vendoriq-platform

byS Sanjana

i have to do an intership project on this topic can you help me with it the given full structure doc is there right it says completed, partiaaly completed but i have not done anything yet i have to do it from the starch can you help me just give me all the thing full correct codes in one go keep the ui design like that and add visuals, kpi charts and more every dashboards should be unique and unique with their roles and for dataset : Important Instruction Regarding the Dataset for the Project: Everyone, for the Predictive Vendor Intelligence Platform for Supplier Risk and Performance Management, you are not strictly required to find an external dataset. The core application should be developed using our own PostgreSQL database containing realistic data for vendors, purchase orders, deliveries, invoices, contracts, compliance, communication, performance, and risk. However, if you find a good-quality and relevant dataset, you are allowed and encouraged to use it, especially if you are implementing the predictive/AI part of the project. The dataset should actually relate to vendor or supplier performance and should contain useful information such as delivery delays, order history, quality, response time, issue resolution, contract compliance, or other factors that can contribute to vendor reliability and risk. Do not select a dataset just because it is available on Kaggle or another website. First check whether the columns and data are relevant to our project. You should be able to clearly explain what the dataset contains, which columns you are using, what problem you are solving with it, and how it connects to the Vendor Reliability and Risk modules. If you use the dataset for machine learning, you must clearly define what your model is predicting. For example, the model could predict a vendor's risk level, potential delivery delay, or reliability category. Simply displaying existing dataset values on a dashboard will not be considered predictive AI. You can also use the dataset as historical data to make your dashboards realistic. For example, historical vendor delivery records can be used to generate vendor performance trends, reliability scores, risk analysis, and procurement analytics. The recommended approach is to combine the external dataset, if suitable, with our application's own PostgreSQL database. The external data can provide historical information or training data, while the application database should handle the actual users, vendors, purchase orders, invoices, contracts, communications, notifications, and other application transactions. Do not waste time searching for a dataset if you cannot find one that properly fits the project. A well-designed application with realistic database data is better than using an unrelated dataset just for the sake of having one. we will have csv files for that is that ok give me the full correct code with their location in one go please