Global Big Data Markets in Internet of Things, 2019-2024 - Need for New Protocols, Platforms, Streaming and Parsing, Software and Analytical Tools

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Sep 10, 2019, 07:15 ET

DUBLIN, Sept. 10, 2019 /PRNewswire/ -- The "Big Data in Internet of Things: IoT Data Management, Analytics, and Decision Making 2019-2024" report has been added to ResearchAndMarkets.com's offering.

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 2019 through 2024.

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 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 than conventional IoT and thus will requires 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 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 begins to take advantage of new business opportunities such as syndicating their own data.

Summary and Conclusions

Emerging Opportunity Areas within Big Data in IoT

IoT Data Management and Analytics Marketplace
Decisions as a Service

Evolution of Structured and Unstructured Data Exchange

Phase One: Limited Data Exchange
Phase Two: Selective Data Exchange between Industries
Phase Three: Expanded Data Exchange across Industries and Between Competitors

Report Benefits:

Forecasts (global, regional, and by industry) to 2024
Understand the role and importance of Big Data in IoT
Identify key market issues and drivers for Big Data in IoT
Identify leading companies for Big Data and Analytics in IoT
Understand the emerging vendor ecosystem for Big Data in IoT
Identify areas for infrastructure, platform, and software investment

Key Topics Covered:

1 Executive Summary

2 Big Data in Internet of Things
2.1 Big Data Framework for IoT
2.2 Need for New Protocols, Platforms, Streaming and Parsing, Software and Analytical Tools
2.2.1 Big Data in IoT will need Unified Logging Layer
2.2.2 Big Data in IoT Data Formats
2.2.3 Big Data in IoT Protocols
2.2.4 Big Data in IoT Protocols for Network Interoperability
2.2.5 Big Data in IoT Data Processing Scalability
2.3 Big Data in IoT Challenges
2.3.2 Data Security and Personal Information Privacy Challenges

3 Big Data in IoT Business Trends and Predictions
3.1 Large Companies Partnerships and M&A
3.2 Big Data as a Service for IoT Becomes Mainstream
3.3 M2M Analytics and Cloud Services will be Early Beneficiaries
3.4 Cybersecurity for Big Data Analytics in IoT
3.5 Flexible and Scalable Revenue Models for Big Data Services
3.6 Big Data Operational Savings and New Business Models

4 Big Data in IoT Vendor Ecosystem
4.1 Cloud based Analytics Platforms for IoT
4.2 Cloud-based Data Storage Service and Management Toolsets
4.3 Big Data Processing for Massive Data Analysis
4.4 Compute, Store, and Analyze Data at the Edge of Networks
4.5 Predictive Platforms and Solutions
4.6 Cloud based Analytics Systems for IoT
4.7 Database System Upgrades and Evolution
4.8 Analytics Platform Upgrades and Evolution
4.9 Real Time DDS and Comprehensive Messaging Platforms

5 Big Data in IoT Market Analysis and Forecasts
5.1 Driving Factors for Big Data in IoT
5.1.1 Consumer IoT
5.1.2 Industrial IoT
5.1.3 Enterprise IoT
5.1.4 Government IoT
5.2 Overall Global Market for Big Data in IoT 2019 - 2025
5.3 Global Big Data Solutions in IoT Market 2019 - 2025
5.4 Global Big Data in IoT Hardware, Software, and Services 2019 - 2025
5.5 Global Big Data in IoT Products and Services 2019 - 2025
5.6 Big Data in IoT by Industry 2019 - 2025

6 Key Companies

1010Data (Advance Communication Corp.)
Accenture
Actian Corporation
AdvancedMD
Alation
Allscripts Healthcare Solutions
Alpine Data Labs
Alteryx
Amazon
Anova Data
Apache Software Foundation
Apple Inc.
APTEAN (Formerly CDC Software)
Athena Health Inc.
Attunity
Booz Allen Hamilton
Bosch Software Innovations: Bosch IoT Suite
BGI
Big Panda
Bina Technologies Inc.
Capgemini
Cerner Corporation
Cisco Systems
CLC Bio
Cloudera
Cogito Ltd.
Compuverde
CRAY Inc.
Computer Science Corporation (CSC)
Crux Informatics
Ctrl Shift
Cvidya
Cybatar
DataDirect Network
Data Inc.
Databricks
Dataiku
Datameer
Data Stax
Definiens
Dell EMC
Deloitte
Domo
eClinicalWorks
Epic Systems Corporation
Facebook
Fluentd
Flytxt
Fujitsu
Genalice
General Electric
GenomOncology
GoodData Corporation
Google
Greenplum
Grid Gain Systems
Groundhog Technologies
Guavus
Hack/reduce
HPCC Systems
HP Enterprise
Hitachi Data Systems
Hortonworks
IBM
Illumina Inc
Imply Corporation
Informatica
Inter Systems Corporation
Intel
IVD Industry Connectivity Consortium-IICC
Jasper (Cisco Jasper)
Juniper Networks
Knome,Inc.
Leica Biosystems (Danaher)
Longview
MapR
Marklogic
Mayo Medical Laboratories
McKesson Corporation
Medical Information Technology Inc. (MEDITECH)
Medio
Medopad
Microsoft
Microstrategy
MongoDB (Formerly 10Gen)
MU Sigma
N-of-One
Netapp
NTT Data
Open Text (Actuate Corporation)
Opera Solutions
Oracle
Palantir Technologies Inc.
Pathway Genomics Corporation
Perkin Elmer
Pentaho (Hitachi)
Platfora
Qlik Tech
Quality Systems Inc (QSI)
Quantum
Quertle
Quest Diagnostics Inc.
Rackspace
Red Hat
Revolution Analytics
Roche Diagnostics
Rocket Fuel Inc.
Salesforce
SAP
SAS Institute
Selventa Inc.
Sense Networks
Shanghai Data Exchange
Sisense
Social Cops
Software AG/Terracotta
Sojern
Splice Machine
Splunk
Sqrrl
Sumo Logic
Sunquest Information Systems
Supermicro
Tableau Software
Tableau
Tata Consultancy Services
Teradata
ThetaRay
Thoughtworks
Think Big Analytics
TIBCO
Tube Mogul
Verint Systems
VolMetrix
VMware (Part of EMC)
Wipro
Workday (Platfora)
WuXi NextCode Genomics
Zoomdata

For more information about this report visit https://www.researchandmarkets.com/r/5fnaft

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