Jack Walker

We bring qualified leads for your business through Facebook ads and organic social media marketing | Helped 50+ clients with profitable paid campaigns (5x ROI) | Award-winning digital marketing agency🚀

Do your staff spend hours trying to create social media content to generate sales/ leads? 

Do you want to make more money from social media? 

Are the posts not getting engagements? 

Do you want your posts to go out to targeted profiles!?  

Yes it’s possible!!! 

We have your solution for you! OptiModo Marketing has the answers to your problems!

We create custom social media marketing projects for YOU, focused on your ROI (Return On Investment) making sure you get the most out of your marketing!

Did you know the average company spends an hour a day posting on their social media channels? That means you have spent roughly (if you pay them £15 an hour) £450 a month on social media. 

Our social media management packages start at £219 saving you time and money. 

We also make sure your content is high quality and being seen by your target market. 

The best thing about us is THERE ARE NO LOCK IN CONTRACTS! We will send you a report after each month, and if you are not happy (we are sure you will be) you can leave!

Not only do we do social media management, we can make sure your website is up to date, make sure it is working to its potential. We can design, build or modify your website to your needs, with your budget.

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What can we help with?
Social Media Marketing
Social Media Management
Social Media Content
B2B Leads
B2C Leads
Website Design
Website Maintenance 
And much more!

Managing Director

Enabling businesses to unlock their full potential using social media, websites and email marketing.

Stopping you SPENDING money on your marketing and helping you MAKE money marketing.

Data & AI Enthusiast | Attracting High-Quality Opportunities Through Personal Branding & Smart Outreach | German Expat Mastering Dutch Life

I’m Francie (you pronounce it like “fancy”) :P, the Head of Global Sales Development who wants to turn the bad image of SDRs around through personal branding, content creation, and smart outbound. 

If you’re curious, here’s a quick rundown:

👋 Who am I? 
A bubbly, face-to-face extrovert. My background? Everything from big corporations to tiny AI & Data startups. Now, I’m on a mission to translate that energy into driving growth online. 

🤝 What do I do? 
I help businesses create more high-quality opportunities using savvy outbound strategies, lead-generating content, and genuine personal branding. Fed up with outdated tactics? You’re in the right place!

Francie Kastl

🚀 dbt Labs+ Apache Flink - Now for Batch and Streaming Jobs

Real-time data teams, this one’s big.

We’re excited to introduce the new DBT connector for Flink, making it easier than ever to deploy both batch and streaming jobs directly from your DBT workflows.

That means:
⚡ Define transformations once
 ⚡ Deploy to Flink for true streaming or batch execution
 ⚡ Keep your data models versioned, tested, and production-ready
 ⚡ Eliminate custom pipeline glue code

This is about more than convenience - it’s about unifying your transformation layer. No more separate tooling for batch vs. streaming. No more operational friction when moving from development to low-latency production pipelines.

Now you can combine DBT’s developer-friendly modeling experience with Flink’s stateful stream processing engine - giving you scalable, fault-tolerant pipelines built for high-throughput, event-driven architectures.

Build once. Run anywhere. Stream at scale.

And as a side note, Flink also supports Unity Catalog integration and Delta Lake sync, making governance and lakehouse alignment seamless across your real-time data stack.

Curious to see it in action? Let’s talk about how this can simplify your streaming architecture.

If your “real-time AI” runs on batch data from yesterday, we need to talk. | Head of Global Sales Development | German potato enjoying the vibrant Netherlands :)

Was a bit quiet on my profile for quite some time, but all for a very good reason:

I was busy hiring our new members for our SDR/growth team and onboarding them. All of them are in Barcelona and I am in the Netherlands, so I am kinda missing out on the f2f every day - so I wanted to make our first in-person meeting special.

First thought that came into my mind was... let's go skydiving :D ok, a bit too extreme maybe, so let's do it inside haha

Luckily, we work for a company, Ververica | Original creators of Apache Flink®, that supports ideas like this, and I could surprise my team with this activity. 

Arriving at the location, the smiles got bigger and bigger, but for some also the nervousness :D 

So happy to have spent this day with you legends Debi Besleyen Esin, Conor Walls, Zeynep Ozer and Lisa Osti, and that you are making our SDR team so great!

Most lakehouse architectures today still operate in 𝗯𝗮𝘁𝗰𝗵 𝗺𝗼𝗱𝗲.

Data lands in a 𝗕𝗿𝗼𝗻𝘇𝗲 𝗹𝗮𝘆𝗲𝗿, pipelines run every few hours, and eventually 𝗦𝗶𝗹𝘃𝗲𝗿 and 𝗚𝗼𝗹𝗱 datasets are refreshed for analytics.

But if your business operates in real time, this model creates a gap between 𝘄𝗵𝗲𝗻 𝗲𝘃𝗲𝗻𝘁𝘀 𝗵𝗮𝗽𝗽𝗲𝗻 and 𝘄𝗵𝗲𝗻 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗮𝗿𝗲 𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲.

This is where the concept of a Streaming Lakehouse comes in. Our work here Ververica | Original creators of Apache Flink® is around this 𝗦𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴 𝗟𝗮𝗸𝗲𝗵𝗼𝘂𝘀𝗲, 𝗮 𝗹𝗼𝘄-𝗰𝗼𝘀𝘁 𝘀𝘁𝗿𝗲𝗮𝗺/𝗯𝗮𝘁𝗰𝗵 𝘂𝗻𝗶𝗳𝗶𝗲𝗱 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵.

A 𝘀𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴 𝗹𝗮𝗸𝗲𝗵𝗼𝘂𝘀𝗲 turns the traditional batch lakehouse into a 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀𝗹𝘆 𝘂𝗽𝗱𝗮𝘁𝗲𝗱 𝗱𝗮𝘁𝗮 𝘀𝘆𝘀𝘁𝗲𝗺, where every layer evolves incrementally as new events arrive.

Instead of recomputing large datasets repeatedly, we process 𝘀𝗺𝗮𝗹𝗹 𝗶𝗻𝗰𝗿𝗲𝗺𝗲𝗻𝘁𝗮𝗹 𝘂𝗽𝗱𝗮𝘁𝗲𝘀. This keeps data fresh while significantly reducing compute costs.

Let’s look at a financial platform example.

𝗕𝗿𝗼𝗻𝘇𝗲 𝗹𝗮𝘆𝗲𝗿
Raw events continuously arrive from operational systems such as:
• payment transactions
• card activity
• account updates
• transfers
• mobile banking events
• market data feeds

These events are ingested in real time into the Bronze layer, forming the raw data foundation of the lakehouse.

𝗦𝗶𝗹𝘃𝗲𝗿 𝗹𝗮𝘆𝗲𝗿
As new financial transactions arrive, they are incrementally enriched and merged with customer information, account data, and historical activity.

This continuously builds and updates a 360° customer financial profile.

Instead of rebuilding this profile periodically in batch pipelines, the system updates the state event by event as new transactions happen.

This enables capabilities like:
• real-time fraud detection signals
• continuously updated customer risk profiles
• transaction monitoring and compliance checks
• real-time financial insights for customers

𝗚𝗼𝗹𝗱 𝗹𝗮𝘆𝗲𝗿
The Silver layer then feeds continuously updated business aggregates.

For example:
• total transaction volume per region
• payment activity by merchant category
• real-time liquidity metrics
• revenue and fee aggregates
• fraud detection metrics

These Gold tables evolve incrementally as new transactions flow through the system, meaning dashboards, analytics systems, and AI models always operate on fresh financial data.

The key idea behind the streaming lakehouse is data continuity.

Raw financial events → enriched customer profiles → business aggregates
𝗮𝗹𝗹 𝗲𝘃𝗼𝗹𝘃𝗲 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀𝗹𝘆 𝘄𝗶𝘁𝗵𝗶𝗻 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲. The lakehouse stops being a system that updates every few hours.

It becomes a living data platform where insights evolve as transactions happen.

Lambda Architecture was supposed to be a temporary fix.

That was 10 years ago.

Apache Fluss (Incubating) finally kills it. 

Streaming storage that's fast like Kafka, queryable like a Lakehouse, and doesn't require two separate pipelines held together with duct tape.

One layer. 

No trade-offs. 

No therapy required.

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Francie Kastl

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The Battle

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