USD 576.47 billion
Report ID:
SQMIG45A2187 |
Region:
Global |
Published Date: October, 2024
Pages:
264
|Tables:
90
|Figures:
76
Global Big Data in Manufacturing Industry Market size was valued at around USD 5.1 billion in 2022 and is expected to rise from USD 5.8 billion in 2023 to reach a value of USD 14.8 billion by 2031, at a CAGR of 12.5% over the forecast period (2024–2031).
Big data analytics is a framework for accumulating a lot of data for trend analysis and data mining. The industrialization has advanced quickly over time, and manufacturing output has been rising steadily. As a result, the manufacturing sector's enormous change in data generation is driving the global Big Data in Manufacturing Industry Market for big data analytics in this sector.
The idea of a "smart industry," where data creation and visualization occur in real-time, is being aggressively adopted by industries. The industry is now aware of the advantages that may be gained from this data volume thanks to the progression of analytics from descriptive to predictive analytics. The industrial sector is transitioning to a metrics-based industry, which can enhance decisions made using data.
Strong processing power is needed at the edge of networks due to the rise in connected devices, industrial digitalization, and the need to satisfy rising workplace demands for simple and efficient operations. Furthermore, IT teams require flexibility, consistency, and quick provisioning of both on-premises and cloud-based apps. By automating and monitoring network configuration, automatically identifying devices on the network, and troubleshooting network faults, big data in manufacturing industry systems can achieve these objectives. Big data, artificial intelligence, and machine learning are used in more advanced big data in the manufacturing industry to configure and manage networks. In addition to this, there are many open-source initiatives devoted to creating norms for virtualization-based big data in the manufacturing industry.
Despite optimistic Big Data analytics outcomes, the manufacturing sector has not yet fully tapped into the technology's potential. Big Data analytics in the manufacturing sector now have a lot of room to grow in the future. According to estimates, the manufacturing sector has varied efficiency among verticals that are similar and has a variety of factors at play. For instance, an automaker might work with a large number of suppliers and vendors to get the various parts needed to put a car together.
US Big Data In Manufacturing Industry is poised to grow at a sustainable CAGR for the next forecast year.
Global Market Size
USD 576.47 billion
Largest Segment
Software
Fastest Growth
Software
Growth Rate
26.7% CAGR
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Global Big Data in Manufacturing Industry Market is segmented by Offering, Deployment Mode, Application, and region. Based on Offering, the market is segmented into Solutions, and Services. Based on Deployment Mode, the market is segmented into On-premises, Cloud, and Hybrid. Based on Application the market is segmented into Customer Analytics, Operational Analytics, Quality Assessment, Supply Chain Management, Production Management, and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & and Africa.
Big Data in Manufacturing Industry Analysis by Type
Based on the Type, the global big data in manufacturing industry market is segmented into Software and Services. For the global manufacturing analytics Big Data in Manufacturing Industry Market to recover and overcome the effects of the imposed recession, a variety of services are needed. The segment of software has acquired the larger share from both of these due to the growing use of big data analytics tools for production forecasting and measuring business success. Due to the growing need for consulting to choose the best analytics platform, architecture evaluation, and prototyping, the service segment is anticipated to have stable growth in terms of revenue throughout the course of the forecast period.
Big Data in Manufacturing Industry Analysis by Deployment Type
Based on the Deployment type the big data in manufacturing industry market is segmented as, On-premises, Cloud based. Because of the increasing adoption of cloud technology in the manufacturing industry, the cloud-based category is likely to lead the global big data in the manufacturing market in terms of revenue contribution during the forecast period. Additionally, the growing use of cloud-based big data analytics software for easy data sharing is anticipated to further fuel market expansion over the course of the projected year. Providing the necessary help in all manufacturing sectors around the world is referred to as deployment. When analyzing the market's bifurcation for deployment, the region is crucial.
Big Data in Manufacturing Industry Analysis by Application
On the basis of Application, the Global Big data in manufacturing industry market is segmented as Predictive asset management, Inventory management, supply chain analysis, Power, and Energy. Each of these contributes in a distinctive and special way to the world's industrial sectors. In terms of revenue contribution to the global big data analytics in the manufacturing market, predictive maintenance is expected to perform better than other application segments throughout the forecast period. This is due to the growing need to reduce the number of failures that occur during production, as any system or machinery malfunction could result in supply chain disruptions. Due to the manufacturing sector's growing need to optimise supply chains, the supply chain management segment is anticipated to experience significant revenue growth during the projection period.
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In 2021, Asia Pacific held the largest global big data in manufacturing industry market share. The manufacturing industry in the Asia-Pacific is undergoing a shift as smart manufacturing gains traction in local corporate operations. This is especially true for nations like China, India, South Korea, and Japan, which serve as the primary manufacturing centers in the area and are therefore major big data analytics adopters.
Given the wide variations in government policies, infrastructure, technical skills, and research and development (R&D) spending, the level of technological innovation among industrial facilities in the expanding Asia-Pacific area remains unequal.
In the upcoming years, North America is anticipated to hold the largest Big Data in Manufacturing Industry Market share for big data in the manufacturing sector. The manufacturing sectors in the US and Canada are developing quickly, which will help the market expand in this area. In addition to North America, the market in Europe will experience significant growth over the next few years due to the presence of large manufacturing facilities in a number of the countries in this region.
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Big Data in Manufacturing Industry Driver
Increased Internet Penetration Will Boost the Market Growth
Growing Enterprise Adoption to Provide Robust Opportunities
Big Data in Manufacturing Industry Restraint
Concerns About Privacy and Security Will Act as Market Restraints
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Global big data in manufacturing industry market is has some major and medium size enterprises, with a high level of competition. Companies are working on new product launches and other initiatives to provide better equipment to their customers and expand their companies globally. These industry leaders are expanding their client base in a variety of ways, and many organizations are forming strategic and creative partnerships with other start-up businesses to increase market share and profitability.
Big Data in Manufacturing Industry Top Player's Company Profiles
Big Data in Manufacturing Industry Recent Developments
SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Co-relates, and Analyses the Data collected utilizing Primary Exploratory Research backed by the robust Secondary Desk research.
According to our Global Big Data In Manufacturing Industry Market Analysis, In 2021, the North America region led the global Big data in manufacturing industry market. The growth is attributed to the broad adoption of cutting-edge technologies like DevOps, SD-WAN, and intent-based networking. The market has grown as a result of the rising demand for deep learning AI algorithms for remotely controlling network equipment and growing investments in 5G projects. These algorithms assist market participants in providing improved automation technologies to their end consumers, such as image processing and speech recognition. According to the segmental analysis, the segment of On-premises segment acquired a larger share due to its offerings like annual service agreement and one-time license fee, which includes free installation and up-gradation of new functionalities. According to application, Telecom service providers were able to deploy more virtualization in their networks as a result of the growing adoption of NFV technologies.
Report Metric | Details |
---|---|
Market size value in Manufacturing | USD 5.1 billion |
Market size value in 2031 | USD 14.8 billion |
Growth Rate | 12.5% |
Base year | 2023 |
Forecast period | 2024–2031 |
Forecast Unit (Value) | USD Billion |
Segments covered |
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Regions covered | North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA) |
Companies covered |
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Customization scope | Free report customization with purchase. Customization includes:-
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Executive Summary
Market overview
Parent Market Analysis
Market overview
Market size
KEY MARKET INSIGHTS
COVID IMPACT
MARKET DYNAMICS & OUTLOOK
Market Size by Region
KEY COMPANY PROFILES
For the Big Data In Manufacturing Industry Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:
1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.
2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the Big Data In Manufacturing Industry Market.
3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.
4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.
Customization Options
With the given market data, our dedicated team of analysts can offer you the following customization options are available for the Big Data In Manufacturing Industry Market:
Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.
Regional Analysis: Further analysis of the Big Data In Manufacturing Industry Market for additional countries.
Competitive Analysis: Detailed analysis and profiling of additional Market players & comparative analysis of competitive products.
Go to Market Strategy: Find the high-growth channels to invest your marketing efforts and increase your customer base.
Innovation Mapping: Identify racial solutions and innovation, connected to deep ecosystems of innovators, start-ups, academics, and strategic partners.
Category Intelligence: Customized intelligence that is relevant to their supply Markets will enable them to make smarter sourcing decisions and improve their category management.
Public Company Transcript Analysis: To improve the investment performance by generating new alpha and making better-informed decisions.
Social Media Listening: To analyze the conversations and trends happening not just around your brand, but around your industry as a whole, and use those insights to make better Marketing decisions.
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Report ID: SQMIG45A2187
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