Data Analytics has proven its importance in knowledge discovery and decision support in different data and application domains. Big data analytics poses a serious challenge in terms of the necessary hardware and software resources. The cloud technology today offers a promising solution to this challenge by enabling ubiquitous and scalable provisioning of the computing resources. However, there are further challenges that remain to be addressed such as the availability of the required analytic software for various application domains, estimation and subscription of necessary resources for the analytic job or workflow, management of data in the cloud, and design, verification and execution of analytic workflows. We present a taxonomy for analytic workflow systems to highlight the important features in existing systems. Based on the taxonomy and a study of the existing analytic software and systems, we propose the conceptual architecture of CLoud-based Analytics-as-a-Service (CLAaaS), a big data analytics service provisioning platform, in the cloud. We outline the features that are important for CLAaaS as a service provisioning system such as user and domain specific customization and assistance, collaboration, modular architecture for scalable deployment and Service Level Agreement.