Data as a Service and Data Marketplaces

Related Links

Meet the Experts

Photo of Lynne Schneider
Lynne Schneider

Research Director, Data as a Service & Location and Geospatial Intelligence

Data fuels digital business. Consumption of external data continues to rise, and organizations continue to explore opportunities for external data monetization. A plethora of new data providers are emerging to coexist with — and sometimes replace — more traditional data vendors in the information industry. These companies are aggregating, curating, analyzing, and adding value to information. This data is being used to augment organizations' internal data sets to improve business processes and decision making, to train cognitive/AI solutions, and to wrap around other products or services. When two or more organizations buy, sell, or trade machine-readable data in exchange for something of value, this concept is known as data as a service (DaaS). IDC's Data as a Service and Data Marketplaces market research and advisory service covers DaaS supply and demand trends.

Markets and Subjects Analyzed

  • Open source and proprietary data collections and providers
  • Developing DaaS capabilities
  • Data creation, aggregation, and enrichment
  • Data marketplaces
  • Data monetization, including packaging, pricing, and channels
  • DaaS use cases
  • Training data for cognitive/AI solutions

Core Research

  • Data Providers' Taxonomy and Market Landscape
  • Key Players and Competitive Positioning
  • Market Analysis and Forecast
  • Predictions
  • End-User Demand Trends
  • Buyer and Vendor Case Studies

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. How large is the DaaS market, and how is it segmented today? What is the future opportunity?
  2. Who/what are the leading data providers and marketplaces, what are the areas of differentiation, and why are they important?
  3. How is third-party data being collected, curated, and used in predictive and prescriptive applications and other workflows?
  4. What is the range of pricing and go-to-market strategies? How do these fit with existing analytics and other ecosystems?
  5. How can companies leverage DaaS to create new assets and monetize their current data?
  6. How are regulatory developments (e.g., GPDR, other privacy-related developments) impacting the development of this market?