Fabric ETL/DWH Implementation
A clean, reliable, modeled data foundation in Microsoft Fabric — so your analysts build on solid ground instead of fighting raw data.
+ VAT · Custom scope
Typical delivery 4–24 weeks · Covers one domain
Pasirinkite planąKas įtraukta
Pasirinkite planą
Pasirinkite tinkamą variantą, pridėkite priedų ir užsakykite pasiūlymą — toliau viskuo pasirūpinsime mes.
Fabric ETL/DWH Implementation
A clean, reliable, modeled data foundation in Microsoft Fabric — so your analysts build on solid ground instead of fighting raw data.
- Working Fabric environment configured in your tenant — yours to keep and grow
- Data pipelines connecting and refreshing every in-scope source automatically, no manual exports
- Lakehouse / warehouse built on Medallion architecture (Bronze / Silver / Gold) — cleaned, conformed, documented data
- A well-structured, BI-ready Gold-layer data model your analysts can point Power BI straight at
- Automated refresh and basic monitoring so data lands reliably without babysitting
- Handover pack: architecture overview, data dictionary, refresh/run procedures
+ VAT · Custom scope
Dabar mokėti nereikia — pasiūlymo užsakymas pradeda pokalbį. Suderinsime apimtį ir galutinę kainą su jumis.
Apžvalga
Fabric ETL/DWH Implementation
We build the data engineering layer of your Fabric platform — pipelines, lakehouse/warehouse, and cleaned, modeled, documented data — and hand it over BI-ready. Your internal analysts keep full ownership of semantic models and Power BI; we take care of the part that's hardest to hire for and most time-consuming to get right. Delivered by an experienced team, following Microsoft best practices, shaped around your sources and the data your reporting actually needs.
Kam tai tinka
- You have capable analysts, but they spend most of their time cleaning and prepping data instead of analyzing it
- Every report rebuilds the same logic from scratch because there's no shared, modeled data layer underneath
- Data engineering skills are hard to hire, expensive to keep, and you don't want a permanent team for it
- Pipelines are fragile or manual — data arrives late, breaks, or can't be trusted
- You're committed to Fabric and want the engineering done properly, while keeping BI in-house
Ką pateikiame
- Working Fabric environment configured in your tenant — yours to keep and grow
- Data pipelines connecting and refreshing every in-scope source automatically, no manual exports
- Lakehouse / warehouse built on Medallion architecture (Bronze / Silver / Gold) — cleaned, conformed, documented data
- A well-structured, BI-ready Gold-layer data model your analysts can point Power BI straight at
- Automated refresh and basic monitoring so data lands reliably without babysitting
- Handover pack: architecture overview, data dictionary, refresh/run procedures
Kaip dirbame
Ką gaunate
- Analysts do what they're good at — insight, not data wrangling
- A foundation everyone trusts — one clean, modeled data layer instead of repeated, conflicting prep
- No data-engineering hiring headache — the scarce, expensive skill is handled
- Data that arrives on time, every time — automated and monitored
- You keep control of BI — your tools, your models, your reports
Geriausiai tinka, kai
You have analysts who can own semantic models and Power BI, but you need a dependable, modeled data foundation underneath — and you'd rather outsource the data engineering than hire and manage a scarce, expensive team for it.
Nerandate būtent to, ko reikia?
Pasakykite, kokio rezultato norite — mes parinksime pasiūlymą.
Aprašykite savo duomenų poreikį, ir mes nurodysime tinkamą kūrimo, skolinimosi ir perdavimo derinį.