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Market Highlights:

Businesses are in need of new capabilities to sustain in the market and create a competitive advantage for themselves. Due to rapid changes in technology, the enterprises are shifting towards cloud-based services to help their businesses to reduce the cost of building, running, and protecting applications, thus, accelerating business agility.

Data as a service (DaaS) is a model that provides data on demand to the users irrespective of the geography or organization separation of provider and consumer. DaaS is a cost-efficient, responsive service that lets businesses focus on selling their products, rather than sourcing, managing, and activating data.

The factors responsible for driving the market are growing adoption of big data analytics across different industry verticals and rising demand for real-time data analytics. Moreover, the market is also driven by increased adoption of cloud-based services in enterprises. Initiatives such as Bring Your Own Device (BYOD) and enterprise mobility are the major opportunities in data as a service (DaaS) market. The market is also facing a few challenges including data theft and cyber-attacks, and lack of technical expertise in data as a service (DaaS), which can potentially hinder the market growth.

Cloudera has expanded its Altus Data Science platform as a service offering to the Azure cloud. This development will preserve the business metadata and security, and governance policies so they can be implemented across data processing and data analytics workload in the cloud.

 

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Major Key Players:

  • Microsoft Corporation (U.S.)
  • IBM Corporation (U.S.)
  • Facebook, Inc. (U.S.)
  • Fair Isaac Corporation (U.S.)
  • Alibaba Group Holding Limited (China)
  • Google Inc. (U.S.)
  • Oracle Corporation (U.S.)
  • Bloomberg Finance L.P. (U.S.)
  • com, Inc. (U.S.)
  • LinkedIn Corporation (U.S.)
  • Mastercard Advisors LLC (U.S.)
  • LexisNexis Corporation (U.S.)

 

Other players in the market include comScore, Inc. (U.S.), Dow Jones & Company, Inc. (U.S.), Equifax, Inc. (Canada), Experian plc (Ireland), Acxiom Corporation (U.S.), FirstRain, Inc. (U.S.), Twitter, Inc. (U.S.), Verizon Communications, Inc. (U.S.), SAS Institute Inc. (U.S.), and EMC Corporation (U.S.).

 

Regional Analysis:

The global market for Data as a Service Market is estimated to grow at a significant rate during the forecast period 2018 – 2023. The geographical analysis of data as a service market is covered for the regions such as North America, Europe, Asia Pacific, and rest of the world. Due to technological advancements in North America, the region is expected to lead the market during the forecast period. Also, owing to the developed and well-established economies, the companies in North America are majorly investing in research and development activities.

 

U.S. based company Salesforce has acquired application network platform MuleSoft as part of the company’s effort to expand its ecosystem into cross-platform application management. The Salesforce Integration Cloud is a unified platform useful for small businesses to maintain multiple cloud systems and apps through different portals as they scale their businesses to various geographies.

 

Segmentation:

  • By deployment, the market is segmented into public cloud, private cloud, and hybrid cloud.
  • By organization size, the market is segmented into small and medium enterprise, and large enterprise.
  • By end user, the market is segmented into BFSI, healthcare, retail, manufacturing, media & entertainment, transportation, IT & telecom, and others.
  • By pricing model, the market is segmented into volume-based pricing model and data type-based pricing model. Volume-based pricing model includes quantity based pricing and pay per use pricing.
  • By solution, the market is segmented into disaster recovery and backup solution, test data management, data warehousing, data migration, and others.
  • By professional services, the market is segmented into implementation & deployment, support & maintenance, and consulting.

 

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Intended Audience:

  • 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

 

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