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Global Big data as a Service Market 2016-2020

  • April 2016
  • -
  • Infiniti Research Limited
  • -
  • 92 pages

About Big-data as a Service

With the rise in IT consumerization, technology has created a new platform for financial applications, helping banks to collect, consolidate, and consume information to change the engagement model with customers through websites and mobile applications.
With the rise in mobile workforce and consumer expectation, financial institutions are gearing up their efforts to attract, retain, and grow their next-generation IT-driven bankers. However, many industry verticals are struggling to act quickly to meet the expectations of online customers due to fragmented processes, legacy technology infrastructure, and ingrained businesses.
Financial service is in a positive stage for the adoption of big data. Most financial services currently focus on improving their traditional data infrastructure and address issues such as customer data management, risk, workforce mobility, and multichannel effectiveness. These consistent problems have led financial organization to deploy big data as a long-term strategy.

Technavio’s analysts forecast the global big data as a service market to grow at a CAGR of 60.9% during the period 2016-2020.

Covered in this report
The report covers the present scenario and the growth prospects of the global big data as a service market for 2016-2020. To calculate the market size, the report considers the revenue generated from the three segments: Hadoop as a service (HaaS), data platform as a service (PaaS), and analytics as a service that consists of consulting and advisory services as well.


The market is divided into the following segments based on geography:
- Americas
- APAC
- EMEA

Technavio's report, Global Big-data as a Service Market 2016-2020, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the market landscape and its growth prospects over the coming years. The report also includes a discussion of the Key vendorsoperating in this market.

Key vendors
- HP Co.
- IBM Corp.
- SAP SE
- SAS Institute Inc.
- Teradata


Other prominent vendors
- 1010data
- Accenture
- Alteryx
- Altiscale
- Atos
- Attivio
- Chartio
- Cirro
- ClearStory Data
- Cloudera
- Continuum Analytics
- Datameer
- DataStax
- Doopex
- EMC
- Enthought
- Hortonworks
- MAANA
- MapR Technologies
- MarkLogic
- Microsoft
- MongoDB
- Mu Sigma
- Predixion Software

Market driver
- Increased use of cloud-based predictive analytics
- For a full, detailed list, view our report

Market challenge
- Data integration issues
- For a full, detailed list, view our report

Market trend
- Rise in spending on customer engagements
- For a full, detailed list, view our report

Key questions answered in this report
- What will the market size be in 2020 and what will the growth rate be?
- What are the key market trends?
- What is driving this market?
- What are the challenges to market growth?
- Who are the key vendors in this market space?
- What are the market opportunities and threats faced by the key vendors?
- What are the strengths and weaknesses of the key vendors?

You can request one free hour of our analyst’s time when you purchase this market report. Details are provided within the report.

Table Of Contents

Global Big data as a Service Market 2016-2020
PART 01: Executive summary
- Highlights
PART 02: Scope of the report
- Market overview
- Top-vendor offerings
PART 03: Market research methodology
- Research methodology
- Economic indicators
PART 04: Introduction
- Key market highlights
- Market overview
- Market size and forecast
- Five forces analysis
PART 05: Application segmentation
- Global big data as a service by application
- HaaS
- Global analytics as a service
- Global data PaaS market
PART 06: End-user segmentation
- Global big data as a service by end-user
PART 07: Geographical segmentation
- Global big data as a service by geography
- Americas
- EMEA
- APAC
PART 08: Market drivers
PART 09: Impact of drivers
PART 10: Market challenges
PART 11: Impact of drivers and challenges
PART 12: Market trends
PART 13: Vendor landscape
- Competitive scenario
- Other prominent vendors
PART 14: Key vendor analysis
- HP
- IBM
- SAP
- SAS
- Teradata
PART 15: Appendix
- List of abbreviation
PART 16: Explore Technavio





Exhibit 01: Product offerings
Exhibit 02: Applications of big data
Exhibit 03: Level of abstraction in big data analytics as a service
Exhibit 04: Global API as a service market 2015-2020 ($ billions)
Exhibit 05: Five forces analysis
Exhibit 06: Global big data as a service by application 2015
Exhibit 07: Global big data as a service market by application 2015-2020
Exhibit 08: Global HaaS market 2015-2020 ($ billions)
Exhibit 09: Global analytics as a service market 2015-2020 ($ billions)
Exhibit 10: Global data PaaS market 2015-2020 ($ billions)
Exhibit 11: Global big data as a service by end-user 2015
Exhibit 12: Global big data as a service by end-user 2015-2020
Exhibit 13: Global big data as a service by geography 2015
Exhibit 14: Key activities in cloud-based predictive analytics
Exhibit 15: Impact of drivers
Exhibit 16: Impact of drivers and challenges
Exhibit 17: Other prominent vendors
Exhibit 18: HP: Business segmentation by revenue 2014
Exhibit 19: HP: Business segmentation by revenue 2013 and 2014 ($ billions)
Exhibit 20: HP: Geographical segmentation by revenue 2014
Exhibit 21: HP: HPE Big Data Platform products, services, and solutions
Exhibit 22: HP: Recent developments
Exhibit 23: IBM: Product portfolio
Exhibit 24: IBM: Services
Exhibit 25: IBM: Business segmentation by revenue 2014
Exhibit 26: IBM: GTS segment by revenue 2013 and 2014 ($ billions)
Exhibit 27: IBM: GBS segment by revenue 2013 and 2014 ($ billions)
Exhibit 28: IBM: Featured big data solutions
Exhibit 29: IBM: Big data products
Exhibit 30: IBM: Recent developments
Exhibit 31: SAP: Business segmentation by revenue 2014
Exhibit 32: SAP: Business segmentation by revenue 2013 and 2014 ($ billions)
Exhibit 33: SAP: Geographical segmentation by revenue 2014
Exhibit 34: SAP: Big data solutions
Exhibit 35: SAP: Recent developments
Exhibit 36: SAS: Business segmentation by industry 2014
Exhibit 37: SAS: Revenue segmentation by geography 2014
Exhibit 38: SAS: Key solutions
Exhibit 39: SAS: Product categories
Exhibit 40: Teradata: Business segmentation by revenue 2014
Exhibit 41: Teradata: Business segmentation by revenue 2013 and 2014 ($ billions)
Exhibit 42: Teradata: Geographical segmentation by revenue 2014
Exhibit 43: Teradata: Recent developments

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