What technologies do you use?

Our core expertise lies in Power BI development, including Power Query, M, and DAX. To enhance development, performance optimisation and version control we use external tools such as Tabular Editor, DAX Studio, ALM Toolkit, VS Code and others. Additionaly we use Microsoft Excel, VBA and SQL when needed, and occasionally Python.

Do you offer Data Warehousing or Data Science?

We primarly focus on Power BI. For projects that scale into Data Warehousing, Data Science, Machine Learning or the broader Power Platform, we work via a Partner Network Model. While we lead the reporting and visualization layer, we frequently collaborate with:

• Infrastructure Partners for SQL and DWH development.

• Analytics Partners for specialized Data Science and AI.

• Low-Code Partners for Power Apps and automation.

What are customised and interactive reports in modern BI?
Customised and interactive reports are tailored analytical solutions designed to reflect specific business goals, allowing users to filter, drill down, and explore data dynamically instead of viewing static information. They combine structured semantic models with flexible visuals to support role-based insights and faster decision-making. In practice, organisations build interactive reporting environments using tools such as Microsoft Power BI or Tableau, aligning design with Business Intelligence principles. Effective implementations usually include:

• automated data refresh and scheduled updates,
• dynamic filtering, bookmarks, and drill-through navigation,
• KPI-focused layouts designed for executives and analysts,
• reusable datasets that ensure consistency across departments,
• performance optimisation strategies aligned with semantic modeling best practices,
• visual storytelling techniques that make insights understandable for non-technical stakeholders,
• row-level security and controlled access to insights,
• auditability and version control.

How long does it take to develope a Power BI report?

Most Power BI reports take 8–40 hours depending on the complexity of the data and required calculations. Simple dashboards based on prepared data can be completed within 10–20 hours, while more advanced reports involving complex data transformations, advanced calculations and performance optimisation may take 40–80+ hours.

How does advanced data analysis improve reporting accuracy?
Advanced data analysis applies statistical methods, predictive logic, and contextual modeling to transform raw datasets into actionable insights that improve business decision quality. Instead of relying only on descriptive metrics, analysts integrate models inspired by Data Science and platforms like Python analytics ecosystems. This approach often involves:

• anomaly detection to highlight unexpected performance shifts,
• forecasting models aligned with Regression analysis techniques,
• segmentation analysis to identify hidden patterns,
• combining structured and semi-structured data sources,
• integrating advanced calculations into enterprise dashboards powered by Qlik Sense.

Why migrate from Excel to Power BI reporting?
Migrating from Excel-based reporting to Power BI enables scalable automation, centralized data governance, and interactive visualization capabilities that traditional spreadsheets cannot efficiently provide. Organisations move from static files toward cloud-driven analytics environments connected through Microsoft Fabric or enterprise data warehouses. Typical migration benefits include:

• automated refresh instead of manual spreadsheet updates,
• stronger security through identity platforms like Microsoft Entra ID,
• improved performance with in-memory models,
• collaborative sharing across teams without file duplication,
• enhanced visualization options aligned with modern dashboard UX standards.

What happens during a BI report audit?
A BI audit evaluates existing dashboards, datasets, and calculations to identify performance issues, data inconsistencies, and design inefficiencies that reduce analytical reliability. Audits often follow governance methodologies influenced by DAMA International and modern analytics engineering practices. Key audit steps usually involve:

• reviewing semantic model relationships and measures,
• analysing query performance through tools such as DAX Studio,
• validating data sources against business definitions,
• improving visual hierarchy and user experience,
• recommending redesign strategies aligned with enterprise reporting frameworks.

How do interactive dashboards support executive decision-making?
Interactive dashboards provide leaders with real-time visibility into business performance, enabling faster interpretation of trends through intuitive visual exploration. Built within platforms like Looker or Power BI, these dashboards typically follow Information Design principles to ensure clarity. Effective executive dashboards focus on:

• simplified KPI tracking with contextual drill-down options,
• automated alerts for critical thresholds,
• comparison visuals that highlight growth or decline,
• responsive layouts for mobile accessibility,
• integration with operational systems such as Salesforce.

What is report optimisation and why is it important?
Report optimisation improves performance, usability, and scalability by refining data models, visuals, and calculation logic to reduce loading times and enhance user experience. Analysts often apply optimisation techniques inspired by Columnar storage architecture within enterprise BI environments. Key optimisation actions include:

• reducing unnecessary visuals and filters,
• restructuring datasets for efficient aggregations,
• implementing incremental refresh logic,
• improving DAX or SQL calculations,
• monitoring performance using Performance Analyzer tools.

How does semantic modeling influence report development?
Semantic modeling defines how business data is structured, related, and calculated so that reports reflect consistent business logic across all dashboards. Using tabular modeling techniques derived from SQL Server Analysis Services, analysts build reusable datasets that support multiple reports. Best practices include:

• defining clear hierarchies and relationships,
• separating raw data from analytical layers,
• creating reusable measures aligned with business terminology,
• enabling self-service exploration while maintaining governance,
• documenting models using metadata management strategies.

What role does UX design play in BI reporting?
User experience design ensures dashboards are intuitive, visually balanced, and aligned with how users actually consume information, increasing adoption and analytical effectiveness. UX-driven reporting integrates concepts from Human–Computer Interaction and visual psychology to reduce cognitive overload. Typical UX improvements include:

• consistent colour logic for KPIs,
• logical navigation flows across pages,
• prioritising key metrics above supporting details,
• reducing visual clutter through minimalistic design patterns,
• applying storytelling principles from Storytelling with Data.

How does automated reporting reduce operational workload?
Automated reporting eliminates repetitive manual processes by scheduling data refreshes, distributing dashboards automatically, and synchronizing insights across teams. Automation workflows are often orchestrated using tools such as Power Automate or Apache Airflow. Organisations typically benefit from:

• scheduled data refresh and distribution,
• centralized governance over report versions,
• consistent delivery of insights to stakeholders,
• reduced human error in recurring reports,
• faster turnaround for operational monitoring.

What is the difference between analytical and operational dashboards?
Analytical dashboards focus on long-term trends and strategic insights, while operational dashboards monitor real-time processes and immediate performance indicators. Analytical environments often rely on data warehouses like Snowflake, whereas operational dashboards integrate live feeds from systems such as ServiceNow. Differences usually include:

• level of aggregation and refresh frequency,
• target audience (executives vs operational teams),
• visual complexity and interactivity,
• historical versus near real-time data usage,
• performance optimisation strategies aligned with dashboard purpose.

How does report redesign improve stakeholder adoption?
Redesigning reports focuses on simplifying navigation, improving clarity, and aligning dashboards with business workflows, leading to higher user engagement. Analysts apply frameworks inspired by Design Thinking to reimagine reporting structures. Effective redesign strategies involve:

• reorganizing visuals based on user roles,
• reducing redundant pages or metrics,
• standardizing colour schemes and terminology,
• enhancing accessibility for mobile devices,
• integrating feedback loops from business users.

Why is data governance essential during report migration projects?
Data governance ensures that migrated reports maintain accuracy, compliance, and consistent business definitions across new analytical environments. Governance practices align with frameworks from International Organization for Standardization and enterprise metadata platforms like Collibra. Core governance tasks include:

• validating data lineage before migration,
• standardizing metric definitions across systems,
• enforcing role-based permissions,
• documenting transformation logic,
• maintaining auditability across reporting layers.

What advanced analytics techniques are commonly used in BI projects?
Advanced analytics techniques enhance traditional reporting by adding predictive insights, anomaly detection, and statistical modeling to business dashboards. Analysts frequently combine visualization tools with environments such as RStudio or cloud ML platforms like Azure Machine Learning. Common techniques include:

• clustering and segmentation analysis,
• forecasting based on time-series models,
• predictive scoring integrated into KPI visuals,
• automated anomaly alerts,
• combining descriptive and predictive insights in unified dashboards.

How do role-based analytics improve data security and usability?
Role-based analytics delivers personalized dashboards by controlling access to data based on user responsibilities, ensuring both security and relevance. Security models are often implemented using Okta identity workflows or enterprise directory services. Practical applications include:

• limiting sensitive financial data to authorised users,
• creating department-specific dashboard views,
• simplifying navigation by hiding irrelevant visuals,
• aligning access rules with compliance policies,
• enhancing collaboration without exposing confidential information.

What are the key benefits of long-term BI consulting and training?
BI consulting and training help organisations build internal analytical maturity by improving reporting workflows, data literacy, and governance practices. Training initiatives often integrate structured learning approaches influenced by Data Literacy and practical workshops using platforms like Microsoft Teams. Long-term collaboration typically delivers:

• faster onboarding for new analysts,
• standardized reporting methodologies,
• stronger collaboration between technical and business teams,
• continuous optimisation of semantic models and dashboards,
• sustainable growth of data-driven decision-making culture across the organisation.

• Understanding the business goals
  We start by discussing the purpose of the report  — what questions need to be answered, which KPIs are important, and who will use the report.

• Data gathering and preparation
  We connect to the required data sources and clean, transform, and structure the data to ensure it is reliable and ready for analysis.

• Data modelling and analysis
  We design the data model and create calculations and metrics using DAX to support the required analysis.

• Report design and visualisation
  We build the Power BI report with clear layouts, interactive visuals, and intuitive navigation to make insights easy to explore.

• Review and iteration
  We deliver an initial version of the report (usually consisting of several pages) for feedback. Based on client input, we refine and improve the report until it fully meets the business needs.