Currently there is an unmet need for trust and privacy in multi-party data analytics (e.g. in cloud computing). A new solution approach using hardware-based trusted execution environments is called Confidential Computing. The Zurich-based and investor-backed startup decentriq is a provider of confidential analytics software using Confidential Computing and, together with Microsoft, Intel and Google, founding member of the Confidential Computing Consortium. In this project decentriq will be supported by researchers from ZHAW in the design and validation of four software prototypes in cooperation with SIX Group, Swisscom, Intel and two other industry partners. Theprototypes form the basis for the Confidential Data Analytics Platform of decentriq, a software solution enabling confidentiality for multi-party data analytics. Furthermore, the goal is to understand adoption factors and barriers of Confidential Data Analytics in enterprises and develop a generic Confidential Analytics Canvas, a strategic template to identify new opportunities for the use of Confidential Data Analytics.