comments, likes, shares, videos, photos, timestamps, even emojis.”

Ivy nodded. “Okay, third V?”

“Velocity. The speed at which data comes in. Think real-time reactions on Instagram stories. We need to adjust strategy mid-campaign sometimes.”

“And the last one?” she asked.

“Veracity. Can you trust the data? Was it real users or bots? Did the feedback come from our target audience or random noise?”

That night, Ivy lay in bed, staring at the ceiling. Her mind replayed the day like a highlight reel. She realized that data wasn’t some cold, robotic thing. It was human. It was personal. Every click, every view—it told a story.

And if she wanted to become good at this, she needed to learn how to listen.

Not just to people.

But to the data whispering beneath.