We teach your data to earn money
We help companies get the most out of their data and turn it into clear results. We take care of collection, integration, analysis, visualization, and AI that will take your business further.
Case studies
WHY
Guide to transforming into a data-driven company
We demonstrate that data has the power to transform companies into efficient and customer-focused organizations.
HOW
We connect data deployment, data science, and AI with practical business needs to create real value.
WHAT
Data engineering and integration in the Microsoft Azure ecosystem.
Predictive models, BI reporting, and customized AI systems for effective decision-making.
Value skew
We are experienced data guides. We deliver end-to-end projects with clear goals, focused on the client's business and measurable results.
Our clients' stories Case studies
Data warehouse for management and reporting (on-premise)
ERV - European Insurance Company
For the largest travel insurance company in the Czech Republic, we built a central data warehouse as a single source of truth for management, business, and regulatory reporting - fully on-premise in the Microsoft stack.
- 15 comprehensive dashboards across domains
- Processing hundreds of GB of data
- First key reports available within 2 months of resource availability
- Data model for ad hoc analyses with data validity and consistency checks
Online segmentation of website visitors for improved campaign performance AAA Auto
For AAA Auto, we used web behavioral data to create a visitor segmentation that distinguished actual buyers from the majority of casual visitors. This provided the marketing team with a clearly definable audience for performance campaigns and enabled more precise investment decisions.
- 10 distinct visitor segments based on purchase intent
- Analysis of over 300 web behavior attributes
- Identification of segments with the highest business potential
- Project ROI > 5 within 180 days thanks to more precise campaign targeting
Detection of Impression Losses in Sklik Ad Serving Zones
Seznam.cz
For Seznam.cz, we designed and implemented a tool to detect anomalies in Sklik’s ad delivery zones, which automatically identifies impression outages, assesses their severity, and alerts users to the problem in a timely manner. The solution leverages two years of historical data and combines multiple detection methods to ensure reliable performance across thousands of zones and various contexts within the advertising ecosystem.
- Monitoring of nearly 10,000 ad slots daily
- Detection of sudden drops and zero impressions in real-time
- Combination of multiple detection methods to reduce noise and improve reliability
- Faster problem identification and better protection of ad revenue
We are Guides to the world of data We are here for you, we have team spirit and enthusiasm
At Data Mind, we believe that data has enormous potential to change the way companies operate and make decisions. Since 2009, we have been focused on helping organizations extract real value from their data. We are a team of enthusiastic professionals in the fields of Data Science, Data Engineering, and Artificial Intelligence who strive to deliver not only technical solutions but also strategic approaches. Our mission is simple: to make data more accessible and useful for every client.
Want to go deeper? Dive into our knowledgebase
Customer 360
Creating a unified Customer 360 profile is not just a marketing goal, but a complex architectural challenge. This article analyzes the necessary transition to Data Lakehouse architecture in the Microsoft Fabric and Azure ecosystem. Learn how to build a modern data platform that serves as a robust foundation for advanced cloud analytics and hyper-personalized communications using AI and LLM.
RAG over company data
Want to deploy generative AI on top of your company's own know-how without the risk of hallucinations? This technical deep dive into RAG architecture shows that AI success stands and falls with quality data engineering and data architecture. Explore how to build a modern data platform for AI based on Microsoft Fabric and Azure Data Lakehouse and how to overcome the challenges of data vectorization, security, and transition to a production enterprise environment.
Propensity to Buy
How can raw data be transformed into accurate predictions of purchasing behavior? The Propensity to Buy model represents the gold standard of data monetization, but its success stands or falls on the chosen architecture. In this article, we will explore the technical background of implementation in Microsoft Fabric and Azure environments. Learn how to leverage Data Lakehouse principles, advanced machine learning, and generative AI to identify customers with the highest potential—and how to orchestrate it all in a modern, scalable infrastructure.
Not sure if our help is right for you?
Not sure if you need our help? We will be happy to discuss your needs, data, and goals with you, with no obligation. Together, we will assess whether and how we can be of benefit to you—with the utmost professionalism and without unnecessary pressure.
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