
Dimensional Modeling Experts in Berlin
, matched in minutes by AIHire experts who shape star schemas, define business-friendly metrics and prepare warehouse models for BI reporting. FRATCH connects you with vetted, available freelancers through fast, precise AI matching.
Meet FRATCH Experts in Berlin, who have recently used Dimensional Modeling
William N.
Last position:
Power BI Solutions Architect/Engineer & AI Consultant at AVERDUNG GmbH
- Redesign of the company's BI infrastructure: replacement of a fragmented landscape of manually maintained Excel solutions and CSV imports with a centralized Power BI environment featuring a unified data model as the company-wide single source of truth
- Consolidation of previously isolated reporting logic into a central semantic model – eliminating redundant files, manual data transfers, and inconsistent metrics between departments
- Forecasting & planning: Design and implementation of company-wide liquidity planning in Power BI – from business logic to a fully automated, data-source-driven planning model replacing the previous manual Excel process; enables rolling forecasts and continuously up-to-date cash flow transparency for management
- Optimization of existing Power BI dashboards in terms of performance, structure, and analytical value using an AI-native approach
- Analysis and improvement of the data model, including data quality analyses, data cleansing, and consistent modeling using star schema, DAX, and Power Query
- Incident & anomaly analysis: Identification, investigation, and explanation of data anomalies, including root-cause analysis and concrete recommendations for action
- AI solution architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
- Creation of a historical data layer as a basis for trend and time-series analyses
- AI-supported automation: Design and development of AI skills, agents, loops, and processes for the automated analysis and interpretation of reports
- Automated reporting workflow: Setup of scheduled, automated email distribution of AI-generated analyses and recommendations to stakeholders
- Gathering and documentation of business requirements and coordination with business departments and IT as part of requirements engineering / product owner activities
- Breaking down overall requirements into clearly defined work packages and tasks
- Definition, prioritization, and management of milestones throughout the entire project lifecycle
Tools: POWER BI, M365, Copilot Studio, MIRO, Microsoft Business Central, Microsoft Fabric, Claude AI, ChatGPT, LangDock, MS VS Code
Nisanthan S.
Last position:
Business Intelligence Consultant (freelance) at NBIC – Nisanthan BI Consulting
Advising companies on building, migrating and optimising BI and reporting landscapes (Power BI, SQL, Python, ETL)
5 client engagements in real estate and finance since 05/2025: taking over and stabilising existing reporting, automating recurring standard and management reports, building cash-flow models
Proposal and feasibility assessments for BI and reporting projects
Using AI-assisted development (Claude Code) to accelerate automation, tooling and web/app development
Custom ERP system
Problem: A client's core processes ran on scattered, siloed Excel files with no central data storage – error-prone, hard to scale and impossible to analyse end-to-end.
Approach: Captured the business processes and requirements, modelled the data and developed iteratively together with the business team.
Implementation: Built a tailored, web-based ERP system with a central database, role-based modules and automated reporting – delivered using AI-assisted development in Claude Code.
Timesheet app
Starting point: Time tracking based on an overgrown, macro-heavy Excel template – maintenance-intensive, single-user and error-prone.
Implementation: Migrated all functionality and VBA macros into a standalone web app with central data storage, multi-user support and automated reporting.
Cash-flow modelling
Starting point: The existing cash-flow model covered standing investments only; project developments were missing from steering.
Implementation: Built and extended the CF model to include project-development cash flows.
Optimisation: Reviewed and optimised existing CF models and expanded the KPI outputs for reporting and steering.
Anshita S.
Last position:
Business Intelligence Developer and Data Analyst at Deloitte Consulting
Specialize in turning complex data from diverse environments into actionable business value through compelling visual storytelling. I am an expert in generating actionable insights and presenting recommendations to business stakeholders. My technical proficiency in SQL, Python, and leading data visualization tools like Tableau and Power BI allows me to deliver a new generation of self-service tools and analytics services.
- Data Visualization & Storytelling: Created impactful data visualizations and dashboards in Tableau and Power BI, effectively communicating findings and presenting actionable recommendations to C-suite stakeholders and business leaders.
- Stakeholder Management: Built effective working relationships with key business stakeholders, data engineers, and other partners to achieve common data-driven goals and targets.
- Insights & Recommendations: Generated actionable insights from complex data analysis for funnel conversion, marketing performance, and ROI, directly influencing business performance and strategy.
- Data Collaboration & Empowerment: Worked closely with cross-functional teams to support the ongoing data needs of internal partners, helping to optimize internal data processes and workflows.
- BI & Data Expertise: Applied extensive experience in data modeling, data collection, data mining, and analysis to deliver end-to-end analytical solutions from stakeholder discovery to production.
Lasya M.
Last position:
Data Engineer at Carelon Global Solutions (Elevance Health)
- Designed and implemented scalable ETL/ELT pipelines using Python, SQL, dbt, AWS and Informatica to ingest data from sources such as APIs, relational databases, and flat files into Snowflake, reducing pipeline runtime by ~30%.
- Migrated high-volume datasets from on-premises Teradata to Snowflake using AWS services (S3, Glue, Step Functions, IAM), ensuring data consistency and integrity.
- Applied Kimball methodology to design star and snowflake schemas, improving query performance and reducing Snowflake compute costs.
- Implemented automated data quality checks using SQL-based dbt tests and the Great Expectations framework to detect anomalies and enforce data correctness before production loads.
- Orchestrated ETL workflows in Airflow using Python and managed code deployments via Git with CI/CD best practices to increase deployment reliability and maintain pipeline uptime.
- Built interactive Power BI dashboards and curated datasets to enable data-driven decision-making for stakeholders.
- Maintained technical documentation in Confluence for ETL workflows, and led knowledge-sharing sessions for new joiners.
Gyan P.
Last position:
Senior DevOps and Cloud Architect at Bosch
- Architected and operated cloud-based data and ML platforms for autonomous driving and parking systems, supporting large-scale (multi PB scale) simulation and vehicle data ingestion.
- Implemented security, compliance, and governance standards across Azure subscriptions and cloud resources.
- Managed GitHub organizations and CI/CD pipelines to improve deployment reliability and developer productivity.
- Contributed to hiring and technical interviews as part of the recruitment panel.
Enrico G.
Last position:
Freelance Software & Data/AI Engineer at Freiberuflicher Software & Data/AI Engineer
- Lecturer for the GenAI Track at the Master School Institute of Technology
- Development of a full-stack AI application (React + Python/FastAPI) for automated supplier product import with intelligent column and category classification (4-layer hierarchical) including human-in-the-loop validation
Germo G.
Last position:
BI Developer at Rhenus Logistics
- Business intelligence development in the logistics sector.
- Migrating existing reporting and analysis solutions from Cognos to Microsoft BI.
- Using Microsoft SQL Server, SSAS, Power BI, and other Microsoft BI platform components.
Discover over 15,000 top freelancers
Statistics of experts using Dimensional Modeling
Aggregated from the professional profiles of matched freelancers.
Experience
13 years

Position duration
2.4 years

Positions per freelancer
12

Top business areas
Business Intelligence, Information Technology, Project Management

Top industries
Information Technology, Banking and Finance, Automotive

Certification focus areas
Information Technology, Business Intelligence, Human Resources
Bachelor's degree or higher
100%
Master's degree or higher
40%

Certifications per freelancer
3

Most common languages
German, English, Hindi

Speak two or more languages
100%
Based on our profile pool as of 16 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Berlin are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Berlin using Dimensional Modeling
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 16 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Dimensional Modeling experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (71%)
- Banking and Finance (57%)
- Automotive (43%)
- Healthcare (43%)
- Professional Services (43%)
- Education (29%)
- Fashion (29%)
- Manufacturing (29%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What it structures
Dimensional Modeling organizes analytical data around measurable business events and the context needed to understand them. It separates fact tables, which record events such as orders or usage, from dimension tables that describe customers, products, dates or locations. The result is a model that supports clear reporting and efficient analysis.
Star and snowflake schemas
The star schema keeps dimensions broad and easy to query, making it a common choice for dashboards and self-service BI. A snowflake schema normalizes parts of those dimensions when reuse, governance or storage design calls for it. Strong specialists know when simplicity matters more than additional normalization.
- Define grain before building fact tables
- Set conformed dimensions across business areas
- Separate measures from descriptive attributes
- Document keys, hierarchies and calculation rules
Warehouse ecosystem
Dimensional models can sit in cloud warehouses, lakehouses or established enterprise data platforms. Projects often involve SQL, dbt, ELT pipelines, semantic layers and BI tools such as Power BI, Tableau or Looker. Useful adjacent knowledge includes source-system analysis, data quality checks, orchestration and access control.
When specialists help
Companies bring in freelance expertise when reports disagree, a warehouse has grown without a consistent grain, or a new subject area must connect to existing data. In Berlin, teams may also use remote collaboration across distributed data and analytics groups, with clear documentation supporting German- and English-speaking stakeholders.
- Rework an inconsistent sales or finance model
- Migrate reporting from spreadsheets to a warehouse
- Add a shared customer or product dimension
- Prepare trusted datasets for executive dashboards
What strong professionals deliver
A strong professional starts with business processes and source-system realities rather than copying table structures. They make grain, keys, slowly changing dimensions and historical behavior explicit. Their deliverables include model diagrams, tested SQL, transformation logic, metric definitions and guidance that reporting teams can maintain.
Choosing the right approach
Dimensional Modeling is especially effective when users need stable metrics, understandable navigation and repeatable reporting across departments. A specialist should also assess whether a normalized model, data vault or wide analytical table is more suitable for the workload. Quality shows in consistent results, explainable trade-offs and tests that catch duplicate facts, missing keys and broken history.
Frequently asked questions
Before you brief your next project: the most common questions about Dimensional Modeling.
Dimensional Modeling is used to organize warehouse data for reporting, analytics and business intelligence. It connects measurable events in fact tables with descriptive dimensions such as customer, product, date and location, so users can explore consistent metrics.
Dimensional Modeling favors readable analytical structures, often with denormalized dimensions and straightforward joins. Normalized relational modeling reduces duplication and is usually better suited to transactional applications, while dimensional designs prioritize query usability and reporting performance.
A star schema keeps dimensions close to the fact table and is often easier for BI users and reporting tools to navigate. A snowflake schema can make sense when dimensions contain reusable hierarchies or stronger normalization is needed, but it adds joins and design complexity.
A strong Dimensional Modeling specialist usually understands SQL, warehouse architecture, ETL or ELT, data quality and BI semantics. Experience with dbt, orchestration tools, cloud warehouses, slowly changing dimensions and stakeholder-led metric definitions is also valuable.
The right level of Dimensional Modeling experience depends on scope, source complexity and the cost of incorrect metrics. A focused subject area may need a specialist who can model one business process, while an enterprise warehouse requires experience with shared dimensions, history and governance.
Dimensional Modeling can be delivered remotely when workshops, source documentation and design decisions are captured clearly. Berlin-based teams may collaborate with remote specialists across locations, but they should agree on language, meeting routines, ownership and access to data systems.
Review whether the dimensional model has an explicit grain, stable keys, well-defined measures and consistent dimensions across reports. Ask for examples of tests, documentation and handling for late-arriving data, duplicate events and changes to historical attributes.
Before starting, a Dimensional Modeling specialist should clarify the business processes, reporting decisions, source-system ownership and expected refresh behavior. They should also confirm whether the warehouse already has conformed dimensions, how metric definitions are approved and who will maintain the model.
The average hourly rate of freelancers in Berlin, Germany who have used Dimensional Modeling in their recent projects is 81 €, which corresponds to a daily rate of about 649 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Dimensional Modeling in their recent projects, 100% hold at least a Bachelor's degree and 40% hold at least a Master's degree.
On average, freelancers in Berlin, Germany who have used Dimensional Modeling in their recent projects have 13 years of professional experience, with a single engagement typically lasting around 2.4 years.
The most common languages among freelancers in Berlin, Germany who have used Dimensional Modeling in their recent projects are German (100%), English (100%), and Hindi (29%).
The most common industries among freelancers in Berlin, Germany who have used Dimensional Modeling in their recent projects are Information Technology (71%), Banking and Finance (57%), and Automotive (43%).
The most common business areas among freelancers in Berlin, Germany who have used Dimensional Modeling in their recent projects are Business Intelligence (100%), Information Technology (100%), and Project Management (86%).
Main locations of FRATCH Experts, who have recently used Dimensional Modeling
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Countries:
Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
