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Global Big Data Analytics in Manufacturing Market Growth (Status and Outlook) 2023-2029

Publisher LP Information, Inc.
Published Feb 09, 2023
Length 86 Pages
SKU # LPI17998089

Description

Global Big Data Analytics in Manufacturing Market Growth (Status and Outlook) 2023-2029


According to this study, the global Big Data Analytics in Manufacturing market size will reach US$ million by 2029.

Big data is a term used for large volume of structured and unstructured data stored on a daily basis. Further, big data analytics technique is implemented by the companies to examine market trends, hidden patterns, and other useful information, which helps in making effective business decisions.

This report presents a comprehensive overview, market shares, and growth opportunities of Big Data Analytics in Manufacturing market by product type, application, key players and key regions and countries.

Segmentation by product type:
Software
Services

Segmentation by Application:
Predictive Maintenance
Budget Monitoring
Product Lifecycle Management
Field Activity Management
Others

This report also splits the market by region:
United States
China
Europe
Other regions:
Japan
South Korea
Southeast Asia
Rest of world

The report also presents the market competition landscape and a corresponding detailed analysis of the major players in the market. The key players covered in this report:
VIS Networks
IBM
SAP
Microsoft
Oracle
SAS Institute
OpenText
Microstrategy
Information Builders
Tableau Software
Qlik Technologies

Please note: The report will take approximately 2 business days to prepare and deliver.

Table of Contents

86 Pages
*This is a tentative TOC and the final deliverable is subject to change.*
1 Scope of the Report
2 Executive Summary
3 Big Data Analytics in Manufacturing Key Players
4 Big Data Analytics in Manufacturing by Regions
5 United States
6 Europe
7 China
8 Rest of World
9 Market Drivers, Challenges and Trends
10 Key Investors in Big Data Analytics in Manufacturing
11 Key Players Analysis
12 Research Findings and Conclusion

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