Big Data Markets, 2026: Data Volume and Variety, Increasing Adoption of Big Data by Enterprises and Telecom, Maturation of Big Data Software, Continued Investments in Big Data by Web Giants

DUBLIN, Feb. 8 2021 /PRNewswire/ -- The "Big Data Market by Leading Companies, Solutions, Use Cases, Infrastructure, Data Integration, IoT Support, Deployment Model and Services in Industry Verticals 2021 - 2026" report has been added to ResearchAndMarkets.com's offering.

This report provides an in-depth assessment of the global big data market, including business case issues/analysis, application use cases, vendor landscape, value chain analysis, and a quantitative assessment of the industry with forecasting from 2021 to 2026. This report also evaluates the components of big data infrastructure and security framework.

This report also provides an analysis of leading big data solutions with key metrics such as streaming IoT data analytics revenue for leading providers such as Teradata, IBM, Oracle, SAS, and Datameter. The report evaluates, compares, and contrasts vendors, and provides a vendor ranking matrix. Analysis takes into consideration solutions integrating both structured and unstructured data.

Big data solutions are relied upon to gain insights from data files/sets so large and complex that it becomes difficult to process using traditional database management tools and data processing applications. The publisher sees key solution areas for big data as commerce, geospatial, finance, healthcare, transportation, and smart grids. Key technology integration includes AI, IoT, cloud and high-performance computing.

AI facilitates the efficient and effective supply of information to enterprises for optimized business decision-making. Some of the biggest opportunity areas are commercial applications, search in the big data environment, and mobility control for the generation of actionable business intelligence.

In terms of big data integration with cloud-based infrastructure, cloud solutions allow companies that previously required large investments into hardware to store data to do the same through the cloud at a lower cost. Companies save not only money but physical space where this hardware was previously stored. The trend to migrate to big data technologies is driven by the need for additional information derivable from analysis of all of the electronic data available to a business.

To realize the true potential to transform intelligence information from the huge amount of unstructured data, government agencies cannot leverage traditional data management technologies and DB techniques in terms of processing data. To understand patterns that exist in unstructured data, government agencies apply statistical models to large quantities of unstructured data.

Select Report Findings:

• Big data in SCM will exceed $6.6B globally by 2026
• Data Integration and Quality Tools $9.9B globally by 2026
• Enterprise performance analytics will reach $27.8B globally by 2026
• Big data in business intelligence applications will reach $50.4B by 2026
• Combination of AI and IoT (AIoT) will rely upon advanced big data analytics software
• Real-time data will be a key value proposition for all use cases, segments, and solutions
• Market leading companies are rapidly integrated big data technologies with IoT infrastructure

Key Topics Covered:

1.0 Executive Summary

2.0 Introduction
2.1 Big Data Overview
2.1.1 Defining Big Data
2.1.2 Big Data Ecosystem
2.1.3 Key Characteristics of Big Data
2.2 Research Background
2.2.1 Scope
2.2.2 Coverage
2.2.3 Company Focus

3.0 Big Data Challenges and Opportunities
3.1 Securing Big Data Infrastructure
3.1.1 Big Data Infrastructure
3.1.2 Infrastructure Challenges
3.1.3 Big Data Infrastructure Opportunities
3.2 Unstructured Data and the Internet of Things
3.2.1 New Protocols, Platforms, Streaming and Parsing, Software and Analytical Tools
3.2.2 Big Data in IoT and Lightweight Data Interchange Format
3.2.3 Big Data in IoT and Lightweight Protocols
3.2.4 Big Data in IoT and Network Interoperability Protocols
3.2.5 Big Data in IoT Data Processing Scalability

4.0 Big Data Technologies and Business Cases
4.1 Big Data Technology
4.1.1 Hadoop
4.1.1.1 Other Apache Projects
4.1.2 NoSQL
4.1.3 MPP Databases
4.1.4 Other Technologies
4.2 Emerging Technologies, Tools, and Techniques
4.2.1 Streaming Analytics
4.2.2 Cloud Technology
4.2.3 Search Technologies
4.2.4 Customizes Analytics Tools
4.2.5 Keywords Optimization
4.3 Big Data Roadmap
4.4 Market Drivers
4.4.1 Data Volume an Variety

For more information about this report visit https://www.researchandmarkets.com/r/wlf6cl

Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.

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