Big Data technologies and the new way of thinking about data management and analytics
The increasing volumes and variety of data, as well as the speed with which they are generated and exchanged, have made it necessary to adopt new computational and analytical models.
Traditional OLAP systems based mainly on batch processing and often limited to vertical scaling have made way for distributed technologies and stream processing systems with horizontal scalability.
Data warehousing is maturing from its traditional definition towards IoT-type scenarios by integrating predictive analytical intelligence (Machine Learning and AI).
- Architectural and functional assessmentsSupporting the building of new solutions for integrating existing systems, with a detailed examination of specific technologies and functional flows.
- Specific development consultancySupport for implementation activities in existing teams, to facilitate work peaks or increase specific skills.
- Turnkey
projectsDevelopment of new applications with teams composed exclusively of Lynx Group personnel. - Application
MaintenanceMaintenance and evolution of applications developed by Lynx or by third parties (Clients or other suppliers), to support innovation, technological transformation, and quality on an ongoing basis.
In this scenario, a whole series of innovative technologies capable of operating in the various stages of the pipeline (Edge to AI) are emerging, starting from the collection and distribution of data within the Data Lake (Edge Management and Flow Management) to the application of business intelligence and machine learning algorithms.
The Lynx group has been operating for several years in the field of Big Data technology, with extensive knowledge and consolidated experience in various frameworks and technologies such as Hadoop, Apache Spark and Apache Kafka, as well as the new modelling paradigms introduced with NoSQL databases.
Reference technologies
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Lynx has also consolidated experience and know-how in the design and development of solutions based on the Cloudera Data Platform, reaffirming its partnership with one of the leading integrated systems vendors in the big data market.