Updated Research Report of Big Data in Internet of Things Market 2020-2025:
Overview:
This report evaluates the technologies, companies, and solutions for leveraging big data tools and advanced analytics for IoT data processing. Emphasis is placed on leveraging IoT data for process improvement, new and improved products, and ultimately enterprise IoT data syndication. The report includes detailed forecasts for 2020 through 2025.
Data that is uncorrelated and does not have a pre-defined data model and is not organized in a pre-defined manner requires special handling and analytics techniques. The common industry term, big data, represents unstructured data sets that are large, complex, and prohibitively difficult to process using traditional management tools. As the Internet of Things (IoT) progresses, there will be an increasingly large amount of unstructured machine data. The growing amount of human-oriented and machine-generated data will drive substantial opportunities for AI support of unstructured data analytics solutions.
Big data in IoT is different from conventional IoT and thus will require more robust, agile and scalable platforms, analytical tools and data storage systems than conventional big data infrastructure. Looking beyond data management processes, IoT data itself will become extremely valuable as an agent of change for product development as well as identification of supply gaps and realization of unmet demands. Big data and analytics will increase in importance as IoT evolves to become more commonplace. Data generated through sensors embedded in various things/objects will generate massive amounts of unstructured (big) data on a real-time basis that holds the promise for intelligence and insights for dramatically improved decision processes.
Big data in IoT is also dissimilar than non-machine related analytics and thus will require more robust, agile and scalable platforms, analytics tools, and data storage systems than conventional infrastructure. Due to this new architecture approach, the need to handle data differently, and the sheer volume of unstructured data, there will be great opportunities for big data in IoT. Analytics used in IoT will become an enabler for the entire IoT ecosystem as enterprise begin to take advantage of new business opportunities such as syndicating their own data.
Segmentation by type: breakdown data from 2015 to 2020 in Section 2.3; and forecast to 2025 in section 10.7.SolutionsServices
Segmentation by application: breakdown data from 2015 to 2020, in Section 2.4; and forecast to 2025 in section 10.8.Security & Emergency ManagementInventory ManagementSales & Customer ManagemenEnergy ManagementRemote MonitoringPredictive Maintenance & Asset ManagementOthers
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This report also splits the market by region: Breakdown data in Chapter 4, 5, 6, 7 and 8.AmericasUnited StatesCanadaMexicoBrazilAPACChinaJapanKoreaSoutheast AsiaIndiaAustraliaEuropeGermanyFranceUKItalyRussiaMiddle East & AfricaEgyptSouth AfricaIsraelTurkeyGCC Countries
The report also presents the market competition landscape and a corresponding detailed analysis of the major vendor/manufacturers in the market. The key manufacturers covered in this report: Breakdown data in in Chapter 3.AccentureDell EMCActian CorporationAmazonAPTEAN (Formerly CDC Software)AlationCisco SystemsBosch Software Innovations: Bosch IoT SuiteDatameerCerner CorporationHP EnterpriseHortonworksHitachi Data SystemsDeloitteGeneral ElectricFujitsuGoogleFacebookIBM
In addition, this report discusses the key drivers influencing market growth, opportunities, the challenges and the risks faced by key players and the market as a whole. It also analyzes key emerging trends and their impact on present and future development.
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Major Key Points in Table of Content
1 Scope of the Report
2 Executive Summary
3 Global Big Data in Internet of Things by Players
4 Big Data in Internet of Things by Regions
5 Americas
6 APAC
7 Europe
8 Middle East & Africa
9 Market Drivers, Challenges and Trends
10 Global Big Data in Internet of Things Market Forecast
11 Key Players Analysis
12 Research Findings and Conclusion
Continued………
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