Data scientists can help to achieve value from YGL ERP. Enterprise resource planning (ERP) systems are critical for managing business processes and data within an organization. However, extracting value from ERP systems can be challenging without the right expertise and resources. Data scientists can play a significant role in helping organizations achieve value from their ERP systems by leveraging data analytics and machine learning techniques. Here are a few ways data scientists can help:

1. Data cleaning and preparation: Data scientists can help clean and prepare the data within the ERP system to ensure accuracy and consistency. They can identify and remove duplicates, fill in missing data, and ensure that the data is in the correct format for analysis.
2. Data analysis and insights: Once the data has been cleaned and prepared, data scientists can analyze the data to identify trends, patterns, and insights that can help improve business processes. They can use statistical and machine learning techniques to uncover hidden relationships within the data.
3. Predictive modeling: Data scientists can build predictive models that can help organizations make informed decisions about future business operations. For example, they can build models that predict customer demand, inventory levels, or financial performance.
4. Process automation: Data scientists can automate business processes within the ERP system to increase efficiency and reduce costs. They can use machine learning algorithms to automate tasks such as data entry, invoicing, and inventory management.

Overall, data scientists can bring a data-driven approach to ERP systems, helping organizations leverage the full potential of their data to achieve business value.