DWH Framework

Data integration in Microsoft environment. No more unknown data flows, no more programmer creativity. Just metadata.

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The DWH Framework = standards + best practices in ETL

No more creativity in ETL

The DWH Framework unifies and streamlines data flows in your organization. No more creativity in coding ETL processes, no more unfamiliar data flows, no more coding handwriting.

Processes defined by metadata

The DWH Framework converts or sets up all ETL processes using predefined standardized routines defined by metadata.

Code standardization

With the Adastra DWH Framework, developers and administrators don’t write code directly, they just set the metadata and configure the process. This automatically standardizes the code.

When to use Adastra DWH Framework


To upgrade existing data warehouse built in Microsoft environment.


To develop new data warehouse in Microsoft environment.


To migrate existing data warehouse in Microsoft environment (to on-premise and/or Cloud).


For workflow and schedule for ETL execution, validation and notification.


For development and automated delivery of ETL in Azure DevOps.


For documentation, data lineage, administration and monitoring.

Metadata – the key to standardization and efficient development

All-in-one solution

You get a comprehensive tool to develop and manage ETL processes.

High reliability

Thanks to the rules you will have highquality ETL processes from the very beginning.

Rapid deployment

Within 3 months, you will have a reliable and functional solution without big effort.

High ROI

You will save more than 2000 man-days you would spend on mapping ETL processes.

Minimal costs

You will cut the time required to develop and manage a new solution.


On day 1, you will know what the general patterns and specific ETL processes should look like.

Case studies

Equa Bank clients were fully migrated to Raiffeisenbank in 12 hours

When Equa Bank was being mergedintoRaiffeisenbank in November 2022, we handled the migration of Equa Bank’s client data into Raiffeisenbank’s CRM system. We also ensured the client master data was propagated to the bank’s core systems.  

hours instead of 3 weeks – shorter live migration thanks to 10 months of testing and agile development

subjects to migrate

people - each with 200 attributes, added to Raiffeisenbank’s client base after the acquisition of Equa Bank

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ŠKODA AUTO: data transfers on analytics platform are comprehensively managed and monitored by Adastra’s Adoki

In 2018-19, Adastra built an on-premise Data Analytics Platform (DAP) at ŠKODA AUTO. Its purpose? To visualize data and use advanced analytics and artificial...

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Automatic categorization for 98.5% of card transactions

With millions of clients conducting millions of operations every day, the bank needed to automatically assign a unique category to every banking transaction (card...

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Just-in-time loan offers: a 10x higher conversion rate

Together with the bank, we used several years’ worth of transaction descriptions and a number of transactions of a specific type to identify a...

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Adastra becomes a strategic partner of Škoda Auto University. Its specialists will teach data management, data science, and artificial intelligence courses

Adastra becomes a long-term strategic partner of Škoda Auto University. Its experts will be involved in teaching data management, data science, and artificial intelligence...

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Unraveling the Future: Top 8 Data Management Trends for 2023 and Beyond 

The digital landscape is evolving at an unprecedented pace, and with it comes a new set of challenges and opportunities for IT professionals, data...

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Contact us

David Kaláb
Government, Utility & Insurance Division Director