Optimise the use of your data
Accelerate your digital transformation and your "Data-Driven" approach with a trusted partner
Big data can prove to be a major competitive advantage, but only if the data is properly used. The DataOps approach, a mixture of organisational and technological best practices, aims to facilitate and accelerate access to, and use of, data. The goal: "Self-Service" and real-time data ("Fast Data")..
« Having a good approach to data management has never been more important than it is today for financial services players »
FINEDIGIT supports financial institutions in the choice, architecture, integration and optimisation of big data, data management and data science solutions.
Our unique position combining functional financial knowledge and technological expertise, our independence, and our experience with major accounts enable us to respond effectively to the challenges of your data optimisation projects.
Our DataOps offering covers development, quality assurance, data science and exploitation :
• ARCHITECTURE AND OPERATIONS : Choice, development and maintenance of Big Data infrastructures
• DATA ENGINEERING : Development, optimisation
• DATA MANAGEMENT : Quality assurance, traceability, and data security
• DATA SCIENCE : Data analytics, Machine Learning, and Dataviz
WHY FINEDIGIT ?
- An approach based on business and not just on technology
- Implementation of DataOps methods, inspired by DevOps and Lean Manufacturing, to facilitate interaction between all the players involved in data, and reduce the Data Analytics lifecycle
- Experience from successful Data Science use cases in the banking and insurance industry
« 27% of corporate Finance departments plan to deploy Artificial Intelligence systems by 2020 » (Gartner)
Business expertise :
• Fraud detection
• Risk analysis
• Regulatory compliance
• Credit analysis
• Predictive maintenance
Technical expertise :
• Big Data : Hadoop, ElasticSearch, Neo4j, Kafka, Spark, Flink
• Data Management : Delphix, Pachyderm, Quilt, DataKitchen
• Data Science : Python, R, Scala, Tensorflow, Dataiku, Domino
• Dataviz : Tableau, Qlickview, PowerBI, SAS, MicroStrategy