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Global Neural Network Software Market 2017-2021

  • Published: Jun 2017
  • Pages: 86
  • SKU: IRTNTR14515
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This industry research report identifies Hewlett Packard Enterprise Development, IBM, Intel, Microsoft, and Qualcomm Technologies as the key vendors in the global neural network software market. The neural network software market forecast report also presents a competitive analysis of the industry by deployment model (on-premises neural network software and cloud-based neural network software), by end-user (BFSI, healthcare, and retail), and by geography (the Americas, APAC, and EMEA).

Global neural network software market overvew

Market research analysts at Technavio predict that the global neural network software market  size and share will grow steadily at a CAGR of close to 26% by 2021. This market research analysis identifies the increasing deployment of LTE wireless broadband as one of the primary factors for the neural network software market growth. The growth in Internet of Things (IoT) and the increased deployment of long-term evolution (LTE) globally have fueled the demand for LTE-enabled deep learning systems and IoT devices as they provide higher bandwidth and faster data connections. The implementation of the neural network technologies helps various enterprises in obtaining real-time information and enhancing their operations by reducing expense. Furthermore, the combination of cellular networks with neural networks enables IoT to improve the efficiency of organizations by improving speed and accuracy of the information and data shared without human intervention. Thus, the increased adoption of connected devices among consumers as well as enterprises will drive the market during the forecast period.

The increasing emergence of neural networks in different sectors is one of the latest neural network software market trends that will gain traction in the  market in the coming years. The economic growth forecasting is important to make policies on national economic development. Neural networks are an artificial intelligence (AI) method for modeling complex target functions. For some types of problems, such as learning to interpret complex real-world sensor data, artificial neural networks (ANNs) are among the most effective learning methods.

Competitive landscape and key vendors

The global neural network software market is witnessing an intense competition because of the presence of numerous vendors. Major vendors are constantly competing to attain high market shares with innovation and new development that cater to the needs of customers. Additionally, the leading vendors are acquiring small vendors to gain technological advances and strengthen their market presence.

The leading vendors in the market are -

  • Hewlett Packard Enterprise Development
  • IBM
  • Intel
  • Microsoft
  • Qualcomm Technologies

The other prominent vendors in the market include Alyuda Research, Deep Instinct, Cloudera, Cognisess, Enlitic, GUMGUM, Hu:toma Artificial Intelligence, MulticoreWare, Neurala, NeuroDimension, Palisade, Wave Computing, Ward Systems Group, XENON Systems, and XILINX.

Segmentation by deployment model and the neural network software market analysis

  • On-premises neural network software
  • Cloud-based neural network software

During 2016, the cloud-based neural network software segment accounted for the major shares of this market. The cloud-based neural network is scalable and enables the management of IT resources in a complex IT ecosystem. This software processes information centrally and streamlines the workflow of the enterprise and cloud applications are more accessible and easier to use because all that end-users need is a web browser and an Internet connection. These factors will contribute to the growth of this industry segment in the coming years.

Geographical segmentation and the neural network software market anaysis

  • Americas
  • APAC
  • EMEA

This market study estimates that in terms of geographic regions, the Americas will be the major revenue contributor to the market by 2021 because of the availability of adequate IT infrastructure and wide geographic dispersion of employees’ due to the increasing globalization. Additionally, the increased implementation of the cloud-based neural network in small and medium-sized enterprises (SMEs) and large enterprises in this region has further contributed to the market growth.

Key questions answered in the report include

  • What will the neural network software market size and the growth rate be in 2021?
  • What are the key factors driving the global neural network software market?
  • What are the key neural network software market trends impacting the growth?
  • What are the challenges to the neural network software market growth?
  • Who are the key vendors in the global neural network software market?
  • What are the market opportunities and threats faced by the vendors in the global neural network software market?
  • What are the trending factors influencing the market shares of the Americas, APAC, and EMEA?
  • What are the key outcomes of the five forces analysis of the global neural network software market?

Technavio also offers customization on reports based on specific client requirement.

 

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PART 01: Executive summary

PART 02: Scope of the report

PART 03: Research Methodology

PART 04: Introduction

  • Market outline

PART 05: Global economic overview

  • Economic overview and its impact on the market

PART 06: Market landscape

  • Market overview
  • Market size and forecast
  • Five forces analysis

PART 07: Market segmentation by deployment model

  • Global neural network software market by deployment model
  • Global on-premises neural network software market
  • Global cloud-based neural network software market
  • Difference between on-premises and cloud-based neural network

PART 08: Market segmentation by end-user

  • Global neural network software market by end-user
  • Global neural network software market by BFSI
  • Global neural network software market by healthcare
  • Global neural network software market by retail
  • Global neural network software market by others

PART 09: Geographical segmentation

  • Global neural network software market by geography
  • Neural network software market in Americas
  • Neural network software market in EMEA
  • Neural network software market in APAC

PART 10: Decision framework

PART 11: Drivers and challenges

  • Market drivers
  • Market challenges

PART 12: Trends

  • Increasing emergence of neural networks in different sectors
  • Rising use of neural network algorithm in photography
  • Increasing use of machine learning for automating customer service

PART 13: Vendor landscape

  • Competitive scenario
  • Other prominent vendors
  • Following are the vendors listed based on the framework

PART 14: Key vendor profiles

  • Hewlett Packard Enterprise Development
  • IBM
  • Intel
  • Microsoft
  • Qualcomm Technologies

PART 15: Assumptions

  • Market assumptions

PART 16: Appendix

  • List of abbreviations

Research Framework

Technavio presents a detailed picture of the market by way of study, synthesis, and summation of data from multiple sources. The analysts have presented the various facets of the market with a particular focus on identifying the key industry influencers. The data thus presented is comprehensive, reliable, and the result of extensive research, both primary and secondary.

TechnavioINFORMATION SOURCES

Primary sources

  • Manufacturers and suppliers
  • Channel partners
  • Industry experts
  • Strategic decision makers

Secondary sources

  • Industry journals and periodicals
  • Government data
  • Financial reports of key industry players
  • Historical data
  • Press releases
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TechnavioDATA ANALYSIS

Data Synthesis

  • Collation of data
  • Estimation of key figures
  • Analysis of derived insights

Data Validation

  • Triangulation with data models
  • Reference against proprietary databases
  • Corroboration with industry experts
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TechnavioREPORT WRITING

Qualitative

  • Market drivers
  • Market challenges
  • Market trends
  • Five forces analysis

Quantitative

  • Market size and forecast
  • Market segmentation
  • Geographical insights
  • Competitive landscape
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