Why MetaKraftwerk?
Data is an indispensable resource of the 21st century. Organizations must transform to data-driven entities if they want to stay competitive and tap new business. Therefore, a crucial goal is to unlock the potentials of data allowing information being used for well informed decisions.
The original data location and structure rarely fit the needs of an efficient advanced analytics. Data integration and data engineering transform the data into better suited platforms like data lakes and data warehouses.
The original data location and structure rarely fit the needs of an efficient advanced analytics. Data integration and data engineering transform the data into better suited platforms like data lakes and data warehouses.
Metadata-driven Development
Metadata-driven data integration tools, like Informatica offer almost unlimited access to all imaginable data sources and provide a visual, low-coding platform. This allows a highly efficient development compared to hand coding approaches.
These established platforms provide essential features to operationalize and monitor data integration processes. Moreover, the metadata approach allows for the complete cataloging of the whole system environment to the point of a detailed lineage for all its data.
Problem with Manual Development
A huge achievement of metadata-driven data integration tools is the access to a huge amount of data sources and the handling of the data in an abstract, visual form. The data integration developer is relieved of technical details. Nevertheless, developers still have to design, implement and test each data integration process manually. Big projects can only scale by continually adding more developers.
This results in solving similar problems multiple times and standards are never quite followed. Repetitive work increases the error rate. Making additional management and communication efforts necessary.
In essence, data integration is a big cost driver and projects take months or even years to complete, often with high burn rates.
Over time emerges that problems are similar. Pattern become apparent. For many groups of problems the usage of a standardized and automated development approach is favored.
This results in solving similar problems multiple times and standards are never quite followed. Repetitive work increases the error rate. Making additional management and communication efforts necessary.
In essence, data integration is a big cost driver and projects take months or even years to complete, often with high burn rates.
Over time emerges that problems are similar. Pattern become apparent. For many groups of problems the usage of a standardized and automated development approach is favored.
A huge achievement of metadata-driven data integration tools is the access to a huge amount of data sources and the handling of the data in an abstract, visual form. The data integration developer is relieved of technical details. Nevertheless, developers still have to design, implement and test each data integration process manually. Big projects can only scale by continually adding more developers.
This results in solving similar problems multiple times and standards are never quite followed. Repetitive work increases the error rate. Making additional management and communication efforts necessary.
This results in solving similar problems multiple times and standards are never quite followed. Repetitive work increases the error rate. Making additional management and communication efforts necessary.
In essence, data integration is a big cost driver and projects take months or even years to complete, often with high burn rates.
Over time emerges that problems are similar. Pattern become apparent. For many groups of problems the usage of a standardized and automated development approach is favored.
Over time emerges that problems are similar. Pattern become apparent. For many groups of problems the usage of a standardized and automated development approach is favored.
Automated Development with MetaKraftwerk
Leave the treadmill of repetitive development! Just create one design pattern for each class of similar data integration processes. For implementation and test, you keep using your metadata driven data integration tool. In MetaKraftwerk, you define how the individual data integration processes will be built automatically based on the design pattern. MetaKraftwerk works fully metadata-driven and offers you a user-friendly, visual SaaS-platform.
Instance metadata define the individual data integration process properties like data fields and data types. During its build process using the design pattern and instance metadata, MetaKraftwerk computes the fully executable data integration processes in seconds. Development work that took before month or years is now available after seconds! The most efficient data integration development method!
Instance metadata define the individual data integration process properties like data fields and data types. During its build process using the design pattern and instance metadata, MetaKraftwerk computes the fully executable data integration processes in seconds. Development work that took before month or years is now available after seconds! The most efficient data integration development method!
Effort Analysis of Development Approaches
Analyzing effort and costs in data integration development, we examine separately the phases design, implementation, and test. The chart highlights these development phases for three typical approaches. Moreover, the efforts for the creation of a template or design pattern and three, executable data integration processes, also called instances, are outlined.
Effort Analysis of Development Approaches
Analyzing the effort and costs in data integration development projects, we examine separately the phases design, implementation, and test. The chart highlights these development phases for three typical approaches. Moreover, the efforts for the creation of a template or design pattern and three, executable data integration processes, also called instances, are outlined.
Template-based development
A common development approach in data integration projects is the use of templates. These semi-technical specifications define the general design of the data integration processes. The functionality itself is only implemented and tested in the actual processes. The effort reduction concerning the implementation and test, but even the design is limited.
Pattern-based manual development
Applying the explained pattern-based approach with manual instantiation allows effort reductions by designing, implementing and testing the functionality in the pattern. The functionality itself doesn’t need to be addressed within each single instance.
Nevertheless, manual effort is still necessary to adjust the processes to handle the dedicated data structure and data fields. Pattern with non-trivial functionality and respectively high complexity need to be implemented with great accuracy to minimize test efforts.
Pattern-based automated development
The manual development efforts for the instantiation are eliminated with the pattern-based automated development. The instances are created based on metadata and the automatic application of rules. Divergences from the pattern are eliminated. Therefore, test effort is minimal and only addresses the actual impact of the instance metadata. The effort for the pattern creation fully pays back and an outstanding cost function is realized.
Economies of Scale
Economies of Scale
The different efforts and their relationship to the quantity of produced instances determine the cost function of the development approach. The larger the number of intended instances, the larger the scale effect and the bigger the advantage of the automation by MetaKraftwerk. The invested effort into a careful design, implementation and test of the pattern is negligible, but the benefit of the automated implementation of the instances massive.
Benefits of MetaKraftwerk
Tremendous
Cost Savings
Tremendous Cost Savings
Reduce your development and test costs significantly. This is the crucial success factor for your data platform.
Fastest
Time-To-Market
Fastest Time-To-Market
Execute projects in record time. New technical and business-driven requirements can be fulfilled significantly faster because they are automatically implemented. Also, change requests and maintenance tasks can be addressed directly by changing the relevant metadata and apply the changes to all necessary objects of the data platform.
Agile
Development
Agile Development
Act immediately, fast and with known implications to new requirements. Small, dynamic teams specify and design. MetaKraftwerk creates the data integration processes within seconds.
Power of
Standardization
Power of Standardization
Develop ideal design patterns and not many different “unique works of art”. Exclusively the specific metadata of the processes distinguish the process instances, and not the individual quality of the development. Standardization combined with automation allow lowest development and test efforts.
Excellent
Quality
Excellent Quality
Manual errors within the development are eliminated due to the development and test of one ideal solution pattern that is based on metadata multiplied automatically by MetaKraftwerk.
Full
Functionality
Full Functionality
The Informatica platforms Informatica Cloud (IICS), PowerCenter, Developer (BDM/DEI) are fully supported.
Develop your data integration following your requirements and specifications. MetaKraftwerk allows any functionality that is available in your data integration tool.
Do you have further questions?
Contact us for more information or a personal presentation of the MetaKraftwerk platform