The biGENIUS-X Online Launch Event covered a wide range of topics, including data management trends, product vision, and data security. In this article, we will provide a comprehensive recap of the event, highlighting key insights and innovative features presented.
Introduction: Market and Paradigm Shifts in Data
Carsten Bange, the CEO and Founder of BARC, discussed the strategic shift in the market, where data has become a valuable asset for enterprises. He introduced two key concepts: data fabric and data mesh. Data fabric represents an evolution in data architecture, acknowledging the distributed nature of data and emphasizing metadata for federated access, while Data mesh promotes decentralization and domain-oriented ownership. Bange emphasized the role of Chief Data Officers (CDOs) in empowering teams and enabling widespread data usage while accommodating varying departmental maturity levels.
Full presentation of Market and Paradigm Shifts in Data
biGENIUS-X Product Vision
Gregor Zeiler, the CEO of biGENIUS, shared his product vision for biGENIUS-X. He highlighted the importance of CDOs in empowering data teams and product owners, providing them with dedicated platforms, templates, and patterns for data product implementation. Zeiler emphasized the goal of enabling anyone to become a skilled data engineer and the platform's focus on automating processes, implementing pre-defined patterns, and offering data architecture governance.
Full presentation of biGENIUS-X Product Vision
Message from Jack Ramsay (Accenture)
Data Management Trends and DataOps Principles
Professor Torsten Priebe from Fachhochschule St Pölten discussed various trends in data management. He emphasized the decentralization trend, including data mesh and data products, while underscoring the need for governance to avoid chaos. Priebe also highlighted the evolving tool landscape, with a fragmentation trend in supporting data transformation tools and a convergence trend in data platforms, where different architectural approaches coexist within a unified platform. He stressed the relevance of adopting DataOps practices, leveraging proven software engineering principles.
Full presentation of Data Management Trends and DataOps Principles
Product Demo and Deployment
We saw biGENIUS-X in action with an example use case:
In this demo, we saw some powerful features that can make your data workflow more efficient, including:
- Solution overview and project management in biGENIUS-X.
- Creation and management of branches in the Git repository.
- Uploading and integration of source system data using discovery tools.
- Modeling area for creating views and working with model objects.
- Data lineage visualization to understand data flow.
- Creation of stage model objects based on source model objects.
- Configuration of layers (bronze, silver, gold) and their purpose.
- Creation of link satellites based on stage objects.
- Relationship establishment between link satellites and existing links.
- Mapping of foreign keys and expressions in the data flow.
- Extension of the data mart composite object.
- Generation of scripts for deployment to a test environment.
- Deployment process outside of biGENIUS-X.
Data Security with biGENIUS-X
Thomas Gassmann, the CTO of biGENIUS, explained the data security measures implemented by biGENIUS-X. As a cloud-based application, biGENIUS-X stores minimal customer data, including organization details, registered users, and the URL of the Git repository. However, all other data, such as information about the data warehouse and data lake, is stored in the customer's Git repository. Gassmann emphasized that:
- biGENIUS-X does not retain files or metadata. Instead, it securely transfers this information back to the customer's Git repository, including the biGENIUS metadata. This approach enables seamless integration with platforms like GitHub and Azure DevOps, whether deployed in the cloud or on-premise.
- The user interface of biGENIUS-X runs in the user's browser, loaded from the cloud but executed within the user's browser and organization's network. This design ensures that data processing and interactions with biGENIUS-X remain within the user's controlled environment, enhancing security and data governance.
- The generation service takes the modeling information provided by users and processes it. It then returns the result as code or instructs the browser to push the generated artifacts to an artifact repository. This repository can be the same Git repository where the biGENIUS-X metadata is stored or a separate repository within the organization's environment. From this repository, the CI/CD pipeline is triggered for continuous integration and deployment.
