biGENIUS-X
What is biGENIUS-X?
Tool for automating the development, provisioning and operating cycle of data warehouses, data lakes and data lakehouses.
Self-description of biGENIUS-X
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biGENIUS-X User Reviews & Experiences
The information contained in this section is based on user feedback and actual experience with biGENIUS-X.
Individual user reviews for biGENIUS-X
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What do you like best?
Great ease of use, phenomenal security concept, technology independence, best practices of software engineering applied to data modeling, low-code automation.
What do you like least/what could be improved?
Delta deployment.
What key advice would you give to other companies looking to introduce/use the product?
Try it out on a real use case.
How would you sum up your experience?
Love it. Would not want to work without it anymore.
Number of employees
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What do you like best?
Die Nähe und der schnelle Support des Herstellers; das ausgereifte Tool und seine Generatoren; die Automatisierungsgewinne durch das Tool.
What do you like least/what could be improved?
Die Verbindung zu den Quellen und zu den Zielen; der Deploymentprozess.
What key advice would you give to other companies looking to introduce/use the product?
Einen Proof of Concept mit dem Tool durchführen.
How would you sum up your experience?
Viel gutes Hirnschmalz in einem Tool, das Standardisierung schafft und Automatisierungsgewinne produziert.
Number of employees
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What do you like best?
biGENIUS-X is a web-based interface that makes it possible to completely automate the creation of data lakehouses on modern data platforms, such as Databricks. In our case, we built an enterprise Data Vault in the silver layer of a medallion architecture and a Kimball-style dimensional model in the gold layer, on top of Databricks. biGENIUS-X makes this user-friendly and enables the generation of PySpark code that can directly be used in Databricks workflows. Recently, they added a dbt generator, which also gives us the capacity to deploy our models directly in dbt. biGENIUS-X integrates with DevOps (Azure DevOps, GitHub, etc.), which makes collaboration and CI/CD on data models easy. For our team of 15 data modelers coming from various backgrounds and locations, it enabled us to build our models with a common framework and standards, including metadata and naming conventions, which was a critical success factor in a domain-based data mesh implementation. In addition, biGENIUS-X enables us to share data products (or the metadata for them) in a Data Marketplace available in the software, which helps with reuse and sharing between data modelers. As such, it fits well within a data mesh-based architecture. Last but not least, biGENIUS continuously provides great support, with a fast turnaround whenever we raise questions or find bugs. They really support us and help us make progress in our data modeling efforts.
What do you like least/what could be improved?
As heavy users of SAP systems, we are dealing with lots of tables. The browser-based interface of biGENIUS-X can respond a bit slowly when checking the data lineage across a large number of tables. That said, we see a lot of progress being made in addressing these issues, with new features added regularly. Also, the capability to export nicely formatted database diagrams for sharing is available but still a bit limited.
What key advice would you give to other companies looking to introduce/use the product?
Plan training sessions with biGENIUS to get started and have your data modelers certified. This will make their experience much easier. Ensure that the data modelers/data engineers have a good knowledge of DevOps principles if biGENIUS-X is used within a CI/CD environment. If you implement a Data Vault data model or a dimensional model, it is important to understand the concepts associated with Data Vault and dimensional modeling well, in addition to using the templates and frameworks provided by biGENIUS-X. Plan well how data modelers will be working together. biGENIUS provides different options for teamwork, but it helps to have a good strategy from the start.
How would you sum up your experience?
I do appreciate working in the biGENIUS-X app. I appreciate the efficiency gains and the flexibility provided by biGENIUS-X for data modeling and the capability to generate the code to be run in the target data platform at the push of a button or two. biGENIUS-X has many modern features, which prove extremely useful, such as a data marketplace to share and reuse models between data modelers, the integration with Git, easy data lineage for tables and fields (which makes work much easier while modeling), and the addition of several AI features to simplify a data modeler's work (e.g., automatically mapping field names with GenAI or generating descriptions for fields). We are awaiting the next full GenAI-based models generated from the business concepts we provide.
Number of employees
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What do you like best?
The automated code generation saves us a lot of manual work. We built our data warehouse much faster than we could have by hand, and the metadata-driven approach keeps everything consistent. It's also good to know we're not locked into one target platform. The collaboration with the biGENIUS team is very good and always helpful.
What do you like least/what could be improved?
The data marketplace could be extended further, and we'd like to see more options around automated deployment. Nothing that blocks us in our daily work, but there's room to grow in these areas.
What key advice would you give to other companies looking to introduce/use the product?
Take the time to understand the metadata-driven approach before you start. Start with a clearly scoped part of your data warehouse, and involve the biGENIUS team early. They know their product well.
How would you sum up your experience?
A solid tool for building and maintaining a data warehouse or lakehouse. It takes over the repetitive work so the team can focus on the actual data model and business logic. We would choose it again.
Number of employees
Industry
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What do you like best?
Ease of use, no installation compared to competitors. It's a web app running in the virtual machine of your browser. Best of both worlds: no installation, but still running fully on your machine.
What do you like least/what could be improved?
DevOps integration.
What key advice would you give to other companies looking to introduce/use the product?
Take the biGENIUS e-learning course. It provides best practices and allows your team to make the most of the software from the beginning.
How would you sum up your experience?
Very good software.
