Unlock Data-Driven Insights by Dr Dave Braendler

Unlock Data-Driven Insights

Dr Dave Braendler

Contact for pricing

About this service

Summary

We offer tailored data analysis services that turn your messy, disconnected data into clear, actionable insights. What makes us unique is our ability to bridge the gap between analysis and automation — by structuring and understanding your data first, we lay the foundation for powerful, AI-driven workflows. It’s the first step toward unlocking automation that’s smart, scalable, and aligned with your business goals.

Process

Discovery & Exploration

We start with a strategy session to understand your goals, challenges, and data environment. 👉 Outcome: Clear objectives and a mapped-out plan for what insights or automations to prioritize.

2. Data Audit & Preparation

We gather and assess your existing data sources, clean the mess, and align formats for consistency. 👉 Outcome: A high-quality dataset that’s ready for deep analysis and future automation.

3. Exploratory Data Analysis (EDA)

We surface trends, patterns, gaps, and opportunities through visual and statistical analysis. 👉 Outcome: Key business insights and clarity on what can be automated or optimized.

4. Insight Reporting

We deliver user-friendly reports and dashboards that turn your data into decisions. 👉 Outcome: You get clear answers — not just charts — with actionable recommendations.

5. Automation Blueprint

We translate insights into process maps and identify where AI automation can add value (e.g., reporting, scheduling, classification, alerts). 👉 Outcome: A custom automation roadmap powered by your own data.

6. AI Workflow Implementation (Optional Add-On)

We build smart, integrated workflows using tools like N8N or custom AI models — from lead scoring to report generation. 👉 Outcome: Automated systems that save time, reduce manual work, and scale effortlessly.

FAQs

What types of data can you work with?
We can handle a wide variety of data, including spreadsheets, databases, cloud-based platforms (like CRMs or ERPs), PDFs, APIs, and even unstructured text. If your data is messy or fragmented, we specialize in making sense of it.
How long does a typical engagement take?
It depends on your data complexity and goals, but most clients start seeing value within 2–4 weeks. We offer short engagements to get quick wins, as well as longer-term partnerships.
We already have analysts—why would we need your service?
In-house analysts are great for reporting and insights. We go further by laying the groundwork for automation. We help structure and streamline your data so your team can spend less time cleaning and more time innovating.
How is this different from traditional business intelligence (BI) tools?
Most BI tools focus on dashboards and reports. We go beyond that by preparing your data for advanced, AI-powered workflows—like automatic report generation, personalized customer journeys, or smart decision-making systems.
Can you integrate with our existing tools and systems?
Yes. We focus on working with your existing tech stack, whether it's Excel, Google Sheets, SQL databases, Notion, Airtable, or custom platforms. Integration is part of the process.
Do you offer automation as part of your service?
Yes, but only after the data is structured correctly. This creates a rock-solid foundation for automation so it doesn’t break or produce inaccurate results later on.
Is this a one-time service or ongoing support?
It can be both. Some clients want a one-off analysis and setup, while others prefer ongoing optimization and support as their data and needs evolve.
What’s the ROI of investing in this kind of service?
By cleaning and structuring your data early, you reduce wasted time, improve decision-making, and unlock scalable automation. Many clients see significant time and cost savings almost immediately
Will I need to hire developers to maintain what you build?
Not necessarily. We prioritize no-code/low-code and AI-enhanced tools that your team can manage. We’ll also train your staff if needed.

What's included

Exploration Phase
Discovery session to understand your goals, pain points, and success metrics Review of available data sources and business processes Initial hypothesis mapping: what are we trying to uncover or improve? Agreement on key questions the analysis should answer
Data Audit & Preparation
Evaluation of data quality, consistency, and completeness Cleaning and standardization of raw data Handling duplicates, null values, and formatting inconsistencies
Data Integration
Consolidation of data from multiple sources (e.g., CRMs, sales systems, support platforms) Creation of a unified data model tailored to your objectives
Data Analysis (EDA)
Identification of trends, outliers, patterns, and potential correlations Visual summaries of key metrics and behaviors Preliminary insights and questions surfaced
Insight Reports
Clear and concise visual reports showing meaningful findings Business impact breakdown — what does this insight mean for you? Prioritized recommendations for next steps or strategy shifts
Custom Dashboards
Interactive dashboards with real-time or regularly updated data KPIs and filters tailored to your team’s needs

Skills and tools

Data Analyst

Data Modelling Analyst

Data Scientist

Data Analysis