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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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.

I am excited to share a comprehensive resource: Machine Learning, Deep Learning, and Artificial Intelligence Cheat Sheets compiled by Nikhil Yadav from Stanford University and MIT!

This collection of cheat sheets covers key concepts and techniques across machine learning, deep learning, and AI. 

Perfect for students, professionals, and enthusiasts, this document provides quick references and summaries of essential topics in these fields.

Key topics include:
- Probability and Statistics fundamentals
- Supervised and Unsupervised Learning algorithms
- Linear and Logistic Regression
- Support Vector Machines (SVM) and Generative Learning
- Tree-based and Ensemble Methods
- Principal Component Analysis (PCA) and other dimension reduction techniques
- Neural Networks, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs)
- Reinforcement Learning and Control
- Essential metrics for model evaluation and selection
- Tips and tricks for effective machine learning practice


Enhance your understanding and mastery of machine learning, deep learning, and AI with these detailed cheat sheets!

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ML, Deep Learning and AI Cheat Sheet

SQL Introduction Handnotes

Excited to share an essential resource: DAX Query Plans by Alberto Ferrari!

This comprehensive paper introduces the performance analysis and optimization of DAX code through the use of DAX query plans. 

Ideal for BI professionals and data analysts, this document provides valuable insights into improving query performance by understanding and optimizing DAX queries.

Key topics include:
- Finding and interpreting DAX query plans
- Differences between logical and physical query plans
- Overview of the formula engine and storage engine
- Basic optimization techniques for DAX queries
- Practical examples using the Contoso and AdventureWorks databases


Enhance your DAX skills and improve query performance with this detailed guide!

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DAX Query Plans

Why data engineers are like the unsung heroes of the tech world – and why you should become one.

Ever wondered what makes the tech world tick?

It’s not just the flashy apps or cutting-edge AI.
It’s the data engineers behind the scenes, making everything work smoothly.

Here’s why they’re the real MVPs:

1. Foundation Builders

Data engineers lay the groundwork for any data-driven project.

Without them, data scientists and analysts would be flying blind.

They create robust data pipelines that ensure seamless data flow – the backbone of every tech solution.

2. Problem Solvers

Every day brings a new challenge.

From fragmented data sources to integrating complex systems, data engineers thrive on solving intricate puzzles.

Their work is crucial for turning raw data into actionable insights.

3. Innovation Enablers

The world’s first AI system for air traffic control?

That’s just one example.

Data engineers make groundbreaking innovations possible by ensuring data is clean, reliable, and ready for analysis.

4. Guardians of Data Integrity

Data is valuable, but only if it’s accurate.

Data engineers ensure quality and consistency, protecting organisations from costly errors.

They’re the gatekeepers of trustworthy data.

5. Educators and Mentors

Building the future doesn’t stop at technology.

Data engineers also shape the next generation of tech talent, sharing their knowledge and experience with aspiring professionals.

So, why should you consider becoming a data engineer?
→ It’s a role that combines creativity and technical skill.
→ There’s an evergrowing demand for data-driven solutions.
→ You’ll be at the forefront of innovation, where every project is an opportunity to make a significant impact.

Join the ranks of these unsung heroes and be part of a community that drives the tech world forward.

Are you ready to build the future?

Let’s discuss why data engineering should be your next step.

Drop a comment below to share your thoughts or ask questions about this exciting field.

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.

Data degrees are great, but here’s why data engineering skills might just be the game-changer you need.

In a world overflowing with data, what’s the biggest challenge?

Turning it into something valuable.

That’s where a data engineer steps in.

Here’s why mastering data engineering skills can outshine a traditional data science degree in today’s job market:

1. Demand for Data Engineers is Soaring

→ Companies need robust data pipelines and clean data before they can even start analysing.

↳ Without data engineers, data scientists can’t do their jobs effectively.

2. HandsOn Problem Solving

→ Data engineering focuses on building and optimising data systems.

↳ You’ll deal with realworld data challenges and provide solutions that have immediate impacts.

3. Versatile Skill Set

→ From coding and database management to understanding cloud services, data engineering equips you with a wide array of skills.

↳ It’s about the whole data ecosystem, not just analysis.

4. Foundation for Advanced Data Exploration

→ Before models can be trained, data must be prepped and organised.

↳ This means your work sets the stage for any advanced data science application.

5. Bridge the Gap Between Theory and Practice

→ While data science often leans towards theoretical aspects, engineering is grounded in practical application.

↳ You’re not just predicting the future; you’re building the road to it.

6. CostEffective Learning

→ You can learn data engineering through online courses, handson projects, and bootcamps.

↳ No need for a hefty degree investment.

7. Innovation at the Core

→ Data engineers are the architects of the digital age, creating systems that allow companies to innovate and grow.

↳ You’re paving the way for future technologies.

So, if you’re weighing options between a degree and diving into data engineering, consider what aligns with the current industry needs.

The world needs more data engineers.

Are you ready to be one?

Engage with me in the comments if you’re considering a career shift or just starting out in data engineering.

What’s your next step?

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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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.

Transform Your Business with Cutting-Edge Computer Vision and Edge AI Solutions | AI Specialist & Innovator

Experienced AI/ML Expert | Product Innovator | Strategic Leader

With over 9 years of expertise in Artificial Intelligence and Machine Learning, I have a proven track record of building impactful products and driving effective strategies that deliver tangible results. My work focuses on leveraging AI and ML to develop groundbreaking solutions, integrating coding in C#, Python, and other languages to meet diverse business needs.

► Driving Results: My success is rooted in my ability to collaborate with C-level leaders and stakeholders, assessing the suitability of AI to achieve their objectives, with a keen focus on ROI. I have consistently demonstrated my capacity to align AI initiatives with business goals, ensuring strategic value and practical implementation.

► Thought Leadership: As a thought leader and subject matter expert, I actively share my knowledge through informational sessions, blog posts, and webinars. I recently led an informational webinar that attracted a global audience of 150 attendees, where I explored the principles and applications of AI, highlighting its transformative potential across industries.

► Technical Excellence: My technical proficiency spans a wide range of tools and technologies, including Azure, TensorFlow, and Nvidia Jetson platforms. I specialize in developing and deploying AI models on edge devices, automating processes, and delivering multimodal solutions that incorporate image, video, and sensor data for comprehensive and efficient outcomes.

Whether leading teams, advising clients, or developing innovative AI-driven products, I bring a passion for technology and a commitment to excellence in everything I do.

Timothy Goebel

Brand control or speed why not both?

Most teams live with that trade-off. Keep brand tight. Ship fast. Today, there’s a smoother path.

Ryza Content now lets you lock brand or custom colors into your infographic prompts. Go to the Dashboard. Bottom-left, before you Submit Selections, choose Brand or Custom. Enter your hex codes, or use the color-picker to find what fits. Submit, make sure your theme or topic is clear, then hit Generate Output. Edit as you like. Generate the Infographic Prompt. Paste it into CoPilot, ChatGPT, or DALL·E. Your images render with your colors. You still keep creative control.

Second, your voice. Add up to five writing samples that you wrote. Ryza uses them to shape tone and phrasing. Every output, every edit, keeps training your voice. Retrain every 30 days so your voice doesn’t drift.

What changes when color and voice line up? Less back-and-forth. More brand trust. Faster cycles without sloppy content.

• Mechanism: Pre-set color parameters guide generators, reducing off-brand starts.
• Ops: Define theme/topic up front; it anchors structure and saves edits.
• Governance: 30-day re-training guards against voice drift across contributors.
• Scale: One prompt flows across tools where handoffs usually break consistency.

P.S.: Where do tighter color and voice save your team the most time? 

DM Timothy Goebel or Dr. Kruti Lehenbauer to setup a Demo!

#ContentStrategy, #BrandIdentity, #MarketingOps, #AI, #DigitalMarketing

AI Solutions Architect | Computer Vision & Edge AI Visionary | Building Next-Gen Tech with GENAI | Strategic Leader | Public Speaker

What if approvals fueled velocity?
Approvals often slow teams. Many reviewers, many opinions, many loops. That costs momentum when campaigns repeat.

Ryza Content flips the script. Approvals become reusable intelligence. The “why” behind a change trains the system. Next time, first drafts land closer to done. Review cycles shrink without losing standards.

This is how you move faster with governance, not around it.

• Build approvals into the flow. No side-channel edits or lost context.  
• Turn guidance into rules. What you approve becomes the baseline for future work.  
• Reduce variance across freelancers. Your voice grid guides them from line one.  
• Free leaders to edit for nuance, not basics.

Speed that respects the brand is the actual win.

Created By Ryza Content

DM Timothy Goebel or Dr. Kruti Lehenbauer to setup a Demo!

P.S.: When you approve work, what does the system learn?

#ContentOps, #BrandIntelligence, #MarketingOps, #AI, #Governance

Where does brand live in AI?

If brand lives only in people, AI breaks it. If brand lives only in AI, trust breaks it. The answer is a Brand Intelligence Layer that holds your voice, visuals, and approvals and makes them usable at speed.

Ryza Content is that practical layer. It turns hard-won human judgment into systemized guidance. Every team, every market, same voice. Faster work, safer work. You get speed with governance, not speed versus governance.

That shows up in pipeline. Intent captured earlier. Offers shipped on time. Consistency that converts.

• Centralize tone, visuals, and approvals as re-usable content intelligence.
• Use a content grid to align campaigns to segments and stages.
• Calibrate what AI drafts; keep humans for high-judgment calls.
• Track GTM cycle time; link improvements to pipeline created.

P.S.: Book a demo with Timothy Goebel or Dr. Kruti Lehenbauer.

#BrandIntelligence, #GoToMarket, #BrandGovernance, #B2BPipeline, #AI

If ideas aren’t scarce, what’s slowing content?

Decision fatigue kills speed. You’re picking topics, formats, hooks, and tone every single time. By evening, there’s no energy left for the post. So visibility slips. Then pipeline slips.

A repeatable system changes the math. You decide once, then execute fast with your voice intact. Strategy becomes a grid, not a guess.

• Lock a weekly rhythm: two insights, one proof, one offer. Predictable cadence builds audience trust and sales momentum.
• Use a format library: list, story, teardown, FAQ. Choose, then fill the blanks. No reinventing structure.
• Centralize approvals: pre-approve angles and phrases. Final review becomes “yes/no,” not a rewrite marathon.
• Tie posts to pipeline: each piece earns a next step DM, call, or demo link so content drives conversations.

Less friction. More output. Better pipeline. That’s the trade.

P.S.: See how Ryza Content turns ideas into posts in minutes. Book a demo: https://lnkd.in/gnhnd6Dk or Timothy Goebel, Dr. Kruti Lehenbauer

#ContentStrategy, #B2BMarketing, #FounderLedMarketing, #Pipeline, #RyzaContent

2-3x speed without brand risk?

That’s the promise when humans and AI share a layer. Teams that blend human insight with AI systems see 2-3x faster go-to-market without sacrificing brand integrity. The mechanism matters: reusable intelligence.

Ryza Content captures tone, visuals, and approvals so work doesn’t start from zero. The brand speaks once; the system scales it. Approvals shift from bottlenecks to lightweight checkpoints. The grid turns plans into shipped content.

That’s how speed and governance can work together and why pipeline grows.

• Reuse approved language blocks to cut drafting time.
• Automate low-risk approvals; reserve human focus for high stakes.
• Keep a living content grid to see gaps and move fast.
• Quantify cycle-time wins; forecast pipeline impact by launch timing.

P.S.: Contact Ryza Content or Timothy Goebel or Dr. Kruti Lehenbauer.:

#BrandIntelligence, #GoToMarket, #BrandGovernance, #B2BPipeline, #AI

A week of posts from one PDF?

Every marketer’s week starts the same:
Too many tabs. Too little clarity.
Speed wins the sprint voice loses the race.
Approvals drag. The grid gets messy.

Here’s the simple play I ran with Ryza Content

Go to the Dashboard.
Pick your platform, target persona, funnel stage, KPI, and brand voice.
Switch to PDF mode and upload a HubSpot Marketing Report.
Type the questions you want your posts to answer.
Hit Submit.

Five days of posts appear aligned to your persona and stage.
Each keeps your brand tone intact.
You edit, save, and download.
Then generate infographic prompts, download them, and schedule the week.

1) Mechanism: Question-driven extraction ties content to goals, not noise.
2) Control: Brand voice settings keep tone steady across every post.
3) Ops: Edit, Save, and Download keep approvals tight and visible.
4) Efficiency: One report fuels a week, cutting context switching and chaos.

One file powers a focused narrative.
One workflow respects approvals and speed.
No generic filler every post earns its place on the grid.

Teams using Ryza save 6+ hours per week while keeping full brand alignment.

Try it now upload your first PDF at https://ryzacontent.com

Stop wasting time on scattered drafts.
Build your first week of content in minutes, not meetings.

P.S. If your week’s content took 15 minutes instead of 5 hours, what would you re-invest that time in?

Reach out to Timothy Goebel or Dr. Kruti Lehenbauer for a demo or schedule a demo online

#ContentStrategy, #SocialMediaMarketing, #MarketingOps, #BrandVoice, #MarTech

Faster GTM without brand drift?

Speed usually taxes brand. Or brand slows speed. It doesn’t have to. Teams that blend human insight with AI systems see 2-3x faster go-to-market without sacrificing brand integrity. That’s the point of a Brand Intelligence Layer.

Ryza Content makes this practical. Your tone, visuals, and approvals get captured as reusable intelligence. Not lost in drafts. Not scattered across decks. The system remembers, so every team can work faster, on-brand, every time.

You get a clear plan. A content grid. One voice. Less swivel-chair.

Pipeline impact? Faster GTM means more timely campaigns, more qualified conversations, more dollars created. You gain speed and guardrails in the same move.

• Capture voice, visuals, and approvals once; reuse in every brief.
• Encode approvals as checkpoints; cut rework and review cycles.
• Build a content grid by audience, offer, and channel for speed.
• Measure cycle time to launch; tie gains to pipeline created.

P.S.: Book a demo of Ryza Content or with Timothy Goebel, Dr. Kruti Lehenbauer

#BrandIntelligence, #GoToMarket, #BrandGovernance, #B2BPipeline, #AI

Where does your content memory live?
If it lives in people, you lose it. If it lives in files, you forget it. Memory belongs in the system that makes the work.

Ryza Content captures what works as you work. Drafts, edits, approvals. It learns the patterns you approve, and carries them into the next piece. That is how repeatable campaigns stop wasting cycles.

It’s the difference between making content and building an engine.

• Every edit is signal. The system records why a line stayed or changed.  
• Approvals set the bar. Future drafts start above that bar, not below it.  
• Your plan updates itself. The voice grid tightens with every shipped asset.  
• Knowledge survives turnover. Teams scale without re-explaining the same tone.

When memory compounds, quality and speed move together.

Created By Ryza Content

DM Timothy Goebel or Dr. Kruti Lehenbauer to setup a Demo!

P.S.: If your lead writer left, would your voice stay?

#ContentOps, #BrandIntelligence, #MarketingOps, #AI, #Governance

Serving clients or staying visible what costs more?

Client work pays today. Visibility pays tomorrow. Most teams choose today, then wonder why pipeline feels light next quarter. The problem isn’t ideas. It’s the time and approvals needed to turn those ideas into publish-ready content at speed.

When every post starts from zero, momentum dies. You rebuild your voice, your angle, your format every time. That’s costly context switching. And your brand suffers.

The fix is structure, not inspiration. A simple, repeatable system that reduces decisions, protects your voice, and converts raw thoughts into a week of posts—fast.

• Build a voice grid: tone, stance, phrases, and “never say” lines that keep content on-brand without heavy approvals.
• Set three content pillars tied to pipeline stages: problem, proof, and product. Each post maps to one, clearly.
• Bank pre-approved angles and snippets. Reuse what works. Edit once, deploy everywhere.
• Batch ideas to outputs in one workflow: capture, select format, draft, quick approval, schedule.

Action beats intention. Ryza Content gives you the system so consistency becomes automatic. Pipeline follows consistency.

P.S.: Book a demo to see the workflow: https://lnkd.in/gnhnd6Dk Or Timothy Goebel, Dr. Kruti Lehenbauer
#ContentStrategy, #B2BMarketing, #FounderLedMarketing, #Pipeline, #RyzaContent

Losing tone between drafts and delivery?

That gap burns time and trust. Drafts drift. Reviews balloon. Deadlines slip. Teams need a system that carries the voice from first line to final asset.

Ryza Content captures your voice, visuals, and approvals as reusable intelligence. Every draft starts with the right tone and visual cues. Approvals are not ad hoc; they’re remembered and applied. The handoff from strategy to content to sign-off tightens.

Less rework. More consistency. Faster speed to market. That’s pipeline math.

• Create a shared tone library that informs every brief and draft.
• Lock visual decisions into templates; avoid last-mile deviations.
• Define approval checkpoints that match risk, not rank.
• Measure rework rate; reinvest hours into programs that drive pipeline.

P.S.: Book a demo: Ryzacontent.com

#BrandIntelligence, #GoToMarket, #BrandGovernance, #B2BPipeline, #AI

When drafts become brand intelligence?
A draft is more than words. It’s a record of decisions. What stayed. What changed. Why it mattered for your audience and your plan.

Ryza Content turns that record into brand intelligence. It captures tone, structure, and message DNA automatically. So each new draft starts informed by every approved one.

Over time, your voice sharpens. Your team moves with clarity. Your grid holds the line.

• Drafts feed the model of your brand. Learning builds inside the workflow.  
• Edits are not waste. They become reusable guidance for future pieces.  
• Campaign assets circulate as patterns, not just files. Reuse becomes reliable.  
• Consistency scales across markets and formats without heavy lift.

This is how operations create advantage, not just output.

Created By Ryza Content

DM Timothy Goebel or Dr. Kruti Lehenbauer to setup a Demo!

P.S.: Where in your process does learning actually stick?

#ContentOps, #BrandIntelligence, #MarketingOps, #AI, #Governance

Are your approvals reusable intelligence?

Most teams "approve" and forget. That wastes speed and judgment. Approvals should compound. When your brand calls, edits, and sign-offs get captured, the system learns. The next draft starts right. The review shrinks.

This is the Brand Intelligence Layer in action. Humans set the voice. AI scales it. Ryza Content turns approvals into a living asset teams can pull on-demand. Governance moves from gatekeeping to guidance that accelerates work.

Result: fewer back-and-forths, more on-brand content, faster market moves. And a cleaner path from plan to pipeline.

• Turn past approvals into ready-to-use patterns for new content.
• Standardize tone and visuals; reduce variance across teams.
• Use a shared content grid to align every brief with goals.
• Track time saved per asset; attribute to pipeline velocity.

P.S.: Book a demo with Ryzacontent.com or reach to Timothy Goebel

#BrandIntelligence, #GoToMarket, #BrandGovernance, #B2BPipeline, #AI

This artist built their entire reflection post inside Ryza Content .
They used our question-driven extraction and voice refinement loop to shape a story that connects art, strategy, and emotion.

It’s a great example of what happens when human creativity meets structured AI guidance.


#RyzaContent #BrandVoice #AIforCreatives #MarketingTools

Oil Paint Artist | Owner at Lynn's Art Shop

Chase reach—or build red-balloon recall?
An artist note on marketing:

Two girls on the Riverwalk. One in yellow, clutching a red balloon. A circular bridge, a bold red sculpture, reflections that turn the ordinary into a small spell.

 As I was painting this, I realized something vital given my own background in marketing from eons ago. This is not just a painting. It’s a blueprint for marketing that lasts.

Tension: Most teams optimize for speed and volume. But memory—the kind that makes people come back, forms around a few distinct cues repeated with care. In the scene, the eye anchors to red, travels through the bridge’s opening, lingers in the shimmer. That’s attention architecture and the girls. Not more elements but fewer, placed intentionally.

Insight: Build creative like this walkway. Pair emotion with navigation. Give people one anchor (your “red balloon”), one path (your “bridge”), and room for wonder (your “sky”). When your brand assets walk hand-in-hand, useful and human you turn impressions into shared journeys.

 Action:
 - Pick a living asset (color, shape, object) and commit. Apply it in thumbnails, headers, packaging, onsite micro-interactions.
 - Design a focal hierarchy: primary subject, secondary anchor, space to breathe. Say more by showing less.
 - Map the journey as scenes: arrival (anchor), crossing (bridge), resonance (reflection). Align creative and UX to the same beats.
 - Treat community content as “reflections”—remixes that mirror your anchor, not random posts.

 • Distinctive Asset System: Name 1–2 cues (e.g., one color + one form). Lock usage rules and variant boundaries to prevent drift.
 • Focal Hierarchy: For every creative, declare a single subject, a single anchor, and negative space. Remove competing highlights.
 • Journey Beats: Storyboard scroll → click → dwell as three scenes. Ensure the same asset threads through all three.
 • Ops Ritual: Build a lightweight asset library with tags for anchor/bridge/reflection; add pre-flight checks for consistency.

 P.S.: If your brand had to walk the Riverwalk tonight, what’s the one cue people would still remember tomorrow?

This post was created using Timothy Goebel's Ryza Content App 

 #BrandStrategy, #CreativeOperations, #ExperienceDesign, #PlaceBranding, #NarrativeIntelligence

Rebuilding your voice daily worth the pipeline hit?

Inconsistent voice confuses buyers. They hesitate. Confusion delays deals. Your brand should sound the same on Monday and Friday, in email and on LinkedIn. That requires guardrails you can trust, not gut feel.

Protect the voice. Protect the pipeline.

• Create a voice grid: values, cadence, sentence length, and phrasing do/don’ts. Your team writes “as brand,” not “as themselves.”
• Maintain a proof library: case lines, client objections, and outcomes. Plug proof into posts without hunting.
• Standardize calls-to-action by intent: educate, engage, convert. Readers know what happens next.
• Run a lightweight approval step: owner signs off on voice and claim accuracy. Edits shrink. Speed rises.

Ryza Content keeps your voice intact while scaling output. Clear voice. Clean pipeline. Less risk.

P.S.: Want the voice grid template and workflow? Book a demo: https://lnkd.in/gnhnd6Dk Timothy Goebel or Dr. Kruti Lehenbauer
#ContentStrategy, #B2BMarketing, #FounderLedMarketing, #Pipeline, #RyzaContent

So many have asked who Ryza is built for.

Here are the 10 ICP profiles that get the biggest lift from Ryza:
	1.	Solopreneur consultants
	2.	Business owners
	3.	B2B founders and startup teams
	4.	Marketing managers
	5.	Content creators & influencers
	6.	Agencies handling multiple clients
	7.	Sales & RevOps teams
	8.	HR/talent/employer branding
	9.	Legal/compliance-heavy teams
	10.	IT/data/engineering teams translating complex documents

Big updates are coming, prices will adjust, and anyone on a full-year subscription is locked into today’s rate.

If Ryza Content  is on your radar, now’s the moment to secure current pricing before the rollout.

Busy or visible what’s fueling your pipeline?

Small teams don’t lack ideas. They lack capacity. Delivery eats the day. Invoicing eats the night. Content slips. Visibility fades. Pipeline stalls.

The pattern is familiar. You post in bursts. Then silence. Each restart burns time and voice. You start from scratch instead of from a system.

This isn’t a creativity problem. It’s a systems problem.

The unlock is a macro content operating system. One that reduces decisions, stabilizes voice, and turns rough thoughts into publish‑ready posts at speed. Every week. Without draining the team.

Think less “daily grind,” more “repeatable pipeline.” Capture raw ideas once. Route through a voice-safe grid. Approvals gate. Publish on cadence. The brand shows up. The market remembers. Your pipeline fills.

• Build a weekly grid: topics, formats, owners, deadlines. Decisions made once, reused every cycle.
• Store a voice library: tone, phrases, do/don’t rules. Cuts revisions and protects brand.
• Separate capture from polish: leaders drop notes; the system turns them into content.
• Add an approvals gate: one decision-maker, clear SLAs, no last‑minute rewrites.

P.S.: Book a demo to see the content operating system in action: https://lnkd.in/g78xUQNv Timothy Goebel or Dr. Kruti Lehenbauer
#ContentOperations, #BrandVoice, #SMBMarketing, #B2BGrowth, #Pipeline

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Dr Emmanuel Ogungbemi

Timothy Goebel

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Performance ScoreTimothy Goebel's LinkedIn Performance

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taplio

The Battle

Dr Emmanuel Ogungbemi

Timothy Goebel

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 ScoreTimothy Goebel's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreDr Emmanuel Ogungbemi's LinkedIn Performance