Data Warehouse and Data Management Strategies
From Data Warehousing to Big Data Warehousing
Requirements for a modern data management architecture
Data management architectures are constantly evolving – and yet the current development stage is not necessarily the right one for your process landscape. Based on your requirements, we determine the right approach and procedure for a modern data management architecture.
Whether it is the planning of a data warehouse with Data Vault, the combination of data lake and data hub for a smooth distribution of data, integration of Kappa or Lambda architecture or hybrid solutions in the combination of cloud and on-premise technologies – we will work with you to develop the right solution approach and will also be happy to implement it in collaboration with you.
Scalability, reusability of solutions, agility in implementation and the pursuit of a best-of-breed approach are a matter of course for us.
This is how we work
- Development of overarching basic concepts regarding modelling and ETL implementation
- Contribution of best practices (cimt job framework)
- Project management with reference to Scrum
- Adaptation of Talend components to in-house special cases (Teradata)
- Use of Big Data components (Spark, Hive etc.) in conjunction with classic DWH approaches (BigData-Link)
- Implementation, test and QA of ETL jobs
- Introduction to the operation
Our services at a glance
- Recording/analysis of the environments
- Achitectural design
- Overall responsibility for conceptual design, realisation, coaching, project management
- Introduction, training and coaching of customer employees / Agile procedures in data warehouse development
