DataMinq

Data Architecture Advisory

Stop Burning Margin on Data Chaos. Build a Profit Machine.

Engineer enterprise-grade data architecture and automated pipelines for scale-ups. No spreadsheet firefighting. Just resilient infrastructure designed to optimize EBITDA and protect net profit.

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Grzegorz Bednarski

Who's behind DataMinq

Grzegorz Bednarski

Hi, I'm Grzegorz — I help companies that outgrew the way they work with data.

A company grows. One new hire joins, then another — everyone starts building their own spreadsheet, their own dashboard, their own version of the numbers. At some point nobody's looking at the same figures anymore, and decisions get made on guesswork instead of facts. That's what I do: I clean up that flow of information so the board, marketing, and operations are all looking at the same company. DataMinq is the name I do this under — but behind every audit, call, and implementation, it's me. I start with the board and the numbers, technology comes second. If the work doesn't translate into a financial result, there's no point doing it.

Reach out to me directly on LinkedIn

WHO I'VE WORKED WITH

TheGig.AgencyWarsaw-Apartments Sadyba WilanówKamrenoTheGig.AgencyWarsaw-Apartments Sadyba WilanówKamreno

HOW I HELP

Architecture Clarity

Define data flows, ownership, and model boundaries so teams can move faster with confidence.

Measurable Outcomes

Tie analytics initiatives to KPI improvements and executive-level reporting from day one.

Automation at Scale

Reduce manual operations with robust pipelines and AI-enabled operational workflows.

FROM THE BLOG

Latest Articles

Fresh practical notes on data architecture, analytics strategy, and operational automation.

SELECTED RESULTS

Case Studies Showcase

Proof over promises: compact case snapshots built around business context, technical intervention, and measurable financial impact.

How We Restored Trust in Customer Sentiment Analysis and Added New Reporting in 2 Weeks

Marketing

How We Restored Trust in Customer Sentiment Analysis and Added New Reporting in 2 Weeks

TheGig.Agency

The agency regained confidence that the numbers it shows clients are accurate. Analysts stopped losing time to manual checks and crashing files, and now focus on drawing insight from ready-made reports of the most common customer terms. The whole project — from bug fixes to new features — was completed in two weeks, and the agency walked away with a tool it can trust for every future client campaign.

How an Agency Stopped Stitching Data Together as a Full-Time Job

Marketing

How an Agency Stopped Stitching Data Together as a Full-Time Job

TheGig.Agency

The team took back control of its data instead of losing days piecing it together. Daily, weekly, and monthly reports now build themselves, and every client meeting starts with facts, not guesswork. Managers now compare sales and traffic trends across any time period in seconds, instead of days of manual work. The data simply works — and the team can finally focus on strategy.

Centralizing CSR Platform Operational Data

Services

Centralizing CSR Platform Operational Data

The Purpose Platform

The deployment of the new data architecture permanently unlocked the platform's operational and financial potential. The board has regained full control over performance metrics, and the system seamlessly handles peak loads during rapid scaling. Financial results and engagement statistics are now fully transparent and updated in real time.

Social Proof

Client Testimonials

Feedback from teams that implemented data architecture and automation with us.

”

Having worked with Grzegorz for a couple of years, I have to say he is an excellent professional. He helped me understand the company's project management process and introduced me to useful tools. I am impressed with his work ethic and communication skills. His skills in programming languages are very developed. I would recommend him to everyone who wants to receive a clear code in a short time!

Krystian Rosłon

Krystian Rosłon

Project Associate • CERN

”

I highly recommend Greg as a software engineer whose technical expertise and attention to detail consistently exceed expectations.

His ability to develop efficient backend solutions and seamlessly collaborate with cross-functional teams has been crucial to the success of our projects.

Grzegorz approaches challenges creatively and precisely, quickly identifying solutions and implementing them effectively. He remains calm under pressure and consistently meets deadlines without compromising quality.

His dedication, problem-solving skills, and collaborative spirit make him an invaluable asset to any project or team.

Taylor Hart

Taylor Hart

Data Engineer • Ads.com

”

I recommend Grzegorz as an expert in the field of Business Intelligence and Artificial Intelligence, based on my knowledge of his competencies and skills. Grzegorz demonstrates not only excellent technical abilities but also innovation and a passion for continuously expanding his knowledge. His commitment and expertise make him a valuable asset to any organization in the fields of BI and AI. How he can help?:

  1. Data Collection and Aggregation: · Designing tools for collecting data from various sources. · Creating APIs and bots for automating data collection processes.

  2. Data Science and Machine Learning: · Data analysis, predicting trends, and recognizing patterns. · Creativity in the field of "artificial creativity" and object recognition.

  3. Data Delivery and Automation: · Create efficient systems for data distribution. · Automating processes, enhancing efficiency and productivity.

Renata Kamińska

Renata Kamińska

Founder • Kamreno Ltd

”

I wholeheartedly endorse Grzegorz as an outstanding software engineer, whose remarkable ability to swiftly adapt to emerging technologies and innovate in problem-solving has profoundly benefited our projects. Grzegorz not only brings a wealth of technical proficiency to the table but also excels in teamwork and communication, proving himself to be an indispensable member of any team. Additionally, his consistently positive attitude and exceptional work ethic have left a lasting impression.

Sebastian Paszek

Sebastian Paszek

Co-founder • The Soundproof Ltd

”

Throughout his tenure, Grzegorz made significant contributions to numerous projects for our clients. His profound expertise and understanding of backend technologies greatly benefited our team.

Grzegorz consistently demonstrated readiness to address clients' questions and concerns, alongside his remarkable ability to resolve any challenges encountered during the development process, even under pressing deadlines. His commitment to problem-solving not only enhanced our operational efficiency but also fortified trust-based relationships with our clients. These qualities made him a valuable member of the team.

Grzegorz's technical skills, combined with his dedication to client satisfaction, make him a standout professional.

Mateusz Kupczyk

Mateusz Kupczyk

CEO • Brival Sp. z o.o.

”

I had the pleasure of working closely with Grzegorz on several backend software solutions for various clients.

Greg’s ability to design, develop, implement, and improve complex software was integral to these projects’ success. I knew that if Greg was tasked with something, it would always be completed properly and on time- regardless of complexity.

He consistently delivered high-quality code, could quickly troubleshoot and resolve issues, and kept teams well-organized and on-track.

In short, Grzegorz is a highly reliable and capable developer, and any team will be better with him on it!

Mathew Arrington

Mathew Arrington

Marketing Operations • The Gig Agency

Data Operations Calculator

Estimate your EBITDA leak from manual data operations

Answer three inputs to estimate how much spreadsheet-heavy reporting and data errors cost you each year.

Estimated annual hidden data debt cost

EUR 1,350,400

This estimate combines manual reporting labor cost and annual reporting error impact. A full technical audit typically reveals additional hidden leak points.

Get a free technical recovery blueprint

Executive FAQ

Answers to high-stakes data architecture questions

What's the difference between working with me and hiring a software house or a full-time developer?

The difference is in where I start. For a developer, the goal can end up being the code itself. For me, code is a cost, and solving the business problem is the asset — I don't write code for its own sake, I write it so something specific actually works better.

I start with leadership, not with technology: we work out together how a given change translates into revenue, cost, and margin. If it can't be measured, it's not worth doing. Only then do we move to implementation. My clients don't pay me for hours of coding — they pay for their data simply working, and for a solid foundation under decisions they need to make anyway.

Our company is growing fast, but operating costs are eating our margin. How can data architecture change that?

This is the classic profitability ceiling that fast-growing service businesses, PropTech, and hospitality companies run into: the more you scale, the faster fixed costs from manual work and manual process handling pile up.

I come into the organization and automate the flow of information to eliminate manual spreadsheet work, human error, and reporting bottlenecks. The logic is simple: less manual work means higher margin. The goal is to turn data chaos into something predictable, so the company can grow without having to hire proportionally more people just to keep up.

Our e-commerce business/agency runs on Excel and everything "sort of" works. Why do we need a single source of truth?

That "sort of" holds up right until the day a spreadsheet error burns through an ad budget, or the day the one person who kept the entire data structure in their head leaves the company.

I've seen this repeatedly in performance agencies: the team loses two days a week manually reconciling sales from Shopify or Amazon against ad spend from Meta and Google Ads. That's not a minor inconvenience — it's a real, hidden financial loss that just doesn't have its own line in the budget.

I design and build a central data hub that pulls all of this together automatically, with no manual work — an environment that keeps the numbers accurate on its own and lets leadership optimize spend based on figures they can actually trust, instead of a gut feeling.

We're planning to sell the company (Exit / M&A) in the next 12–24 months. Is it worth investing in cleaning up our data now?

Absolutely — and this is one of the moments where messy data costs you in the most literal way possible, because it shows up directly in the price.

During Due Diligence, funds and strategic investors go through reporting systems very carefully. If they find inconsistencies — different numbers in different departments, data scattered across spreadsheets, no single source of truth — that becomes a hard argument for them to push the deal price down.

In these situations, I come in and put those information assets in order before someone on the other side of the table does it for you. I turn chaotic data into something an investor can actually check and trust — which directly protects the valuation.

What does working with me look like, and what happens after the project ends?

I work in two modes, depending on where the company is in its journey.

The first is a build project — starting with an audit, then designing the data architecture, then automating processes and, where it makes business sense, using AI. I run this personally, from the first conversation with leadership through to the final stage of implementation — whether the technical build itself is done by my team or the client's own IT department depends on the project, that part is secondary.

The second is ongoing support after the build. I don't leave anyone alone with new technology — after the main project, I offer continued support, monitoring, and optimization, so what we built keeps working and doesn't start drifting as the company keeps growing.

Ready to recover margin hidden in data operations chaos?

After the scan, we map your technical bottlenecks and prepare an implementation blueprint tied to EBITDA outcomes, not generic consulting slides.

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