Rapid Data Science Methodology (RDSM) is a framework for carrying out data science projects in an agile and iterative way, with a focus on delivering value quickly. RDSM consists of five main stages:
Business Understanding: The first stage is to understand the business problem or question that needs to be addressed. This involves identifying the stakeholders, their requirements, and the expected outcomes.
Data Acquisition and Understanding: The second stage involves collecting the relevant data, exploring and cleaning it, and understanding its quality and completeness. This stage is critical for ensuring that the data is fit for purpose and can support the analysis.
Modeling: The third stage involves developing models to answer the business question or solve the problem. This can involve a range of techniques, such as machine learning, statistical analysis, or optimization. The aim is to build models that are accurate, robust, and interpretable.
Deployment: The fourth stage involves deploying the models in a production environment and integrating them with the business processes. This requires careful planning and coordination with the IT team and the business stakeholders.
Monitoring and Maintenance: The final stage involves monitoring the performance of the models and maintaining them over time. This includes tracking their accuracy, identifying any drift or deterioration in performance, and updating them as needed.
The RDSM framework emphasizes the importance of collaboration between the data scientists, the business stakeholders, and the IT team. It also encourages an iterative and agile approach, where each stage is carried out in a rapid and iterative way, with frequent feedback and adjustments. This allows for rapid experimentation, learning, and improvement, and enables the team to deliver value quickly and continuously. Data Science Classes in Pune
