Member - Modeo

At Modeo, we are passionate about data and our mission is to help our clients unlock their potential using data management best practices. We are involved in: - in consulting - designing and implementing robust architectures to enable informed analysis and accurate interpretation of data - the placement of our data engineers to support, reinforce and advise teams on technical projects. Modeo enables companies to make informed strategic decisions by implementing robust data architectures for accurate data analysis and interpretation. In parallel, we have developed the Stash® solution which is the result of our internal research and development. "Our tool meets a crucial need that we have identified among our customers during our consulting missions: to facilitate the adoption of tools by business teams", says Matthieu Rousseau. Our solution is unique on the market and provides a comprehensive view of data usage, including cost and carbon impact, making it the essential tool for effective data exploitation in companies. #RSE > This approach has enabled us to develop a unique solution on the data market, which was awarded the 'Innovative Solutions' prize at the Data Night on February 6th 2023. Namely: Defining the implementation of a modern data platform at a client's site requires several key elements: 1. Business goals: The first step is to understand the startup's business goals and identify the data requirements to achieve them. This may include goals such as improving the customer experience, optimizing operations, identifying new market opportunities, etc. 2. Evaluation of existing data: Assessing existing data is important for understanding data gaps and opportunities for additional data collection. This involves identifying available data sources, data gaps, data errors, and opportunities to improve data quality. 3. Data Infrastructure: Establishing a robust data infrastructure is essential for storing and processing data. This may include the implementation of a database management system (DBMS), data warehouse, real-time stream processing system, or other tools. 4. Data Analysis Tools: Data analysis tools are important for extracting actionable information from data. This can include tools such as dashboards, data mining tools, data visualization tools, etc. 5. Data Security: Data security is essential to protect data from internal and external threats. This can include measures such as authentication and authorization, access management, activity monitoring, etc. 6. Qualified personnel: Implementing a modern data platform requires skilled personnel to design, develop, and maintain the platform. This may include data scientists, data engineers, data architects, data analysts, etc.