Plant data quality can be improved by using tools such as data reconciliation and optimal experimental design. This report provides an overview of the main features of these methodologies and their application to industrial case studies. Following some information on the project context (Section 1), this report is divided into four main sections: (Section 2) principles and available tools for data reconciliation, (Section 3) practical applications, challenges and perspectives, (Section 4) optimal experimental design and sensor placement and (Section 5) application to specific case studies. General conclusions and take-home messages are provided in Section 6. More information and links to the webpages on the software packages and of the review studies can be found in the Excel file available as well.