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Data as a Service

A plethora of new companies are emerging to coexist with — and sometimes replace — more traditional data vendors in the information industry. These data providers span across industries and are aggregating, curating, analyzing, and adding value to information. In some cases, they are transforming it completely and finding new ways of deriving economic value from the data such as using it in advanced analytics applications or even in cognitive/artificial intelligence products and services. This concept is known as Data as a Service (DaaS); it is defined as data delivery services that enable an organization to externally monetize raw data generated as part of the organization's ongoing operations, value-added information derived from this raw data, and/or from aggregated third-party data. IDC's DaaS definition includes the metadata from human consumable content, including, but not limited to, books, magazines, newspapers, movies, television, and recorded music; however, the content from these data types is not included in and of itself.

Markets and Subjects Analyzed

  • Open source data collection and providers
  • Personal information and mobile data vendors
  • Roles of data creators, aggregators, and brokers
  • Operational and logistics data providers
  • Internet of Things (IoT) data providers
  • Data marketplaces

Core Research

  • Data Providers Taxonomy and Market Landscape
  • Key Players
  • Data as a Service (DaaS) Services: Market Analysis and Forecast
  • Data Market Infrastructure
  • Data Enrichment and Monetization
  • Content and Data for Cognitive and Machine Learning

In addition to the insight provided in this service, IDC may conduct research on specific topics or emerging market segments via research offerings that require additional IDC funding and client investment.

Key Questions Answered

  1. What impacts are DaaS and data marketplaces having on traditional markets?
  2. How can other firms leverage DaaS to drive new business outcomes?
  3. How large is the data provider market, and how is it segmented today? What is the future opportunity?
  4. What kinds of infrastructure and capacity are data-oriented applications and services built upon?
  5. Who/what are the leading data providers, brokers, and marketplaces, what are the areas of differentiation, and why are they important?
  6. How is third-party data being collected, curated, and used in predictive and prescriptive applications, especially cognitive applications?
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Meet the Experts

Dan Vesset Group Vice President, Analytics and Information Management
David Schubmehl Research Director, Cognitive/Artificial Intelligence Systems
Lynne Schneider Research Director, Data as a Service