Dr Emmanuel Ogungbemi

Head of Data Engineering | I help you improve your productivity with data and AI

From being a data analyst to leading the development of data pipelines, my journey in data engineering and analytics has been both challenging and rewarding.

When I began my career in data, I faced the daunting task of turning vast amounts of raw data into actionable insights.

The problem? Many organisations struggle with fragmented data and inefficient processes.

Here's how I tackled these challenges and built a successful career in data:

1. Crafted Data Solutions: Designed and implemented a Common Data Platform, ensuring seamless data integration and access.
2. Led Innovative Projects: At NATS, I contributed to the world's first AI system for air traffic control, utilising digital twinning and machine learning.
3. Developed Future Talent: Shaped data science and engineering education at Multiverse by developing comprehensive curricula for degree-level apprenticeships.
4. Consulted on High-Impact Projects: Provided AI and data science consultancy for industry giants like BP, Sword and Chaucer (now BIP UK), driving data-driven decision-making and innovation.

Now, I'd like to talk about you.

Are you aspiring to become a successful data analyst/data scientist/data engineer but need help figuring out where to start?

Here's a roadmap to guide you:

1. Master the Fundamentals:
- Learn key programming languages like Python and SQL.
- Understand data structures, algorithms, and database management.

2. Gain Practical Experience:
- Work on real-world projects to apply your skills.
- Use tools like Power BI and Tableau for data visualisation.

3. Join the Community:
- Participate in data science forums and attend industry events.
- Network with professionals to exchange knowledge and opportunities.

4. Continuous Learning:
- Stay updated with the latest trends and technologies in data analytics.
- Take advanced courses to deepen your expertise.

To help you get started, I've created a comprehensive Data Analyst Roadmap that outlines the essential steps and resources you need to succeed.

Join my email list to register your interest in my free Data Analyst Roadmap.

You have the potential to excel in the data industry, and I'm here to support your journey.

Let's connect and share our experiences in data engineering and analytics!

Head of Data Engineering

I'm excited to share an invaluable resource: the Data Engineer Interview Guide by Simplilearn!

Preparing for a data engineering interview can be daunting, but this comprehensive guide has got you covered. 

Whether you are a fresh graduate or an experienced professional, this document provides a detailed overview of the key questions and answers you can expect in a data engineering interview.

Key topics include:
- Understanding the role and responsibilities of a data engineer
- Differences between data engineers and data scientists
- Key skills required for data engineering, including SQL, Hadoop, and Python
- Essential frameworks and applications for data engineers
- Commonly asked interview questions and how to answer them
- Practical tips for handling job-related crises and real-world scenarios
- Insights into data modelling, ETL processes, and working with big data in cloud environments


Enhance your interview preparation and stand out from the competition with this detailed guide!

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- Save to revisit down the road
- Add your comment!

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Talks about #data, #kindness, #interviewtips, #selfimprovement, and #careertransition

Data Engineering Intro

I help you break into data science and AI with practical tips, real-world insights, and the latest trends.

SQL Introduction Handnotes

The real secret to becoming a data professional isn't technical skills—it's storytelling.

Here's how narrative trumps numbers.

When I first entered the world of data, I was captivated by the endless possibilities that numbers could unlock.

But soon, I realised something crucial: data alone doesn't speak.

It's the story you weave around it that truly makes an impact.

Let me explain how you can harness the power of storytelling in data:

1. Understand Your Audience
  ↳ Tailor your narrative to resonate with the specific needs and interests of your audience.
  Whether you're speaking to executives or data enthusiasts, adjust your story accordingly.

2. Find the Human Element
  ↳ Data is ultimately about people.
  By highlighting the human impact, you make your insights relatable and actionable.

3. Create a Compelling Narrative Arc
  ↳ Like any good story, your data-driven narrative should have a clear beginning, middle, and end.
  Start with the problem, introduce the data, and conclude with actionable insights.

4. Simplify Complex Data
  ↳ Great storytelling involves breaking down complex data into understandable and engaging segments.
  Use visuals and analogies to make your points clear.

5. Inspire Action
  ↳ Your story should lead to a call to action, encouraging your audience to make informed decisions based on your insights.
  
Remember, data storytelling isn't just about presenting facts—it's about driving change.

By mastering the art of storytelling in data, you transform from a mere analyst to an influential data storyteller.

And the best part?

Anyone can learn this skill.

So, are you ready to craft stories that drive data-driven decisions?

Start weaving your narrative today.

Excited to share an insightful resource: MLlib: Scalable Machine Learning on Spark by Xiangrui Meng and collaborators!

This comprehensive guide explores the powerful capabilities of MLlib, Spark's scalable machine learning library.

It covers everything from basic algorithms to advanced machine learning techniques, making it an essential resource for data scientists and engineers looking to leverage Spark for large-scale data processing and analysis.

Key topics include:
- Overview of MLlib and its integration with Apache Spark
- Machine learning algorithms: classification, regression, clustering, and collaborative filtering
- Practical examples and implementations of logistic regression, k-means clustering, and ALS
- Performance comparisons and scaling properties of MLlib
- New features and updates in MLlib v1.x
- Integration with other Spark components like Spark SQL, Streaming, and GraphX


Unlock the full potential of machine learning with MLlib on Spark and take your data projects to the next level!

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- Save to revisit down the road
- Add your comment!

Why I believe the future of data engineering lies not in new tech but in teaching empathy and communication.

I started in data engineering with the belief that the latest tech would solve every problem.

That mindset shifted.

Here's why: it's not just about the tools.

It's about understanding the humans behind the data.

In my journey from data analyst to data engineering leader, I've learned that the hardest problems aren't technical.

They're human.

When I was tasked with transforming raw data into insights, I quickly realised that many organisations were drowning in fragmented data.

Not because they lacked technology, but because they lacked communication.

→ Data was siloed.

→ Teams didn't talk to each other.

→ Processes were inefficient.

So I focused on:

1. Building Bridges: I brought together diverse teams, ensuring everyone understood the data's value and purpose.

2. Teaching Empathy: I encouraged my team to see data not just as numbers but as stories with human impact.

3. Enhancing Communication: I led efforts to develop clear channels and languages for data discussions, making complex insights accessible to all.

It wasn’t just about algorithms.

It was about collaboration.

About understanding the fears and hopes of those who rely on the system.

When we embrace empathy and communication, we transform data from a static resource into a dynamic force for change.

We give it life.

The future of data engineering won't be about the flashiest tools.

It will be about the human touch.

So here's my challenge to you:

Focus on the human side of data.

Ask more questions.

Listen more.

Let's build a future where data brings us together, not keeps us apart.

What do you think?

How can we make data engineering more human?

Share your thoughts below.

Top AI Voice | Certified AI Innovator | I Recommend & Teach Individuals & Businesses AI/AITools that yield atleast 90% efficiency

Hi, I'm Awa K. Penn, an AI Top Voice and Certified AI Innovator, passionate about transforming businesses and empowering individuals through the power of AI. With a substantial following across various platforms, including over 224,000 on Instagram, 650,000 on Facebook, 40,000 on Threads, 3,000+ on TikTok, and over 40,000 newsletter subscribers, I help people build their online brand and share actionable tips that drive growth and success with AI.

I specialize in:


➡️ AI Consulting: Offering coaching and mentorship to help individuals leverage AI to build an online brand.

➡️ Training & Workshops: Leading interactive sessions to upskill teams and individuals in the latest AI technologies.

➡️ Custom AI Solutions: Creating tailored AI strategies that align with unique business needs.

➡️ Efficiency Optimization: Implementing AI tools that boost operational efficiency and streamline processes.

Let's connect and explore how AI can enhance your work and help you achieve your goals.

Awa K. Penn

AI will replace busywork.

But only if you know which tools to use.

This cheatsheet gives you everything in one glance.

It covers;

AI Chatbots
AI Presentation
AI Coding Assistance
AI Email Assistance
AI Image Assistance
AI Spreadsheet
AI Meeting Notes
AI Writing Generation
AI Scheduling
AI Video Generation
AI Graphic Design
AI Data Visualization

--------------------------
Learn AI for FREE👉 https://lnkd.in/edj3CsFu

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ChatGPT vs Manus, vs Claude vs Gemini?

Use this guide to pick the right AI tool in seconds.


ChatGPT
 ↳ Ideal for writing, coding, summarizing, or brainstorming. You can also upload files, talk through tasks, or automate workflows with Custom GPTs.

Manus
 ↳ Perfect for full automation. It executes workflows, connects tools, deploys end-to-end agents, and runs tasks completely hands-free.

Claude
 ↳ Excellent for research, reports, and long documents. It reasons deeply, handles large contexts, and produces well-structured analyses and summaries.

Gemini
 ↳ Best within Google Workspace. It integrates with Gmail, Docs, Slides, and Sheets for writing, visual content, presentations, and in-depth research.

AI works when you pick the right tool at the right time.

-------------------------------
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How to create AI agents that actually work

Most people think AI agents are just chatbots with a bit more polish. 

After building and deploying agents across dozens of workflows, 

Here is what actually happens behind the scenes when an AI agent runs your tasks for you.

At the core, an agent is an orchestration layer over three functions:

1️⃣ Reasoning (Think)
 Processes your instructions
 Understands context and constraints
 Determines the next best action

2️⃣ Decision Engine (Decide)
 Evaluates options
 Applies rules and goals
 Chooses the correct step in the workflow

3️⃣ Action Layer (Act)
 Executes tasks across your tools
 Searches, writes, sends, updates
 
Platforms like Zapier bring these pieces together, streamline the handoffs, and run everything in the background without manual supervision.

↳ What makes Zapier AI Agents effective
→ They complete real tasks, not just reply to text
→ They run continuously without reminders
→ They connect to your existing systems instantly
→ They adapt to new instructions with minimal setup

↳ Real-world use case built in the carousel
- Agent searches for potential leads
- Scores each one with Zapier AI
- Saves qualified leads to Notion
- Logs everything in Google Sheets
- Sends a daily Slack summary

↳ The building blocks are simpler than you think
→ Explain the job in plain language
→ Define what a “good” lead looks like
→ Specify what gets stored and where

↳ Tool Connections
→ Web search for discovery
→ AI scoring model for qualification
→ Notion for structured storage
→ Sheets for a full activity log
→ Slack for daily summaries

↳ Testing and Verification
→ Confirm the leads selected make sense
→ Ensure scoring is consistent
→ Check that Notion and Sheets capture the data
→ Review the Slack update for clarity

↳ Activate and let it run

Once activated, the agent handles the workflow independently. 
No manual effort. No code. Just clear instructions.
The setup that used to take hours now takes minutes. 

Ready to start building your AI Agent? Head to the first comment to try Zapier for free. 


#ZapierPartner #ZapierAmbassador

AI agents explained

Teaching 1 Million+ People AI Everyday

How to create better images using Nano Banana Pro

As recommended by Google

Each prompt should consist of the following

1. Style
2. Action
3. Subject
4. Location
5. Composition
6. Editing steps

What the model can do

- Keep a character consistent 
- Mix ideas in one image 
- Edit a small area with care 
- Transfer looks and textures 
- Use logic for next steps

Five prompting moves to try

1. Preserve a hero across scenes
2. Make one precise change
3. Blend two distant ideas
4. Apply a new visual style
5. Ask what happens next

Limits to watch

- Stylization can be uneven 
- Text in images can be wrong 
- Faces can drift across shots 
- Aspect ratios may not hold

--------------------------
If you want more tips and insights about AI, join my newsletter that teaches you how to leverage AI 👇https://lnkd.in/edj3CsFu

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How to Nano Banana Pro

AI is not replacing project managers.

But project managers who use AI?

They’ll replace the ones who don’t.

Here’s the stack that works.

1. ChatGPT
↳ Where It Fits: Brainstorming, decision support, writing briefs
What It Frees Up: Faster planning, sharper decisions

2. Perplexity
↳ Where It Fits: Research vendors, trends, competitive tools
What It Frees Up: Instant clarity for better choices

3. Fellow AI
↳ Where It Fits: Meeting agendas, notes, action tracking
What It Frees Up: Smoother meetings, better execution

4. Gamma
↳ Where It Fits: Sprint reviews, stakeholder decks, project updates
What It Frees Up: Fast, polished slides without design work

5. Guidde AI
↳ Where It Fits: SOPs, tool walkthroughs, async video guides
What It Frees Up: Scalable onboarding, fewer repeated explanations

6. Notion AI
↳ Where It Fits: Project docs, sprint plans, team knowledge base
What It Frees Up: Centralized knowledge, clean collaboration

7. ClickUp AI
↳ Where It Fits: Smart task updates, daily summaries, project reports
What It Frees Up: Less admin work, faster updates

8. Magical AI
↳ Where It Fits: Autofill emails, project updates, recurring data entry
What It Frees Up: Hours saved on routine typing

9. Zapier AI
↳ Where It Fits: Automate workflows and agents, pull data, update project tools
What It Frees Up: Hands-off execution, powerful integration

--------------------------
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10 AI skills to master before 2026


- AI Delegation
- AI Tool Selection
- AI Ethics & Safety
- AI Decision Making
- AI Content Creation
- Prompt Engineering
- AI Workflow Building
- AI for Ideas & Planning
- No-Code Automation/agents
- AI for Customer or Team Support

----------------------
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Canva just dropped 9 free design courses

Save this post for later.

1/ Canva Visual Suite 
https://lnkd.in/ghYd95D7

2/ Canva Essentials 
https://lnkd.in/gm7t8DZJ

3/ Work Smarter with Canva AI 
https://lnkd.in/gTPm9ukH

4/ Graphic Design Essentials  
https://lnkd.in/gEiSkC4j

5/ AI in the Classroom 
https://lnkd.in/gTXjHc3V

6/ Presenting in Canva 
https://lnkd.in/gnRZ_VHb

7/ Designing Emails in Canva 
https://lnkd.in/gEEQpNNu

8/ Canva for Work 
https://lnkd.in/gS2HwwPp

9/ Marketing with Canva
https://lnkd.in/gznjiUHZ

-------------------
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Sora 2 vs Veo 3 vs Higgsfield vs MakeUGC?

Here’s the fastest way to understand what each one is best at.

Sora
↳ Cinematic storytelling. Long scenes, full environment control, character movement.

Veo
↳ Short-form polish. Fast B-roll, smooth transitions, lifestyle visuals for TikTok, Reels, Shorts.

Higgsfield
↳ Faces and presenters. Talking heads, reactions, influencer-style content.

MakeUGC
↳ It combines all three models in one place: product-in-hand shots, AI hooks, B-roll, avatars, and automated editing, so you can focus on building ads instead of juggling tools.

Use MakeUGC to turn them into consistent & scalable output

Repost + Comment “stack” and I’ll send you the full guide.

#MakeUGCPartner

AI is taking over core business functions

The right tools decide how far you can go

These are the stacks that work.

- Business planning and workflow
- Content creation and automation
- Visual identity and creative assets
- Store and landing pages
- Automation and customer
- Scheduling
- Payments
- Automation
- Sales
- Chat

--------------------------------
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Forget GPTs in ChatGPT. 
Claude's Skills are the best.

Most people think Claude Skills are just saved prompts. 

They miss the entire system that lets Claude load instructions, follow your rules, and complete work with the same structure every single time.

The Claude Skills Pipeline
 At its core, it works through three parts.

1️⃣ Selector
 Understands the request
 Chooses the right Skill
 Loads the needed files or templates

2️⃣ Instruction Engine
 Runs the Skill’s rules
 Applies your format and tone
 Keeps output consistent

3️⃣ Work Engine
 Writes, analyses or codes
 Handles multi-step tasks
 Combines Skills when needed

What makes Claude Skills stand out
 → They trigger automatically
 → They keep quality stable
 → They support long, structured work
 → They work in chat and API

Real uses
 • Research summaries
 • Policy drafts
 • Lesson plans
 • Code reviews
 • Report templates


--------------------------------
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Claude Skills explained

AI isn’t replacing creative teams.

But creative teams using AI?

They’ll replace the ones who don’t.

Here’s the stack that’s changing how ads get made 👇

1. MakeUGC V.2
↳ Where it fits: Full ad creation from concept to cinematic output
↳ What it frees up: No shoots, no editors, no waiting

2. Sora2 Pro
↳ Where it fits: Storyboarding, scene design, and creative pacing
↳ What it frees up: Faster ideation, stronger storytelling

3. Veo3.1
↳ Where it fits: Visual direction, transitions, and shot structure
↳ What it frees up: Human-level pacing and emotional rhythm

4. Kling
↳ Where it fits: Realism, human motion, and expressions
↳ What it frees up: Removes the “AI look,” adds authenticity

5. Notion AI
↳ Where it fits: Creative tracking, script organization, and content libraries
↳ What it frees up: Centralized creative workflow

6. Zapier AI
↳ Where it fits: Auto-launching ads, refreshing winners, updating data
↳ What it frees up: Hands-free execution across platforms

8. Perplexity
↳ Where it fits: Creative research, trend discovery, competitor scanning
↳ What it frees up: Better ideas, faster

9. Instantly AI
↳ Where it fits: Influencer outreach and ad collaboration
↳ What it frees up: More partnerships with zero manual work

AI won’t replace your creative team
but teams using MakeUGC V.2 + AI Agents will replace everyone else.

Repost + comment “V2” and I’ll send the full creative stack setup.
(Must be following)

#MakeUGCPartner

Top AI tools every founder should master in 2026


It covers: 

→ Product
→ Marketing
→ Sales
→ Executive
→ Operation
→ Customer

Post inspired by Edwina McKennon

-----------------------------

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Bolt vs Replit vs Base 44 vs Lovable?

Use this guide to choose the right build tool with confidence.

- Bolt
 ↳ Suited for people who want to build quickly with clear logic. It turns text into code, explains reasoning, previews work as you go, and supports instant debugging.

- Replit
 ↳ Strong when you need to run almost anything. It helps you automate scripts, test machine-learning ideas, prepare for interviews, host projects, and deploy code.

- Base 44
 ↳ Designed for internal systems. It helps you manage APIs, build data portals, create dashboards, handle no-code data, organise workflow sync, and support team systems.

- Lovable
 ↳ Good for turning ideas into working products. It offers visual SaaS creation, templates for startups, payment flows, team testing, instant launch, and simple no-code logic.

AI development becomes easier when you choose the right environment for the task.
-----------------------------

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After 3 months of testing, why some brands rank #1 in ChatGPT and others don't,

I finished The Complete Guide to Ranking in AI Search.
You can get it FREE.
Comment "GUIDE" and I'll send it to you.

This is not generic SEO advice repackaged.

It teaches you exactly how to show up when customers ask ChatGPT, Claude, Perplexity, or Gemini for recommendations in your category.

It's the exact playbook used to:
→ 6x AI search visibility for 8-figure brands
→ Get clients cited by ChatGPT 4x more than competitors
→ Turn Reddit threads into ranking opportunities
→ Build content workflows that actually move AI rankings

Inside, I cover:
→ The point-by-point checklist that makes content LLM-crawlable
→ Why 73% of ChatGPT citations come from Reddit (not your website)
→ How to find the exact queries ChatGPT uses to recommend competitors
→ The workflow that took Webflow from 23% to 67% visibility in 30 days
→ Content refresh strategies that work for AI search vs. Google SEO
→ How to use Answer Engine Optimization (AEO) without losing brand voice

It's a complete breakdown of how AI search engines decide what to cite—and how to win that game before your competitors even know it exists.

Follow and comment "GUIDE," and I'll send it to you.

Repost, so your network doesn't get left behind in AI search

#AiropsPartner

Everyone is talking about Vibe coding with AI tools

And they think building an AI-powered app stops at writing prompts. 

But they overlook the entire data layer that lets an app read, understand, and act on real information you already store.

Platforms like Replit make these modules work together, handle permissions, and keep the app in sync with your sources.

 ↳ What makes Replit Vibe Code powerful
→ Works with your real files, not abstract prompts
→ Connects to Notion, Google Drive, HubSpot, Slack, Gmail, Dropbox
→ Let your app read and use material you already created
→ Handles the plumbing so you can focus on logic

 ↳ Real-world build from the carousel
- Use Google Drive as the data store
- Load documents, PDFs, notes, and scripts
- Extract the main ideas from each file
- Create an app from your data
- Produce a fresh piece of content from it

 ↳ The building blocks are simpler than you think
 → Choose a data source
 → Authorize it once
 → Create a safe bridge between your files and your code

 ↳ Vibe Code Instructions
 → Tell the model which folder to read
 → Clarify the tone and structure to follow
 → Anchor the logic in your own examples

 ↳ App Logic
 → Fetch the list of files
 → Read each one
 → Send the content into the model
 → Collect outputs into new files or summaries

 ↳ Final Output
 Your app can produce:
 → Daily content summaries
 → Research briefs built from long documents
 → Draft posts based on your notes
 → Training outlines from stored materials

Once active, your app processes your data automatically, generates new material on command, and updates itself as your library grows.

Want to start creating? 

Earn $10 in credits when you sign up here: https://lnkd.in/eW_DV5_y

-----------------------------
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#ReplitPartner

Vibe code an app using your own data sources

Google just killed the old way we used Gemini.

They rolled out Gemini 3 Pro inside Google’s apps.

Now, Gemini doesn’t just answer. It produces real work.

The game is no longer about simple prompts.

It’s about completing tasks within Docs, Sheets, Gmail, and Drive.

Here’s the breakdown of what these changes:

One Command → Full Workflow
You don’t need plugins, add-ons, or extra tools.

☑ “Review my Gmail inbox and prepare actions.”
☑ “Turn these notes into a full slide deck.”
☑ “Analyse this spreadsheet and create a clear summary.”


 Gemini builds real output inside Google’s environment.

☑ Processes documents
☑ Builds slide presentations
☑ Reviews websites
☑ Generates charts, diagrams, and summaries

It works across text, images, audio, and video in a single workflow. No Setup Required

You don’t need:
☑ APIs
☑ Prompt libraries
☑ Manual configuration

Available now (for some)
 ✅ Google AI Premium
 ✅ Gemini API developers
 🕓 Wider rollout expected as Google expands access
Access It Instantly

-----------------------------

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Cancel your Lovable, Bolt, and Claude subscriptions. 

Canva AI can now code, build, and publish web apps 👇

No coding. No setup.
Just Canva = fast, functional, fully shareable web apps.

Here’s how I do it:
Step 1: Head over to Canva AI
 ↳ Go to canva dot com
 ↳ Click “Canva AI” then hit “Code for me”

Step 2: Write your prompt
 ↳ Drop your idea or app logic in plain English
 ↳ Canva AI will handle the coding

Step 3: Review the code
 ↳ Instantly get clean HTML, CSS, and JS
 ↳ No setup or coding knowledge required

Step 4: Preview the app
 ↳ Click “Use in New Design”
 ↳ Test both mobile and desktop views inside Canva

Step 5: Run & test live
 ↳ Click “Run”
 ↳ See your web app in action without ever opening a terminal

Step 6: Publish & share
 ↳ Hit “Publish”
 ↳ Share as a live link or embed it on your site


--------------------------------
Learn AI for Free 👉 
https://lnkd.in/edj3CsFu

🔄 REPOST to help others know this

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Hi, I'm Awa K. Penn, an AI Top Voice and Certified AI Innovator, passionate about transforming businesses and empowering individuals through the power of AI. With a substantial following across various platforms, including over 215,000 on Instagram, 634,000 on Facebook, 30,000 on Threads, 3,000+ on TikTok, and over 38,000 newsletter subscribers, I help people build their online brand and share actionable tips that drive growth and success with AI.

I specialize in:


➡️ AI Consulting: Offering coaching and mentorship to help individuals leverage AI to build an online brand.

➡️ Training & Workshops: Leading interactive sessions to upskill teams and individuals in the latest AI technologies.

➡️ Custom AI Solutions: Creating tailored AI strategies that align with unique business needs.

➡️ Efficiency Optimization: Implementing AI tools that boost operational efficiency and streamline processes.

Let's connect and explore how AI can enhance your work and help you achieve your goals.

Create webs apps in canva

How to create better UGC ads
using MakeUGC and Nano Banana Pro

- Nano Banana Pro upgrades the visual quality
- It adds an intentional and branded look
- It makes simple clips feel ready for scale

How to structure every Nano Banana Pro prompt

1 → Visual style
 ugc or studio or cinematic or raw selfie

2 → Action
 open product or point or react or scroll

3 → Subject
 creator or ai avatar

4 → Location
 bedroom or kitchen or street or office

5 → Composition
 close up or medium shot or over the shoulder

6 → Editing notes
 lighting or sharpness or grain or color grade

What Nano Banana Pro enables

1 → One creator across many ads
2 → Many ideas inside one clean ugc scene
3 → Edit one part without breaking the clip
4 → Keep the same brand look across creators
5 → Create follow-up scenes for longer ads

Five moves that convert better
1 → Keep one hero creator and test new hooks
2 → Change only one variable per version
3 → Blend problem and demo and reaction
4 → Reuse one script with new visual styles
5 → Ask the model to build the next scene

I created a simple guide
It shows my full workflow
inside MakeUGC with Nano Banana Pro

Comment GUIDE, and I will share it with you

OMG, AI face swaps are getting too hard to spot.

Wan 2.2 inside MakeUGC makes it possible.

Most people think Wan 2.2 only handles simple face replacement.

They miss the entire system that makes character-swapping automatic, consistent, and production-ready.

The Wan 2.2 Pipeline
At its core, it works through three parts.

1️⃣ Selector
Understands the video
Detects the performer
Choose the character you want to replace it with

2️⃣ Character Engine
Rebuilds facial structure
Maps expressions + micro-movements
Keeps lighting + skin texture consistent

3️⃣ Swap Engine
Applies the new face seamlessly
Handles talking, movement, angles
Exports clean clips ready for ads

What makes Wan 2.2 stand out
→ Ultra-realistic swaps
→ Zero manual masking
→ Works on any UGC footage
→ Perfect for multi-character testing in ads

Real uses
- Replace your face with a model without reshooting
- Create 10 variations of the same ad with different creators
- Localize ads with region-specific creators
- Test different characters to find the one that converts best

I made a short guide showing how to use Wan 2.2 inside MakeUGC for ad testing and character swapping.

Repost + comment “Tool” and I’ll send it.


#MakeUGCPartner

AI breaks when the data is broken.

Many teams still store customer information in different places.

- A note in one tool.
- An email in another.
- A conversation saved somewhere no one checks.

When AI works with that, it guesses.
And when it guesses, results fall apart.

- Slow responses.
- Wrong priorities.
- Missed opportunities.

Good AI needs a full picture 
A complete record of every customer.

HubSpot’s Smart CRM webinar in December focuses on this idea. 
It explains why unified data changes everything and why scattered data limits every decision.

You’ll see how a connected CRM helps teams:
→ Keep every conversation, email and record in one place
→ Give AI the right context before it makes a decision
→ Improve forecasting with a full customer history
→ Speed up follow-ups and reduce mistakes
→ Align sales, service and marketing around the same information

The session also shares stories from teams that switched from older systems and rebuilt their process with a single, clean data foundation.

You’ll learn how they moved from confusion to clarity:

• Faster access to customer information
• Stronger predictions
• Better support and smoother workflows
• More reliable AI-driven actions

If you use AI in your work, this session will help you understand the foundation that makes it truly effective.

Register here: https://hubs.la/Q03VP_V_0

#HubSpotPartner

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The Battle

Dr Emmanuel Ogungbemi

Awa K. Penn

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taplio

The Battle

Dr Emmanuel Ogungbemi

Awa K. Penn

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Dr Emmanuel Ogungbemi's LinkedIn Performance

Performance ScoreAwa K. Penn's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreDr Emmanuel Ogungbemi's LinkedIn Performance