Frequently Asked Questions about Data Engineering and Hockey Analytics

Data engineering consulting rates vary depending on project complexity and duration. We offer flexible solutions from $10/month data stacks to enterprise implementations. Contact us for a tailored quote based on your specific needs.

Hockey analytics uses data to improve team performance through analysis of players, tactics, and opponents. Our team specializes in building real-time dashboards that track everything from zone entry success rates to penalty kill efficiency. This can improve penalty kill performance by up to 25%.

With cloud-native tools and serverless architecture, you can create a scalable data stack very cost-effectively. We use tools like Snowflake (free tier), dbt Cloud, and Streamlit to create complete solutions. See our project showcase for detailed guides.

We work primarily with ChatGPT API, Claude API, and Copilot for various types of automation. From prompt engineering in Notion to LLM integration with ServiceNow. Our expertise includes both technical implementation and workflow optimization.

We offer both remote consultation and on-site work. Many data engineering projects can be completed entirely remotely, while hockey analytics often requires closer collaboration with coaching staff.

A basic hockey analytics dashboard can be ready in 2-4 weeks, while advanced solutions with real-time data and predictive analytics take 8-12 weeks. Timeline depends on data availability and specific analytical needs.

Data engineering consultation costs vary depending on project complexity and scope. We offer flexible pricing models for both short-term and long-term projects. Contact us for a customized quote based on your specific requirements.

A basic modern data stack can be implemented in 2-4 weeks, while more advanced solutions with AI integration and automation can take 6-12 weeks. We've developed cost-effective solutions that can be operated for just $10/month.

Hockey analytics uses Python for data analysis, NHL API for statistics, Plotly for interactive visualizations, and DuckDB for data processing. We've developed automated pipelines with Mage AI and deployed dashboards on Streamlit Cloud for real-time hockey performance analysis.

We use advanced data science techniques to analyze Swedish NHL stars like Elias Pettersson and Erik Karlsson. Our analysis includes points per 60 minutes, shooting efficiency, power play productivity, and advanced metrics that go beyond basic statistics to reveal true player value.

Absolutely! Hockey analytics has helped teams improve by 25% in key performance metrics. We provide insights on player positioning, line combinations, penalty kill efficiency, and opponent analysis for SHL, Hockeyallsvenskan, and Elite-serien teams.

Hockey analytics consulting for Swedish teams ranges from €2,000-€10,000 depending on scope. We offer season-long partnerships, individual player analysis, and custom dashboard development. Our cost-effective modern data stack can operate for just €10/month.

Basic hockey analytics setup takes 2-3 weeks, while comprehensive solutions with real-time tracking and predictive modeling take 6-8 weeks. We've streamlined the process for Swedish hockey organizations with proven methodologies.

Yes, AI and Large Language Models can dramatically improve customer support through intelligent ticket routing, automated responses, and predictive problem-solving. We've implemented LLM integration with ServiceNow for enhanced support analysis and efficiency.