摘要: Analytics technologies that mine large amount of structured and unstructured data to gain insights are becoming increasingly important to businesses. In particular, the growing availability of enterprise proprietary data, coupled ... 展开 Analytics technologies that mine large amount of structured and unstructured data to gain insights are becoming increasingly important to businesses. In particular, the growing availability of enterprise proprietary data, coupled with publically aggregated or acquired data allows analytics to gain insights not only about the enterprise itself, but also cross companies, industry, and cross industries. The impact of such analysis is that it is transforming business processes and driving strategic business decision making and business model transformations, all of which overshadow more traditional low level, siloed, tactical optimizations. Such analytics trends are driving shifts in the overall analytics ecosystem that includes data providers and aggregators, analytics technology and service providers, clients in different industries, partners, and other related communities, e.g., visualization providers, academia, open source development communities. In particular, we have observed the emergence of two new service entities in the overall ecosystem: § New forms of data services that aggregate and provide accesses to a wide range of public and private data by partnering with data providers, aggregators, and clients are emerging. We call such services "Data as a Service (DaaS)" in this paper. DaaS can leverage commonly managed Cloud and Web based infrastructure and tools as well as hosted and Web delivery models to offer rich set of data processing, management, and access services, in addition to in house implementations. § On top of DaaS, one can create high value analytics services that can boost productivity and create value for all. Such services may include Business Intelligence reporting, text analytics, and advanced analytics such as predictive modeling, all made in composable forms to allow for direct consumption, integration and customizations. We call such services "Analytics as a Service (AaaS)". DaaS and AaaS help to maximize value for the overa--ll ecosystem by eliminating common costs and delivering high value data and analytics services. Their emergence is transforming the overall analytics ecosystem and forcing significant cost structure and productivity model shifts, i.e., where to cut cost and where to make money -- two key metrics to a business model. As a result, they are driving the emergence of new business models across the overall analytics ecosystem. In this paper, we will analyze the major analytics ecosystem trends. We show that our analysis suggests that there is an analytics ecosystem transformation undergoing. The new ecosystem will increasingly leverage new forms of data and analytics services and roles, e.g., DaaS and AaaS, to maximize value for the overall ecosystem. Such ecosystem changes drive shifts in enterprise cost structures and productivity and value creation models and creates a force for business model innovation. We will describe an evolution of business models around the analytics ecosystem and highlight the emerging business models that are enabled by the new ecosystem, many of which have an open, collaboration, and co-developing spirit. We will also present several real-world case studies to illustrate how the new ecosystem can maximize value for all by implementing innovative business models. 收起