Engineering Innovation in
Digital Industry
With our project we aim at creating a platform to improve the business performances by taking advantage of the Big Data Analytics potential.
Approach & Solution
Approach
Data Science and Machine Learning (DSML) are entering a phase of greater industrialization: organizations have realized that they need to add more agility and resilience to their ML pipelines and production models, and that DSML technologies, alone or combined with Artificial Intelligence (AI), can increase their operational efficiency.
In order to accelerate the transition from proof of concept to production, they must be equipped with automation capabilities, support for the rapid prototyping of AI and Big Data Analytics applications, and with the operationalization of ML models. With ALIDA our Research&Development Lab aims to promptly address these needs in data science and ML, as well as data analytics operationalization.
In order to accelerate the transition from proof of concept to production, they must be equipped with automation capabilities, support for the rapid prototyping of AI and Big Data Analytics applications, and with the operationalization of ML models. With ALIDA our Research&Development Lab aims to promptly address these needs in data science and ML, as well as data analytics operationalization.
Solution
Using the ALIDA platform, users are able to design their own stream/batch workflows by choosing from the ALIDA catalog Big Data Analytics services and the set of big data to process, run and monitor the execution. The resulting Big Data Analytics applications can be deployed and installed in another target infrastructure with the support of a package manager that simplifies deployment within the target cluster.
ALIDA is designed and developed on top of the most cutting-edge Open Source Big Data technologies and frameworks and it is cloud-native, meaning it can scale computing and storage resources thanks to a pipeline orchestration engine that leverages Kubernetes capabilities for cloud resource management.
ALIDA is designed and developed on top of the most cutting-edge Open Source Big Data technologies and frameworks and it is cloud-native, meaning it can scale computing and storage resources thanks to a pipeline orchestration engine that leverages Kubernetes capabilities for cloud resource management.
Results
Shortened time to market for new analytic solutions
Increased flexibility and business responsiveness
Better use of business domain knowledge
Increased acceptance and embedding of DSML within business processes
Improvement of existing business applications
Project value
Innovation
Cost cutting
Process performance
Enabling Technologies
AI & Advanced Analytics
Cloud
Project Team
Research & Innovation