Vancouver, BC -- (SBWIRE) -- 02/25/2021 -- The Big Data Analytics in Manufacturing Market study sheds light on industry profiles across several countries and regions. The extensive document is a rich source of information on market size, share and growth rate. The industry profiles discussed in the Big Data Analytics in Manufacturing Industry report further identifies market segmentation, profit, and competitive landscape and offers forecast information on industry performance and trends for the period, 2021 to 2028. The detailed report offers comprehensive analyses about a particular market situation within a geographic region.

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big data analytics in manufacturing had a market size of USD 1.11 Billion in 2020 and is expected to register a CAGR of 33.1% during the forecast period. The global big data analytics in manufacturing market revenue is expected to grow significantly over the forecast period due to increasing application of big data analytics in manufacturing industry for demand forecasting. Growing demand for solutions to optimize assets is projected to further propel global big data analytics in manufacturing market growth during the forecast period.

Big data analytics in manufacturing market is fragmented, with a substantial number of large- and medium-sized players accounting for a significant share in the global market revenue. Some of the top players are:

Microsoft Corporation
International Business Machines Corporation
Oracle Corporation
SAP SE
SAS Institute Inc.
TIBCO Software Inc.
Alteryx Inc.
Fair Isaac Corporation
MicroStrategy Incorporated
Angoss Software Corporation

The global Big Data Analytics in Manufacturing market is broadly segmented on the basis of different product types, application range, end-use industries, key regions, and an intensely competitive landscape. This section of the report is solely targeted at readers looking to select the most appropriate and lucrative segments of the Big Data Analytics in Manufacturing sector in a strategic manner. The segmental analysis also helps companies interested in this sector make optimal business decisions and achieve their desired goals.

Emergen Research has segmented the global big data analytics in manufacturing market on the basis of component, deployment, application, and region.

Component Outlook (Revenue, USD Billion; 2021–2028)
Solution
Service

Deployment Outlook (Revenue, USD Billion; 2021–2028)
On-Premises
Cloud-Based

Application Outlook (Revenue, USD Billion; 2021–2028)
Predictive Quality
Predictive Maintenance
Anomaly Detection
Tool Life-cycle Optimization
Computer Vision
Supply Chain Management
Production Forecasting
Work Cell Optimization
Product Lifecycle Management (PLM)
Others

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This section of the report offers valuable insights into the geographical segmentation of the Big Data Analytics in Manufacturing market, alongside estimating the current and future market valuations based on the demand-supply dynamics and pricing structure of the leading regional segments. Furthermore, the growth prospects of each segment and sub-segment have been meticulously described in the report.

The report classifies the global Big Data Analytics in Manufacturing market into various regions, including:

North America (U.S., Canada)
Latin America (Chile, Brazil, Argentina, Rest of Latin America)
Europe (U.K., Italy, Germany, France, Rest of EU)
Asia Pacific (India, Japan, China, South Korea, Australia, Rest of APAC)
Middle East & Africa (Saudi Arabia, the U.A.E., South Africa, Rest of MEA)

Report Highlights:

The report conducts a comparative assessment of the leading market players participating in the global Big Data Analytics in Manufacturing market.
The report marks the notable developments that have recently taken place in the Big Data Analytics in Manufacturing industry
It details on the strategic initiatives undertaken by the market competitors for business expansion.
It closely examines the micro- and macro-economic growth indicators, as well as the essential elements of the Big Data Analytics in Manufacturing market value chain.
The repot further jots down the major growth prospects for the emerging market players in the leading regions of the market.

Table of Content

Chapter 1. Methodology & Sources

    1.1. Market Definition

    1.2. Research Scope

    1.3. Methodology

    1.4. Research Sources

          1.4.1. Primary

          1.4.2. Secondary

          1.4.3. Paid Sources

    1.5. Market Estimation Technique

Chapter 2. Executive Summary

    2.1. Summary Snapshot, 2021-2028

Chapter 3. Key Insights

Chapter 4. Big Data Analytics in Manufacturing Market Segmentation & Impact Analysis

    4.1. Big Data Analytics in Manufacturing Market Segmentation Analysis

    4.2. Industrial Outlook

          4.2.1. Market indicators analysis

          4.2.2. Market drivers analysis

                    4.2.2.1. Increasing application of big data analytics in manufacturing industry for demand forecasting.

                    4.2.2.2. Growing demand for solutions for asset optimization

                    4.2.2.3. Rising need for solution to reduce downtime

                    4.2.2.4. Increasing demand for tools for faster integration of automation

          4.2.3. Market restraints analysis

                    4.2.3.1. Data breach issue

                    4.2.3.2. The high cost of implementation

    4.3. Technological Insights

    4.4. Regulatory Framework

    4.5. Porter's Five Forces Analysis

    4.6. Competitive Metric Space Analysis

    4.7. Price trend Analysis

    4.8. Covid-19 Impact Analysis

Chapter 5. Big Data Analytics in Manufacturing Market By Component Insights & Trends Revenue (USD Billion) 

    5.1. Component Dynamics & Market Share, 2020 & 2028

          5.1.1. Solution

          5.1.2. Service

Chapter 6. Big Data Analytics in Manufacturing Market By Deployment Insights & Trends Revenue (USD Billion) 

    6.1. Deployment Dynamics & Market Share, 2020 & 2028

          6.1.1. On-Premises

          6.1.2. Cloud-Based

Chapter 7. Big Data Analytics in Manufacturing Market By Application Insights & Trends Revenue (USD Billion) 

    7.1. Application Dynamics & Market Share, 2020 & 2028

          7.1.1. Predictive Quality

          7.1.2. Predictive Maintenance

          7.1.3. Anomaly Detection

          7.1.4. Tool Life-cycle Optimization

          7.1.5. Computer Vision

          7.1.6. Supply Chain Management

          7.1.7. Production Forecasting

          7.1.8. Work Cell Optimization

          7.1.9. Product Lifecycle Management (PLM)

          7.1.10. Others

Continue…!

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