In-house development may carry long-term risks
Do you store critical business data in relational databases and need a way to allow your employees without database knowledge to edit this data securely and easily? Do you need to integrate data maintenance seamlessly into your business processes?
These highly specialized requirements often lead to the development of custom solutions today. An in-house development offers maximum flexibility for implementing individual requirements, but requires significant long-term resources for development, maintenance, security, and compliance, and carries long-term risks.
BOI FreeDa provides all the necessary functions for audit-proof maintenance of critical data and replaces complex in-house developments for this use case.
In-house development for the audit-proof maintenance of RDB data
What are the key requirements for in-house development?
- Validation and consistency logic – implementation of business rules to ensure data quality and integrity.
- Transaction and version management – traceable changes through transactions, historization, and versioning.
- Specialized maintenance and administration interfaces – custom tools for structured data entry and editing.
- Role and authorization concepts – fine-grained access control to data and functions.
- Integration interfaces – connection to other systems via APIs, ETL, or messaging.
- Auditability and logging – complete traceability of data changes.
- Error handling and data correction mechanisms – detection and correction of inconsistent data.
- Performance and scalability aspects – optimization for large data volumes and high access rates.
What are some examples, what is the effort involved in implementing them?
- Master data management (e.g., customer, product, and supplier data)
Typically involves moderate implementation effort; often includes extensive maintenance workflows and mask forms for business users without database knowledge. - Reference data management (e.g., catalogs, codes, classifications)
Moderate implementation effort; structured maintenance interfaces with validations, often accessible to operating departments. - Production or control data maintenance (e.g., machine parameters)
High implementation effort; often highly regulated workflows, approval processes, and a restricted user group. - Workflow-based approval systems for critical data changes
High implementation effort; comprehensive user-friendly workflows with roles, approvals, and audit functionality.
What is the development process like (including risks and common issues)?
- Iterative approach (e.g., agile)
Risks / Issues: Unclear or changing requirements lead to inconsistent data models and rework. - Close integration of operating and technical department
Risks / Problems: Dependence on individuals (island knowledge), lack of transfer capability. - Use of established technologies and frameworks
Risks / Problems: Technical debt due to pragmatic workarounds or inconsistent technology decisions. - Early integration into existing system landscapes
Risks / Problems: Underestimated integration efforts, inconsistencies between systems. - Start with core functions, then expand to include convenience and processes.
Risks / Problems: Lack of an overall architecture leads to fragmented hard to maintain solutions. - Accompanying documentation and training
Risks / Problems: Outdated or missing documentation complicates operation, maintenance, and auditability.
What challenges can an in-house development for the operating departments present?
- In practice, in-house systems for editing critical data are often not implemented using a structured, software-engineering approach, but are instead created by operating departments themselves using the tools available to them (e.g., Excel, Access, or similar tools).
- These solutions are often developed quickly and specifically address a particular need, but they exhibit structural weaknesses. In particular, clear data models, consistent validation mechanisms, and a clean separation of data storage, logic, and user interface are often lacking. This increases the risk of data inconsistencies, dublicates, and erroneous analyses. Furthermore, such solutions are usually only partially capable of supporting multiple users, are difficult to scale, and offer little versioning or the ability to track changes.
- Another problem is the heavy reliance on the individuals who created these solutions. Documentation, maintainability, and further development are often inadequate, which leads to increased operational costs and risks to data quality in the long term. Integration options with existing system landscapes are also generally limited.
What does BOI FreeDa offer for audit-proof table maintenance?
- BOI FreeDa is a standard solution specifically designed for the secure, traceable, and scalable editing of RDB data by users without database knowledge. All common relational databases can be connected to BOI FreeDa.
- The central user interface of BOI FreeDa enables role- and permission-based data editing and control of table data within guided maintenance processes.
- BOI FreeDa also offers the ability to integrate automated data maintenance into existing business processes—including a complete audit trail, versioning, approval workflows, and much more.
The comparison in detail
Editing RDB Data with BOI FreeDa vs. in-house development
BOI FreeDa
Can be introduced within a few
weeks
In-house development
Months to years for concept,
implementation, and testing
BOI FreeDa
Out of the box: audit trail, versioning,
traceable changes including
user and timestamps
Eigenentwicklung
Implement audit trails by yourself
and document them in an auditproof manner
BOI FreeDa
Standardized 2-, 4-, and 6-eye
processes, including change view
In-house development
Individual setup of concept and
implementation
BOI FreeDa
Seamless import/export workflows
Eigenentwicklung
Individual parsers, mappings,
and error handling
BOI FreeDa
High usability of the user interface, optimized for table maintenance without database knowledge
In-house development
Develop UI/UX concepts and all
compenents by yourself, ensuring
accesssibility
BOI FreeDa
Stable architecture for large
datasets (>10.000 tables) and many concurrent users (100+)
In-house development
Additional safeguards against
non-functional requirements
(load, latency)
BOI FreeDa
Plannable: license + implementation + operation
In-house development
Variable/increasing: development
+ maintenance + know-how
retention
BOI FreeDa
High configurability, extensibility
via APIs
In-house development
Maximum flexibility, but significant implementation effort
FAQ: Practical perspective
Which system is best in practice?
What benefits and challenges should you expect when developing in-house solutions to edit RDB data?
- Benefits: Attractive because it can be implemented quickly and cost-effectively while focusing on essential maintenance functions. Operating departments edit data in databases using their own forms or small tools. Changes are often written directly to the databases.
- Challenges: Development and implementation are time-consuming. The total cost of ownership is difficult to calculate initially. Over time, shadow IT, silos, and inconsistencies arise, along with non-standardized data maintenance processes. Governance is lacking (e.g., duplicate checks, versioning), there is no audit-proof documentation, and interfaces must be developed individually at great expense. Maintenance depends heavily on specific individuals. In the long term, this leads to high risk, high effort, and rising costs.
What benefits and challenges should you expect when using BOI FreeDa to edit RDB data?
- Benefits: Quick to use, as it is standard software. Easy calculation of the total cost of ownership. BOI FreeDa provides a central web interface for guided and audit-proof critical data maintenance in various relational databases by users without database knowledge. All applications can access a central database (single source of truth).
- Challenges: Initial integration and the implementation of governance rules. Special requirements often need to be addressed through custom logic.
What is the conclusion of the comparison for this use case?
- In-house development: Fully customizable to meet customer needs, but hardly a long time-to-value, high implementation risks, and maintenance dependens on specific individuals, which makes it less future-proof.
- BOI FreeDa: Short time-to-value, many out-of-the-box features, low implementation risks, and support and maintenance provided by the manufacturer, making it future-proof.
