Data, Analytics & Databases
Data quality is the foundation for BI, KPI dashboards and reliable decisions – find the right entry point for databases, analytics and reporting here.
Databases, data quality, and BI – so decisions are faster and based on reliable metrics.
Services: Data, Analytics & Databases
Data analytics & business intelligence
BI, dashboards and analytics for decisions you can trust.
View Data analytics & business intelligence →Database solutions
Database design, migration, performance and scalable models.
View Database solutions →Database & business intelligence
Scope, process and FAQ on the service page – Made in Germany from East Frisia.
View Database & business intelligence →
Estimate your project costs
Use our interactive calculator for a first budget indication—free and non-binding.
Thorsten Frieling – Projektmanagement
Find the right entry point in Data, Analytics & Databases
Data quality: context, benefits and typical use cases
Data quality is the prerequisite for KPI dashboards, group reporting and operational decisions that rely on the same numbers. Duplicate master data, missing history or inconsistent terms across ERP and spreadsheets lead to costly wrong decisions—before BI tools even enter the picture. This hub routes you to the right entry point: from data warehouse & database consulting and KPI dashboard & BI to Power BI.
When companies should prioritise data quality
Prioritise data quality when departments report different revenue or inventory figures, audit finds variances between systems, or a BI rollout would fail without data-quality rules. We combine analysis, design and delivery: profiling, cleansing, governance and ongoing monitoring—supported by interfaces and data analytics where exploratory work is needed. Next step: review your data and BI potential.
Which data, analytics or database service fits your starting problem?
| Starting problem | Matching service | Next step |
|---|---|---|
| BI consulting, KPIs, reporting, data analytics consulting | Data analytics & business intelligence | Book a data strategy call |
| Database design, migration, performance, architecture | Database solutions | Project check |
| BI storage, warehouse, semantic layer | Database & business intelligence | Cost calculator |
| Power BI, DAX, dashboards, Microsoft BI | Power BI consulting | Microsoft 365 |
Direct answer: what is the data cluster for?
Data analytics ≠ Power BI ≠ database architecture: strategic BI on data analytics, Microsoft Power BI on Power BI, BI data layers on database & BI – separate URLs, no overlapping topics.
Sources & silos: ERP/CRM connectivity via API integration in the integration & interfaces cluster. Made in Germany from East Frisia.
Roles in the cluster: data, analytics & databases
So pages do not overlap, each has a clear role. The matrix shows focus and delineation – so you quickly find the right entry point.
| Service | Role | Focus | Delineation |
|---|---|---|---|
| Data analytics & business intelligence | Core service | KPIs, reporting, dashboards | Analysis and visualisation – not data storage |
| Database & business intelligence | Core service | BI architecture and data storage | Storage and models as the basis for analytics |
| AI knowledge base | Specialist topic | RAG search across documents | Knowledge access instead of classic reporting |
| AI implementation | Specialist topic | Roadmap, coaching and pilot | Adoption process, not a finished solution |
| Database solutions | Specialist topic | Database design and operations | Technical data foundation below analytics |
Related pages for Data, Analytics & Databases
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Services & costs
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Frequently asked questions: Data, Analytics & Databases
Short answers to orient you in this cluster – the same content is marked up as FAQPage schema.
Data analysis or Power BI – which URL is responsible?
Data analysis covers questions, KPI logic and DWH basics; Power BI is the specialised Microsoft BI service – the overview on this page avoids overlapping topics.
Do we need a database solution before BI?
Without a solid data foundation BI rarely pays off – we often recommend database or integration work first; this hub links the right sequence.
How does this cluster relate to AI projects?
Knowledge bases and RAG need clean data; after data quality and integration we link to AI introduction or knowledge base services in the AI cluster.
What is the next step after this hub?
Short intro call, matching cost calculator or project check – then the detail page (data analysis, databases, BI layer or Power BI) with concrete scope.
Data, analytics & databases: provider profile and approach
„Trusted metrics only emerge when it is clear whether you need BI consulting, database architecture, BI data layers or Power BI—not when every data keyword lands on one URL.“
Questions about our services?
Need a tailored quote? Contact us or book a consultation.
Thorsten Frieling – Project management
Or call us:+49 491 960 999 00
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Quick context: Overview of this service category – with clear boundaries to related topics.
Service at a glance – for your decision
Data, analytics & databases: compact service description
Definition: This cluster covers data analysis, database architecture, BI data layers and Power BI – so metrics are reliable and business teams can decide on data.
When it applies: When reporting is chaotic, data quality is poor, a DWH/BI layer is needed or Power BI must connect to ERP data.
Audience: Leadership, finance and IT teams that want BI without silos and with ties to operational systems.
Outcome: Usable dashboards, structured models and documented ETL/integration paths – often alongside integration or AI work.
Approach: Clarify sources and KPIs, improve data quality and models, validate dashboards with business teams, document operations and iteration.
Prerequisites and limits: Prerequisites and limits: defined KPIs, data sources with permissions and a business owner. Limits: not a full ERP rollout or app build without a data model—see platform and integration services.
Differentiation: Pure interfaces without BI focus → Integration; AI knowledge bases → AI & ML; bespoke software → Software & platforms.
Trust: Mid-market BI, database and Power BI experience from East Frisia with clear milestones and handover.
Sensible next step: Sensible next step: clarify data sources and KPI questions in an intro call—then model or dashboard roadmap.
Approach in steps
- Vorgehen: Clarify sources and KPIs, improve data quality and models, validate dashboards with business teams, document operations and iteration.
Up to 50% of your investment via BAFA/KfW
Use our funding calculator to see which government grants may apply to your project.
Björn Groenewold – Managing Director
Service cluster
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Databases, data quality, and BI – so decisions are faster and based on reliable metrics.
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