Numbers for Big Data Vendor Revenue and Forecast

Comments on 'Numbers for Big Data Vendor Revenue and Forecast'

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  From our original report-- the information below details the methodology. We also used financial analysis of startup business models working with the venture community.
  
  Confidence-wise we would say the market project, as defined, is as solid as any typical supply-side oriented forecast that is the early stages of development. Having performed this research now for several years I would say comfortably that the information continues to improve annual as we get more feedback from the community. However, many components of the forecast were modeled or even educated guesses based on survey work and historical data about IT markets. For example - some markets such as services are so fragmented and so local in nature it would not have been possible to identify all the suppliers. Other sectors such as Hadoop were much easier to identify (albeit with less history).
  
  On a scale of 1-10, where 1 is a total SWAG and 10 is absolute 100% confidence I would give this work a 6.5-7, depending on the segment.
  
  Methodology
  Regarding methodology, the Big Data market size, forecast, and related market-share data was determined based on extensive research of public revenue figures, media reports, interviews with vendors, venture capitalists and resellers regarding customer pipelines, product roadmaps, and feedback from the Wikibon community of IT practitioners.
  
  Many vendors were not able or willing to provide exact figures regarding their Big Data revenue, and because many of the suppliers are privately held, Wikibon had to triangulate various types of information to determine our final figures. We also held extensive discussions with former employees of Big Data companies to further calibrate our models.
  
  Information types used to estimate revenue of private Big Data vendors included supply-side data collection, number of employees, number of customers, size of average customer engagement, amount of venture capital raised, and age of vendor.
  
  Big Data Definitions
  It is critically important to understand how Wikibon defines Big Data as it relates to the market size overall and to revenue estimates for specific vendors in particular. Wikibon’s definition of Big Data contains two equally important parts.
  
  First, from a technology perspective, Wikibon defines Big Data as those data sets whose size, type, and speed-of-creation make them impractical to process and analyze with traditional database technologies and related tools in a cost- or time-effective way.
  
  Second, Wikibon believes Big Data requires practitioners to embrace an exploratory and experimental mindset regarding data and analytics, one that replaces gut instinct with data-driven decision-making, and exchanges stubbornness for a willingness to question long-held assumptions. Projects whose processes are informed by this mindset meet Wikibon’s definition of Big Data, even in cases where some of the tools and technology involved may not.
  
  Based on the above definition, Wikibon includes the following products and services under the umbrella of Big Data:
  
  Hadoop software and related hardware;
  NoSQL database software and related hardware;
  Next-generation data warehouses/analytic database software and related hardware;
  Non-Hadoop Big Data platforms, software, and related hardware;
  In-memory – both DRAM and flash – databases as applied to Big Data workloads;
  Data integration and data quality platforms and tools as applied to Big Data deployments;
  Advanced analytics and data science platforms and tools;
  Application development platforms and tools as applied to Big Data use cases;
  Business intelligence and data visualization platforms and tools as applied to Big Data use cases;
  Analytic and transactional applications as applied to Big Data use cases;
  Big Data support, training, and professional services.

  
  

  Posted By:David Vellante| Mon Nov 03, 2014 10:49

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  I appreciate the quick response, David.
  
  The data points I am particularly interested in pertain to the Hadoop software and related services. Is there any possibility for you to share the underlying data for your report?

  
  

  Posted By:Ken Wong| Mon Nov 03, 2014 10:54

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