Toll Free: 1-888-928-9744

Big Data in the Healthcare & Pharmaceutical Industry: 2017 - 2030 - Opportunities, Challenges, Strategies & Forecasts

Published: Aug 7, 2017 | Pages: 499 | Publisher: SNS Research | Industry: Pharmaceuticals & Healthcare | Report Format: Electronic (PDF)

“Big Data” originally emerged as a term to describe datasets whose size is beyond the ability of traditional databases to capture, store, manage and analyze. However, the scope of the term has significantly expanded over the years. Big Data not only refers to the data itself but also a set of technologies that capture, store, manage and analyze large and variable collections of data, to solve complex problems.

Amid the proliferation of real-time and historical data from sources such as connected devices, web, social media, sensors, log files and transactional applications, Big Data is rapidly gaining traction from a diverse range of vertical sectors. The healthcare and pharmaceutical industry is no exception to this trend, where Big Data has found a host of applications ranging from drug discovery and precision medicine to clinical decision support and population health management.

SNS Research estimates that Big Data investments in the healthcare and pharmaceutical industry will account for nearly $4 Billion in 2017 alone.  Led by a plethora of business opportunities for healthcare providers, insurers, payers, government agencies, pharmaceutical companies and other stakeholders, these investments are further expected to grow at a CAGR of more than 15% over the next three years.

The “Big Data in the Healthcare & Pharmaceutical Industry: 2017 – 2030 – Opportunities, Challenges, Strategies & Forecasts” report presents an in-depth assessment of Big Data in the healthcare and pharmaceutical industry including key market drivers, challenges, investment potential, application areas, use cases, future roadmap, value chain, case studies, vendor profiles and strategies. The report also presents market size forecasts for Big Data hardware, software and professional services investments from 2017 through to 2030. The forecasts are segmented for 8 horizontal submarkets, 5 application areas, 36 use cases, 6 regions and 35 countries.

The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

Topics Covered

The report covers the following topics: 
 - Big Data ecosystem
 - Market drivers and barriers
 - Enabling technologies, standardization and regulatory initiatives
 - Big Data analytics and implementation models
 - Business case, application areas and use cases in the healthcare and pharmaceutical industry
 - 34 case studies of Big Data investments by healthcare providers, insurers, payers, pharmaceutical companies and other stakeholders
 - Future roadmap and value chain
 - Company profiles and strategies of over 240 Big Data vendors
 - Strategic recommendations for Big Data vendors, and healthcare and pharmaceutical industry stakeholders
 - Market analysis and forecasts from 2017 till 2030

Forecast Segmentation

Market forecasts are provided for each of the following submarkets and their subcategories:

Hardware, Software & Professional Services
 - Hardware
 - Software
 - Professional Services

Horizontal Submarkets
 - Storage & Compute Infrastructure
 - Networking Infrastructure
 - Hadoop & Infrastructure Software
 - SQL
 - NoSQL
 - Analytic Platforms & Applications
 - Cloud Platforms
 - Professional Services

Application Areas
 - Pharmaceutical & Medical Products
 - Core Healthcare Operations
 - Healthcare Support, Awareness & Disease Prevention
 - Health Insurance & Payer Services
 - Marketing, Sales & Other Applications

Use Cases
 - Drug Discovery, Design & Development
 - Medical Product Design & Development
 - Clinical Development & Trials
 - Precision Medicine & Genomics
 - Manufacturing & Supply Chain Management
 - Post-Market Surveillance & Pharmacovigilance
 - Medical Product Fault Monitoring
 - Clinical Decision Support
 - Care Coordination & Delivery Management
 - CER (Comparative Effectiveness Research) & Observational Evidence
 - Personalized Healthcare & Targeted Treatments
 - Data-Driven Preventive Care & Health Interventions
 - Surgical Practice & Complex Medical Procedures
 - Pathology, Medical Imaging & Other Medical Tests
 - Proactive & Remote Patient Monitoring
 - Predictive Maintenance of Medical Equipment
 - Pharmacy Services
 - Self-Care & Lifestyle Support
 - Medication Adherence & Management
 - Vaccine Development & Promotion
 - Population Health Management
 - Connected Health Communities & Medical Knowledge Dissemination
 - Epidemiology & Disease Surveillance
 - Health Policy Decision Making
 - Controlling Substance Abuse & Addiction
 - Increasing Awareness & Accessible Healthcare
 - Health Insurance Claims Processing & Management
 - Fraud & Abuse Prevention
 - Proactive Patient Engagement
 - Accountable & Value-Based Care
 - Data-Driven Health Insurance Premiums
 - Marketing & Sales
 - Administrative & Customer Services
 - Finance & Risk Management
 - Healthcare Data Monetization
 - Other Use Cases

Regional Markets
 - Asia Pacific
 - Eastern Europe
 - Latin & Central America
 - Middle East & Africa
 - North America
 - Western Europe

Country Markets
 - Argentina, Australia, Brazil, Canada, China, Czech Republic, Denmark, Finland, France, Germany,  India, Indonesia, Israel, Italy, Japan, Malaysia, Mexico, Netherlands, Norway, Pakistan, Philippines, Poland, Qatar, Russia, Saudi Arabia, Singapore, South Africa, South Korea, Spain, Sweden, Taiwan, Thailand, UAE, UK,  USA

Key Questions Answered 

The report provides answers to the following key questions:
 - How big is the Big Data opportunity in the healthcare and pharmaceutical industry?
 - How is the market evolving by segment and region?
 - What will the market size be in 2020 and at what rate will it grow?
 - What trends, challenges and barriers are influencing its growth?
 - Who are the key Big Data software, hardware and services vendors and what are their strategies?
 - How much are healthcare providers, insurers, payers, pharmaceutical companies and other stakeholders investing in Big Data?
 - What opportunities exist for Big Data analytics in the healthcare and pharmaceutical industry?
 - Which countries, application areas and use cases will see the highest percentage of Big Data investments in the healthcare and pharmaceutical industry?

Key Findings 

The report has the following key findings: 
 - In 2017, Big Data vendors will pocket nearly $4 Billion from hardware, software and professional services revenues in the healthcare and pharmaceutical industry. These investments are further expected to grow at a CAGR of more than 15% over the next three years, eventually accounting for over $5.8 Billion by the end of 2020.
 - Through the use of Big Data technologies, hospitals and other healthcare facilities have been able to achieve cost reductions of more than 10%, improvements in outcomes by as much as 20% for certain conditions, growth in revenue by 30%, and increase in patient access to services by more than 35%.
 - Big Data technologies are playing a pivotal role in accelerating the transition towards accountable and value-based care models, by enabling the continuous collection, consolidation and analysis of clinical and operational data from healthcare facilities and other available data sources.
 - Addressing privacy and security concerns is necessary in order to fully leverage the benefits of Big Data in the healthcare and pharmaceutical industry. Therefore, it is essential for key stakeholders to make significant investments in data encryption and cybersecurity, in addition to adopting defensible de-identification techniques and implementing strict restrictions on data use.

List of Companies Mentioned

•	1010data
•	Absolutdata
•	Accenture
•	ACR (American College of Radiology)
•	Actian Corporation
•	Adaptive Insights
•	Advizor Solutions
•	AeroSpike
•	Aetna
•	AFS Technologies
•	Alation
•	Algorithmia
•	Alluxio
•	Alphabet
•	Alpine Data
•	Alteryx
•	Ambient Clinical Analytics
•	AMD (Advanced Micro Devices)
•	Amino
•	Apixio
•	Arcadia Data
•	Arimo
•	ARM
•	ASF (Apache Software Foundation)
•	ASTM (American Society for Testing and Materials)
•	AstraZeneca
•	AtScale
•	Attivio
•	Attunity
•	Australian Digital Health Agency
•	Automated Insights
•	AWS (Amazon Web Services)
•	Axiomatics
•	Ayasdi
•	Bangkok Hospital Group
•	Basho Technologies
•	Bayer
•	BCG (Boston Consulting Group)
•	Bedrock Data
•	BetterWorks
•	Big Cloud Analytics
•	Big Panda
•	BigML
•	Birst
•	Bitam
•	Blue Medora
•	BlueData Software
•	BlueTalon
•	BMC Software
•	BOARD International
•	Booz Allen Hamilton
•	Boxever
•	CACI International
•	Cambridge Semantics
•	Capgemini
•	Cazena
•	CDC (Centers for Disease Control & Prevention)
•	Centerstone
•	Centrifuge Systems
•	CenturyLink
•	Chartio
•	Cincinnati Children’s Hospital Medical Center
•	Cisco Systems
•	Civis Analytics
•	ClearStory Data
•	Cloudability
•	Cloudera
•	Clustrix
•	CMS (U.S. Centers for Medicare & Medicaid Services)
•	CNIL (Data Protection Regulatory Authority, France)
•	CognitiveScale
•	Collibra
•	Concurrent Computer Corporation
•	Confluent
•	Contexti
•	Continuum Analytics
•	CosmosID
•	Couchbase
•	CrowdFlower
•	CSA (Cloud Security Alliance)
•	CSCC (Cloud Standards Customer Council)
•	CSIRO (Commonwealth Scientific and Industrial Research Organization)
•	Databricks
•	DataGravity
•	Dataiku
•	Datameer
•	DataRobot
•	DataScience
•	DataStax
•	DataTorrent
•	Datawatch Corporation
•	Datos IO
•	DDN (DataDirect Networks)
•	Decisyon
•	Dell Technologies
•	Deloitte
•	Demandbase
•	Denodo Technologies
•	Digital Reasoning Systems
•	Dimensional Insight
•	DMG  (Data Mining Group)
•	Dolphin Enterprise Solutions Corporation
•	Domino Data Lab
•	Domo
•	DriveScale
•	Dundas Data Visualization
•	DXC Technology
•	Eligotech
•	Engineering Group (Engineering Ingegneria Informatica)
•	EnterpriseDB
•	eQ Technologic
•	Ericsson
•	EXASOL
•	Express Scripts
•	Exscientia
•	Facebook
•	Faros Healthcare
•	FDA (U.S. Food and Drug Administration)
•	FICO (Fair Isaac Corporation)
•	Fractal Analytics
•	Fujitsu
•	Fuzzy Logix
•	Gainsight
•	GE (General Electric)
•	Genomics England
•	Ginger.io
•	Glassbeam
•	GNS Healthcare
•	Gold Coast Health
•	GoodData Corporation
•	Google
•	Greenwave Systems
•	GridGain Systems
•	GSK (GlaxoSmithKline)
•	Guavus
•	H2O.ai
•	HDS (Hitachi Data Systems)
•	Hedvig
•	HHS (U.S. Department of Health & Human Services)
•	HL7 (Health Level Seven)
•	HLI (Human Longevity Inc.)
•	Hortonworks
•	HPE (Hewlett Packard Enterprise)
•	Huawei
•	IBM Corporation
•	iDashboards
•	IEEE (Institute of Electrical and Electronics Engineers)
•	IHE (Integrating the Healthcare Enterprise)
•	Illumina
•	IMI (Innovative Medicines Initiative)
•	Impetus Technologies
•	INCITS (InterNational Committee for Information Technology Standards)
•	Incorta
•	INDS (National Institute of Health Data, France)
•	InetSoft Technology Corporation
•	Infer
•	Infor
•	Informatica Corporation
•	Information Builders
•	Infosys
•	Infoworks
•	Insightsoftware.com
•	InsightSquared
•	Intel Corporation
•	Interana
•	InterSystems Corporation
•	ISO (International Organization for Standardization)
•	ITU (International Telecommunications Union)
•	IU Health (Indiana University Health)
•	IURTC (Indiana University Research & Technology Corporation)
•	Jedox
•	Jethro
•	Jinfonet Software
•	Johnson & Johnson
•	Juniper Networks
•	KALEAO
•	KBV/NASHIP (National Association of Statutory Health Insurance Physicians, Germany)
•	Keen IO
•	Kinetica
•	KNIME
•	Kognitio
•	Kyvos Insights
•	Lavastorm
•	Lexalytics
•	Lexmark International
•	Linux Foundation
•	Logi Analytics
•	Longview Solutions
•	Looker Data Sciences
•	LucidWorks
•	Luminoso Technologies
•	Maana
•	Magento Commerce
•	Manthan Software Services
•	MapD Technologies
•	MapR Technologies
•	MariaDB Corporation
•	MarkLogic Corporation
•	Mathworks
•	Mayo Clinic
•	Medtronic
•	MemSQL
•	Merck & Co.
•	Merck KGaA
•	Metric Insights
•	Microsoft Corporation
•	MicroStrategy
•	Ministry of Health, Labor and Welfare, Japan
•	Minitab
•	MolecularMatch
•	MongoDB
•	MSQC (Michigan Surgical Quality Collaborative)
•	Mu Sigma
•	NCCS  (National Cancer Centre Singapore)
•	NCPDP (National Council for Prescription Drug Programs)
•	NEC Corporation
•	NEMA (National Electrical Manufacturers Association)
•	Neo Technology
•	NetApp
•	NHS (National Health Service, United Kingdom)
•	NHS England
•	NHS Scotland
•	Nimbix
•	NIST (U.S. National Institute of Standards and Technology)
•	Nokia
•	Novartis
•	NTT Data Corporation
•	Numerify
•	NuoDB
•	Nutonian
•	NVIDIA Corporation
•	OASIS (Organization for the Advancement of Structured Information Standards)
•	Oblong Industries
•	ODaF (Open Data Foundation)
•	ODCA (Open Data Center Alliance)
•	ODPi (Open Ecosystem of Big Data)
•	OGC (Open Geospatial Consortium)
•	OpenText Corporation
•	Opera Solutions
•	Optimal Plus
•	Optum
•	OptumLabs
•	Oracle Corporation
•	Palantir Technologies
•	Panorama Software
•	Paxata
•	Pentaho Corporation
•	Pepperdata
•	Pfizer
•	Phocas Software
•	Pivotal Software
•	Prognoz
•	Progress Software Corporation
•	Proteus Digital Health
•	PwC (PricewaterhouseCoopers International)
•	Pyramid Analytics
•	Qlik
•	Quantum Corporation
•	Qubole
•	Rackspace
•	Radius Intelligence
•	RapidMiner
•	Recorded Future
•	Red Hat
•	Redis Labs
•	RedPoint Global
•	Reltio
•	Roche
•	Rocket Fuel
•	Royal Philips
•	RStudio
•	Ryft Systems
•	Sailthru
•	Salesforce.com
•	Salient Management Company
•	Samsung Group
•	Sanofi
•	SAP
•	SAS Institute
•	ScaleDB
•	ScaleOut Software
•	SCIO Health Analytics
•	Seagate Technology
•	Seattle Children's Hospital
•	Sickweather
•	Sinequa
•	SingHealth (Singapore Health Services)
•	SiSense
•	SnapLogic
•	Snowflake Computing
•	Software AG
•	Splice Machine
•	Splunk
•	Sproxil
•	Sqrrl
•	Strategy Companion Corporation
•	StreamSets
•	Striim
•	Sumo Logic
•	Supermicro (Super Micro Computer)
•	Syncsort
•	SynerScope
•	Tableau Software
•	Talena
•	Talend
•	Tamr
•	TARGIT
•	TCS (Tata Consultancy Services)
•	Teradata Corporation
•	The Weather Company
•	ThoughtSpot
•	TIBCO Software
•	Tidemark
•	TM Forum
•	Toshiba Corporation
•	TPC (Transaction Processing Performance Council)
•	Trifacta
•	U.S. Department of Energy
•	U.S. Department of Veterans Affairs
•	UN (United Nations)
•	UnitedHealth Group
•	University of Michigan
•	University of Utah Health Care
•	Unravel Data
•	VHA (U.S. Veterans Health Administration)
•	VMware
•	VoltDB
•	W3C (World Wide Web Consortium)
•	Waterline Data
•	Western Digital Corporation
•	WiPro
•	Workday
•	X12
•	Xplenty
•	Yellowfin International
•	Yseop
•	Zendesk
•	Zoomdata
•	Zucchetti
 Table of Contents
		
Chapter 1: Introduction	24
1.1	Executive Summary	24
1.2	Topics Covered	26
1.3	Forecast Segmentation	27
1.4	Key Questions Answered	30
1.5	Key Findings	31
1.6	Methodology	32
1.7	Target Audience	33
1.8	Companies & Organizations Mentioned	34
		
Chapter 2: An Overview of Big Data	38
2.1	What is Big Data?	38
2.2	Key Approaches to Big Data Processing	38
2.2.1	Hadoop	39
2.2.2	NoSQL	41
2.2.3	MPAD (Massively Parallel Analytic Databases)	41
2.2.4	In-Memory Processing	42
2.2.5	Stream Processing Technologies	42
2.2.6	Spark	43
2.2.7	Other Databases & Analytic Technologies	43
2.3	Key Characteristics of Big Data	44
2.3.1	Volume	44
2.3.2	Velocity	44
2.3.3	Variety	44
2.3.4	Value	45
2.4	Market Growth Drivers	46
2.4.1	Awareness of Benefits	46
2.4.2	Maturation of Big Data Platforms	46
2.4.3	Continued Investments by Web Giants, Governments & Enterprises	47
2.4.4	Growth of Data Volume, Velocity & Variety	47
2.4.5	Vendor Commitments & Partnerships	47
2.4.6	Technology Trends Lowering Entry Barriers	48
2.5	Market Barriers	48
2.5.1	Lack of Analytic Specialists	48
2.5.2	Uncertain Big Data Strategies	48
2.5.3	Organizational Resistance to Big Data Adoption	49
2.5.4	Technical Challenges: Scalability & Maintenance	49
2.5.5	Security & Privacy Concerns	49
		
Chapter 3: Big Data Analytics	51
3.1	What are Big Data Analytics?	51
3.2	The Importance of Analytics	51
3.3	Reactive vs. Proactive Analytics	52
3.4	Customer vs. Operational Analytics	53
3.5	Technology & Implementation Approaches	53
3.5.1	Grid Computing	53
3.5.2	In-Database Processing	54
3.5.3	In-Memory Analytics	54
3.5.4	Machine Learning & Data Mining	54
3.5.5	Predictive Analytics	55
3.5.6	NLP (Natural Language Processing)	55
3.5.7	Text Analytics	56
3.5.8	Visual Analytics	57
3.5.9	Graph Analytics	57
3.5.10	Social Media, IT & Telco Network Analytics	58
		
Chapter 4: Business Case & Applications in the Healthcare & Pharmaceutical Industry	59
4.1	Overview & Investment Potential	59
4.2	Industry Specific Market Growth Drivers	60
4.3	Industry Specific Market Barriers	61
4.4	Key Applications	63
4.4.1	Pharmaceutical & Medical Products	63
4.4.1.1	Drug Discovery, Design & Development	63
4.4.1.2	Medical Product Design & Development	64
4.4.1.3	Clinical Development & Trials	64
4.4.1.4	Precision Medicine & Genomics	65
4.4.1.5	Manufacturing & Supply Chain Management	66
4.4.1.6	Post-Market Surveillance & Pharmacovigilance	68
4.4.1.7	Medical Product Fault Monitoring	68
4.4.2	Core Healthcare Operations	69
4.4.2.1	Clinical Decision Support	69
4.4.2.2	Care Coordination & Delivery Management	70
4.4.2.3	CER (Comparative Effectiveness Research) & Observational Evidence	71
4.4.2.4	Personalized Healthcare & Targeted Treatments	71
4.4.2.5	Data-Driven Preventive Care & Health Interventions	72
4.4.2.6	Surgical Practice & Complex Medical Procedures	72
4.4.2.7	Pathology, Medical Imaging & Other Medical Tests	73
4.4.2.8	Proactive & Remote Patient Monitoring	73
4.4.2.9	Predictive Maintenance of Medical Equipment	74
4.4.2.10	Pharmacy Services	74
4.4.3	Healthcare Support, Awareness & Disease Prevention	75
4.4.3.1	Self-Care & Lifestyle Support	75
4.4.3.2	Medication Adherence & Management	76
4.4.3.3	Vaccine Development & Promotion	77
4.4.3.4	Population Health Management	77
4.4.3.5	Connected Health Communities & Medical Knowledge Dissemination	78
4.4.3.6	Epidemiology & Disease Surveillance	79
4.4.3.7	Health Policy Decision Making	79
4.4.3.8	Controlling Substance Abuse & Addiction	80
4.4.3.9	Increasing Awareness & Accessible Healthcare	81
4.4.4	Health Insurance & Payer Services	81
4.4.4.1	Health Insurance Claims Processing & Management	81
4.4.4.2	Fraud & Abuse Prevention	82
4.4.4.3	Proactive Patient Engagement	83
4.4.4.4	Accountable & Value-Based Care	83
4.4.4.5	Data-Driven Health Insurance Premiums	84
4.4.5	Marketing, Sales & Other Applications	84
4.4.5.1	Marketing & Sales	84
4.4.5.2	Administrative & Customer Services	85
4.4.5.3	Finance & Risk Management	86
4.4.5.4	Healthcare Data Monetization	87
4.4.5.5	Other Applications	88
		
Chapter 5: Healthcare & Pharmaceutical Industry Case Studies	89
5.1	Pharmaceutical & Medical Device Companies	89
5.1.1	AstraZeneca: Analytics-Driven Drug Development with Big Data	89
5.1.2	Bayer: Accelerating Clinical Trials with Big Data	91
5.1.3	GSK (GlaxoSmithKline): Increasing Success Rates in Drug Discovery with Big Data	93
5.1.4	Johnson & Johnson: Intelligent Pharmaceutical Marketing with Big Data	95
5.1.5	Medtronic: Facilitating Predictive Care with Big Data	96
5.1.6	Merck & Co.: Optimizing Vaccine Manufacturing with Big Data	97
5.1.7	Merck KGaA: Discovering Drugs Faster with Big Data	98
5.1.8	Novartis: Digitizing Healthcare with Big Data	99
5.1.9	Pfizer: Developing Effective and Targeted Therapies with Big Data	101
5.1.10	Roche: Personalizing Healthcare with Big Data	103
5.1.11	Sanofi: Proactive Diabetes Care with Big Data	104
5.2	Healthcare Providers, Insurers & Payers	106
5.2.1	Aetna: Predicting & Improving Health with Big Data	106
5.2.2	Bangkok Hospital Group: Transforming the Patient Experience with Big Data	108
5.2.3	Gold Coast Health: Reducing Hospital Waiting Times with Big Data	110
5.2.4	IU Health (Indiana University Health): Preventing Hospital-Acquired Infections with Big Data	111
5.2.5	MSQC (Michigan Surgical Quality Collaborative): Surgical Quality Improvement with Big Data	112
5.2.6	NCCS  (National Cancer Centre Singapore): Advancing Cancer Treatment with Big Data	113
5.2.7	NHS Scotland: Improving Outcomes with Big Data	115
5.2.8	Seattle Children's Hospital: Enabling Faster & Accurate Diagnosis with Big Data	116
5.2.9	UnitedHealth Group: Enhancing Patient Care & Value with Big Data	117
5.2.10	VHA (Veterans Health Administration): Streamlining Healthcare Delivery with Big Data	119
5.3	Other Stakeholders	121
5.3.1	Amino: Healthcare Transparency with Big Data	121
5.3.2	CosmosID:  Advancing Microbial Genomics with Big Data	122
5.3.3	Express Scripts: Improving Medication Adherence with Big Data	123
5.3.4	Faros Healthcare: Enhancing Clinical Decision Making with Big Data	125
5.3.5	Genomics England: Developing the World's First Genomics Medicine Service with Big Data	126
5.3.6	Ginger.io: Improving Mental Wellbeing with Big Data	128
5.3.7	Illumina: Enabling Precision Medicine with Big Data	129
5.3.8	INDS (National Institute of Health Data, France): Population Health Management with Big Data	130
5.3.9	MolecularMatch: Advancing the Clinical Utility of Genomics with Big Data	131
5.3.10	Proteus Digital Health: Pioneering Digital Medicine with Big Data	133
5.3.11	Royal Philips: Enhancing Workflows in ICUs (Intensive Care Units) with Big Data	135
5.3.12	Sickweather: Sickness Forecasting & Mapping with Big Data	136
5.3.13	Sproxil: Fighting Counterfeit Drugs with Big Data	138
		
Chapter 6: Future Roadmap & Value Chain	140
6.1	Future Roadmap	140
6.1.1	2017 – 2020: Growing Investments in Real-Time & Predictive Health Analytics	140
6.1.2	2020 – 2025: Large-Scale Adoption of Precision Medicine	141
6.1.3	2025 – 2030: Moving Beyond National-Level Population Health Management	142
6.2	Value Chain	142
6.2.1	Hardware Providers	143
6.2.1.1	Storage & Compute Infrastructure Providers	143
6.2.1.2	Networking Infrastructure Providers	144
6.2.2	Software Providers	144
6.2.2.1	Hadoop & Infrastructure Software Providers	144
6.2.2.2	SQL & NoSQL Providers	145
6.2.2.3	Analytic Platform & Application Software Providers	145
6.2.2.4	Cloud Platform Providers	145
6.2.3	Professional Services Providers	145
6.2.4	End-to-End Solution Providers	146
6.2.5	Healthcare & Pharmaceutical Industry	146
		
Chapter 7: Standardization & Regulatory Initiatives	147
7.1	ASF (Apache Software Foundation)	147
7.1.1	Management of Hadoop	147
7.1.2	Big Data Projects Beyond Hadoop	147
7.2	CSA (Cloud Security Alliance)	150
7.2.1	BDWG (Big Data Working Group)	151
7.3	CSCC (Cloud Standards Customer Council)	151
7.3.1	Big Data Working Group	151
7.4	DMG  (Data Mining Group)	152
7.4.1	PMML (Predictive Model Markup Language) Working Group	152
7.4.2	PFA (Portable Format for Analytics) Working Group	152
7.5	IEEE (Institute of Electrical and Electronics Engineers)	153
7.5.1	Big Data Initiative	153
7.6	INCITS (InterNational Committee for Information Technology Standards)	154
7.6.1	Big Data Technical Committee	154
7.7	ISO (International Organization for Standardization)	155
7.7.1	ISO/IEC JTC 1/SC 32: Data Management and Interchange	155
7.7.2	ISO/IEC JTC 1/SC 38: Cloud Computing and Distributed Platforms	156
7.7.3	ISO/IEC JTC 1/SC 27: IT Security Techniques	156
7.7.4	ISO/IEC JTC 1/WG 9: Big Data	156
7.7.5	Collaborations with Other ISO Work Groups	158
7.8	ITU (International Telecommunications Union)	158
7.8.1	ITU-T Y.3600: Big Data – Cloud Computing Based Requirements and Capabilities	158
7.8.2	Other Deliverables Through SG (Study Group) 13 on Future Networks	159
7.8.3	Other Relevant Work	160
7.9	Linux Foundation	160
7.9.1	ODPi (Open Ecosystem of Big Data)	160
7.10	NIST (National Institute of Standards and Technology)	161
7.10.1	NBD-PWG (NIST Big Data Public Working Group)	161
7.11	OASIS (Organization for the Advancement of Structured Information Standards)	162
7.11.1	Technical Committees	162
7.12	ODaF (Open Data Foundation)	163
7.12.1	Big Data Accessibility	163
7.13	ODCA (Open Data Center Alliance)	163
7.13.1	Work on Big Data	163
7.14	OGC (Open Geospatial Consortium)	164
7.14.1	Big Data DWG (Domain Working Group)	164
7.15	TM Forum	164
7.15.1	Big Data Analytics Strategic Program	164
7.16	TPC (Transaction Processing Performance Council)	165
7.16.1	TPC-BDWG (TPC Big Data Working Group)	165
7.17	W3C (World Wide Web Consortium)	165
7.17.1	Big Data Community Group	165
7.17.2	Open Government Community Group	166
7.18	Other Initiatives Relevant to the Healthcare & Pharmaceutical Industry	166
7.18.1	HIPAA (Health Insurance Portability and Accountability Act of 1996)	166
7.18.2	HITECH (Health Information Technology for Economic and Clinical Health) Act	167
7.18.3	European Union's GDPR (General Data Protection Regulation)	168
7.18.4	Australian Digital Health Agency	168
7.18.5	United Kingdom's ITK (Interoperability Toolkit)	169
7.18.6	Japan's SS-MIX (Standard Structured Medical Information eXchange)	169
7.18.7	Germany's xDT	169
7.18.8	France's DMP (Dossier Médical Personnel)	170
7.18.9	HL7 (Health Level Seven) Specifications	170
7.18.10	IHE (Integrating the Healthcare Enterprise)	171
7.18.11	NCPDP (National Council for Prescription Drug Programs)	172
7.18.12	DICOM (Digital Imaging and Communications in Medicine)	173
7.18.13	eHealth Exchange	173
7.18.14	EDIFACT (Electronic Data Interchange For Administration, Commerce, and Transport)	173
7.18.15	X12 & Others	173
		
Chapter 8: Market Analysis & Forecasts	175
8.1	Global Outlook for Big Data in the Healthcare & Pharmaceutical Industry	175
8.2	Hardware, Software & Professional Services Segmentation	176
8.3	Horizontal Submarket Segmentation	177
8.4	Hardware Submarkets	177
8.4.1	Storage and Compute Infrastructure	177
8.4.2	Networking Infrastructure	178
8.5	Software Submarkets	178
8.5.1	Hadoop & Infrastructure Software	178
8.5.2	SQL	179
8.5.3	NoSQL	179
8.5.4	Analytic Platforms & Applications	180
8.5.5	Cloud Platforms	180
8.6	Professional Services Submarket	181
8.6.1	Professional Services	181
8.7	Application Area Segmentation	182
8.7.1	Pharmaceutical & Medical Products	182
8.7.2	Core Healthcare Operations	183
8.7.3	Healthcare Support, Awareness & Disease Prevention	183
8.7.4	Health Insurance & Payer Services	184
8.7.5	Marketing, Sales & Other Applications	184
8.8	Use Case Segmentation	185
8.9	Pharmaceutical & Medical Products	187
8.9.1	Drug Discovery, Design & Development	187
8.9.2	Medical Product Design & Development	187
8.9.3	Clinical Development & Trials	188
8.9.4	Precision Medicine & Genomics	188
8.9.5	Manufacturing & Supply Chain Management	189
8.9.6	Post-Market Surveillance & Pharmacovigilance	189
8.9.7	Medical Product Fault Monitoring	190
8.10	Core Healthcare Operations	190
8.10.1	Clinical Decision Support	190
8.10.2	Care Coordination & Delivery Management	191
8.10.3	CER (Comparative Effectiveness Research) & Observational Evidence	191
8.10.4	Personalized Healthcare & Targeted Treatments	192
8.10.5	Data-Driven Preventive Care & Health Interventions	192
8.10.6	Surgical Practice & Complex Medical Procedures	193
8.10.7	Pathology, Medical Imaging & Other Medical Tests	193
8.10.8	Proactive & Remote Patient Monitoring	194
8.10.9	Predictive Maintenance of Medical Equipment	194
8.10.10	Pharmacy Services	195
8.11	Healthcare Support, Awareness & Disease Prevention	195
8.11.1	Self-Care & Lifestyle Support	195
8.11.2	Medication Adherence & Management	196
8.11.3	Vaccine Development & Promotion	196
8.11.4	Population Health Management	197
8.11.5	Connected Health Communities & Medical Knowledge Dissemination	197
8.11.6	Epidemiology & Disease Surveillance	198
8.11.7	Health Policy Decision Making	198
8.11.8	Controlling Substance Abuse & Addiction	199
8.11.9	Increasing Awareness & Accessible Healthcare	199
8.12	Health Insurance & Payer Services	200
8.12.1	Health Insurance Claims Processing & Management	200
8.12.2	Fraud & Abuse Prevention	200
8.12.3	Proactive Patient Engagement	201
8.12.4	Accountable & Value-Based Care	201
8.12.5	Data-Driven Health Insurance Premiums	202
8.13	Marketing, Sales & Other Application Use Cases	202
8.13.1	Marketing & Sales	202
8.13.2	Administrative & Customer Services	203
8.13.3	Finance & Risk Management	203
8.13.4	Healthcare Data Monetization	204
8.13.5	Other Use Cases	204
8.14	Regional Outlook	205
8.15	Asia Pacific	205
8.15.1	Country Level Segmentation	206
8.15.2	Australia	206
8.15.3	China	207
8.15.4	India	207
8.15.5	Indonesia	208
8.15.6	Japan	208
8.15.7	Malaysia	209
8.15.8	Pakistan	209
8.15.9	Philippines	210
8.15.10	Singapore	210
8.15.11	South Korea	211
8.15.12	Taiwan	211
8.15.13	Thailand	212
8.15.14	Rest of Asia Pacific	212
8.16	Eastern Europe	213
8.16.1	Country Level Segmentation	213
8.16.2	Czech Republic	214
8.16.3	Poland	214
8.16.4	Russia	215
8.16.5	Rest of Eastern Europe	215
8.17	Latin & Central America	216
8.17.1	Country Level Segmentation	216
8.17.2	Argentina	217
8.17.3	Brazil	217
8.17.4	Mexico	218
8.17.5	Rest of Latin & Central America	218
8.18	Middle East & Africa	219
8.18.1	Country Level Segmentation	219
8.18.2	Israel	220
8.18.3	Qatar	220
8.18.4	Saudi Arabia	221
8.18.5	South Africa	221
8.18.6	UAE	222
8.18.7	Rest of the Middle East & Africa	222
8.19	North America	223
8.19.1	Country Level Segmentation	223
8.19.2	Canada	224
8.19.3	USA	224
8.20	Western Europe	225
8.20.1	Country Level Segmentation	225
8.20.2	Denmark	226
8.20.3	Finland	226
8.20.4	France	227
8.20.5	Germany	227
8.20.6	Italy	228
8.20.7	Netherlands	228
8.20.8	Norway	229
8.20.9	Spain	229
8.20.10	Sweden	230
8.20.11	UK	230
8.20.12	Rest of Western Europe	231
		
Chapter 9: Vendor Landscape	232
9.1	1010data	232
9.2	Absolutdata	233
9.3	Accenture	234
9.4	Actian Corporation	235
9.5	Adaptive Insights	236
9.6	Advizor Solutions	237
9.7	AeroSpike	238
9.8	AFS Technologies	239
9.9	Alation	240
9.10	Algorithmia	241
9.11	Alluxio	242
9.12	Alpine Data	243
9.13	Alteryx	244
9.14	AMD (Advanced Micro Devices)	245
9.15	Apixio	246
9.16	Arcadia Data	247
9.17	Arimo	248
9.18	ARM	249
9.19	AtScale	250
9.20	Attivio	251
9.21	Attunity	252
9.22	Automated Insights	253
9.23	AWS (Amazon Web Services)	254
9.24	Axiomatics	255
9.25	Ayasdi	256
9.26	Basho Technologies	257
9.27	BCG (Boston Consulting Group)	258
9.28	Bedrock Data	259
9.29	BetterWorks	260
9.30	Big Cloud Analytics	261
9.31	BigML	262
9.32	Big Panda	263
9.33	Birst	264
9.34	Bitam	265
9.35	Blue Medora	266
9.36	BlueData Software	267
9.37	BlueTalon	268
9.38	BMC Software	269
9.39	BOARD International	270
9.40	Booz Allen Hamilton	271
9.41	Boxever	272
9.42	CACI International	273
9.43	Cambridge Semantics	274
9.44	Capgemini	275
9.45	Cazena	276
9.46	Centrifuge Systems	277
9.47	CenturyLink	278
9.48	Chartio	279
9.49	Cisco Systems	280
9.50	Civis Analytics	281
9.51	ClearStory Data	282
9.52	Cloudability	283
9.53	Cloudera	284
9.54	Clustrix	285
9.55	CognitiveScale	286
9.56	Collibra	287
9.57	Concurrent Computer Corporation	288
9.58	Confluent	289
9.59	Contexti	290
9.60	Continuum Analytics	291
9.61	Couchbase	292
9.62	CrowdFlower	293
9.63	Databricks	294
9.64	DataGravity	295
9.65	Dataiku	296
9.66	Datameer	297
9.67	DataRobot	298
9.68	DataScience	299
9.69	DataStax	300
9.70	DataTorrent	301
9.71	Datawatch Corporation	302
9.72	Datos IO	303
9.73	DDN (DataDirect Networks)	304
9.74	Decisyon	305
9.75	Dell Technologies	306
9.76	Deloitte	307
9.77	Demandbase	308
9.78	Denodo Technologies	309
9.79	Digital Reasoning Systems	310
9.80	Dimensional Insight	311
9.81	Dolphin Enterprise Solutions Corporation	312
9.82	Domino Data Lab	313
9.83	Domo	314
9.84	DriveScale	315
9.85	Dundas Data Visualization	316
9.86	DXC Technology	317
9.87	Eligotech	318
9.88	Engineering Group (Engineering Ingegneria Informatica)	319
9.89	EnterpriseDB	320
9.90	eQ Technologic	321
9.91	Ericsson	322
9.92	EXASOL	323
9.93	Facebook	324
9.94	FICO (Fair Isaac Corporation)	325
9.95	Fractal Analytics	326
9.96	Fujitsu	327
9.97	Fuzzy Logix	329
9.98	Gainsight	330
9.99	GE (General Electric)	331
9.100	Glassbeam	332
9.101	GoodData Corporation	333
9.102	Google	334
9.103	Greenwave Systems	335
9.104	GridGain Systems	336
9.105	Guavus	337
9.106	H2O.ai	338
9.107	HDS (Hitachi Data Systems)	339
9.108	Hedvig	340
9.109	Hortonworks	341
9.110	HPE (Hewlett Packard Enterprise)	342
9.111	Huawei	344
9.112	IBM Corporation	345
9.113	iDashboards	347
9.114	Impetus Technologies	348
9.115	Incorta	349
9.116	InetSoft Technology Corporation	350
9.117	Infer	351
9.118	Infor	352
9.119	Informatica Corporation	353
9.120	Information Builders	354
9.121	Infosys	355
9.122	Infoworks	356
9.123	Insightsoftware.com	357
9.124	InsightSquared	358
9.125	Intel Corporation	359
9.126	Interana	360
9.127	InterSystems Corporation	361
9.128	Jedox	362
9.129	Jethro	363
9.130	Jinfonet Software	364
9.131	Juniper Networks	365
9.132	KALEAO	366
9.133	Keen IO	367
9.134	Kinetica	368
9.135	KNIME	369
9.136	Kognitio	370
9.137	Kyvos Insights	371
9.138	Lavastorm	372
9.139	Lexalytics	373
9.140	Lexmark International	374
9.141	Logi Analytics	375
9.142	Longview Solutions	376
9.143	Looker Data Sciences	377
9.144	LucidWorks	378
9.145	Luminoso Technologies	379
9.146	Maana	380
9.147	Magento Commerce	381
9.148	Manthan Software Services	382
9.149	MapD Technologies	383
9.150	MapR Technologies	384
9.151	MariaDB Corporation	385
9.152	MarkLogic Corporation	386
9.153	Mathworks	387
9.154	MemSQL	388
9.155	Metric Insights	389
9.156	Microsoft Corporation	390
9.157	MicroStrategy	391
9.158	Minitab	392
9.159	MongoDB	393
9.160	Mu Sigma	394
9.161	NEC Corporation	395
9.162	Neo Technology	396
9.163	NetApp	397
9.164	Nimbix	398
9.165	Nokia	399
9.166	NTT Data Corporation	400
9.167	Numerify	401
9.168	NuoDB	402
9.169	Nutonian	403
9.170	NVIDIA Corporation	404
9.171	Oblong Industries	405
9.172	OpenText Corporation	406
9.173	Opera Solutions	408
9.174	Optimal Plus	409
9.175	Oracle Corporation	410
9.176	Palantir Technologies	412
9.177	Panorama Software	413
9.178	Paxata	414
9.179	Pentaho Corporation	415
9.180	Pepperdata	416
9.181	Phocas Software	417
9.182	Pivotal Software	418
9.183	Prognoz	420
9.184	Progress Software Corporation	421
9.185	PwC (PricewaterhouseCoopers International)	422
9.186	Pyramid Analytics	423
9.187	Qlik	424
9.188	Quantum Corporation	425
9.189	Qubole	426
9.190	Rackspace	427
9.191	Radius Intelligence	428
9.192	RapidMiner	429
9.193	Recorded Future	430
9.194	Red Hat	431
9.195	Redis Labs	432
9.196	RedPoint Global	433
9.197	Reltio	434
9.198	Rocket Fuel	435
9.199	RStudio	436
9.200	Ryft Systems	437
9.201	Sailthru	438
9.202	Salesforce.com	439
9.203	Salient Management Company	440
9.204	Samsung Group	441
9.205	SAP	442
9.206	SAS Institute	443
9.207	ScaleDB	444
9.208	ScaleOut Software	445
9.209	SCIO Health Analytics	446
9.210	Seagate Technology	447
9.211	Sinequa	448
9.212	SiSense	449
9.213	SnapLogic	450
9.214	Snowflake Computing	451
9.215	Software AG	452
9.216	Splice Machine	453
9.217	Splunk	454
9.218	Sqrrl	455
9.219	Strategy Companion Corporation	456
9.220	StreamSets	457
9.221	Striim	458
9.222	Sumo Logic	459
9.223	Supermicro (Super Micro Computer)	460
9.224	Syncsort	461
9.225	SynerScope	462
9.226	Tableau Software	463
9.227	Talena	464
9.228	Talend	465
9.229	Tamr	466
9.230	TARGIT	467
9.231	TCS (Tata Consultancy Services)	468
9.232	Teradata Corporation	469
9.233	ThoughtSpot	471
9.234	TIBCO Software	472
9.235	Tidemark	473
9.236	Toshiba Corporation	474
9.237	Trifacta	475
9.238	Unravel Data	476
9.239	VMware	477
9.240	VoltDB	478
9.241	Waterline Data	479
9.242	Western Digital Corporation	480
9.243	WiPro	481
9.244	Workday	482
9.245	Xplenty	483
9.246	Yellowfin International	484
9.247	Yseop	485
9.248	Zendesk	486
9.249	Zoomdata	487
9.250	Zucchetti	488
		
Chapter 10: Conclusion & Strategic Recommendations	489
10.1	Why is the Market Poised to Grow?	489
10.2	Geographic Outlook: Which Countries Offer the Highest Growth Potential?	489
10.3	Partnerships & M&A Activity: Highlighting the Importance of Big Data	490
10.4	Improving Outcomes, Achieving Operational Efficiency and Reducing Costs	491
10.5	Assessing the Impact of Connected Health Solutions	491
10.6	Accelerating the Transition Towards Value-Based Care	492
10.7	The Value of Big Data in Precision Medicine	493
10.8	Addressing Privacy & Security Concerns	494
10.9	The Role of Data Protection Legislation	494
10.10	Blockchain: Enabling Secure, Efficient and Interoperable Data Sharing	495
10.11	Recommendations	496
10.11.1	Big Data Hardware, Software & Professional Services Providers	496
10.11.2	Healthcare & Pharmaceutical Industry Stakeholders	497
List of Figures	
	
	Figure 1: Hadoop Architecture	42
	Figure 2: Reactive vs. Proactive Analytics	55
	Figure 3: Distribution of Big Data Investments in the Healthcare & Pharmaceutical Industry, by Application Area: 2016 (%)	62
	Figure 4: Key Characteristics of Genomics and Three Major Sources of Big Data	69
	Figure 5: Bayer's Vision of Big Data in Medicine	95
	Figure 6: Sickweather's Sickness Forecasting & Mapping Service	139
	Figure 7: Counterfeit Drug Identification with Big Data & Mobile Technology	141
	Figure 8: Big Data Roadmap in the Healthcare & Pharmaceutical Industry	143
	Figure 9: Big Data Value Chain in the Healthcare & Pharmaceutical Industry	146
	Figure 10: Key Aspects of Big Data Standardization	156
	Figure 11: Global Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	178
	Figure 12: Global Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Hardware, Software & Professional Services: 2017 - 2030 ($ Million)	179
	Figure 13: Global Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Submarket: 2017 - 2030 ($ Million)	180
	Figure 14: Global Big Data Storage and Compute Infrastructure Submarket Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	180
	Figure 15: Global Big Data Networking Infrastructure Submarket Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	181
	Figure 16: Global Big Data Hadoop & Infrastructure Software Submarket Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	181
	Figure 17: Global Big Data SQL Submarket Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	182
	Figure 18: Global Big Data NoSQL Submarket Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	182
	Figure 19: Global Big Data Analytic Platforms & Applications Submarket Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	183
	Figure 20: Global Big Data Cloud Platforms Submarket Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	183
	Figure 21: Global Big Data Professional Services Submarket Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	184
	Figure 22: Global Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Application Area: 2017 - 2030 ($ Million)	185
	Figure 23: Global Big Data Revenue in Pharmaceutical & Medical Products: 2017 - 2030 ($ Million)	185
	Figure 24: Global Big Data Revenue in Core Healthcare Operations: 2017 - 2030 ($ Million)	186
	Figure 25: Global Big Data Revenue in Healthcare Support, Awareness & Disease Prevention: 2017 - 2030 ($ Million)	186
	Figure 26: Global Big Data Revenue in Health Insurance & Payer Services: 2017 - 2030 ($ Million)	187
	Figure 27: Global Big Data Revenue in Healthcare/Pharmaceutical Marketing, Sales & Other Applications: 2017 - 2030 ($ Million)	187
	Figure 28: Global Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Use Case: 2017 - 2030 ($ Million)	189
	Figure 29: Global Big Data Revenue in Drug Discovery, Design & Development: 2017 - 2030 ($ Million)	190
	Figure 30: Global Big Data Revenue in Medical Product Design & Development: 2017 - 2030 ($ Million)	190
	Figure 31: Global Big Data Revenue in Clinical Development & Trials: 2017 - 2030 ($ Million)	191
	Figure 32: Global Big Data Revenue in Precision Medicine & Genomics: 2017 - 2030 ($ Million)	191
	Figure 33: Global Big Data Revenue in Pharmaceutical/Medical Manufacturing & Supply Chain Management: 2017 - 2030 ($ Million)	192
	Figure 34: Global Big Data Revenue in Post-Market Surveillance & Pharmacovigilance: 2017 - 2030 ($ Million)	192
	Figure 35: Global Big Data Revenue in Medical Product Fault Monitoring: 2017 - 2030 ($ Million)	193
	Figure 36: Global Big Data Revenue in Clinical Decision Support: 2017 - 2030 ($ Million)	193
	Figure 37: Global Big Data Revenue in Care Coordination & Delivery Management: 2017 - 2030 ($ Million)	194
	Figure 38: Global Big Data Revenue in CER (Comparative Effectiveness Research) & Observational Evidence: 2017 - 2030 ($ Million)	194
	Figure 39: Global Big Data Revenue in Personalized Healthcare & Targeted Treatments: 2017 - 2030 ($ Million)	195
	Figure 40: Global Big Data Revenue in Data-Driven Preventive Care & Health Interventions: 2017 - 2030 ($ Million)	195
	Figure 41: Global Big Data Revenue in Surgical Practice & Complex Medical Procedures: 2017 - 2030 ($ Million)	196
	Figure 42: Global Big Data Revenue in Pathology, Medical Imaging & Other Medical Tests: 2017 - 2030 ($ Million)	196
	Figure 43: Global Big Data Revenue in Proactive & Remote Patient Monitoring: 2017 - 2030 ($ Million)	197
	Figure 44: Global Big Data Revenue in Predictive Maintenance of Medical Equipment: 2017 - 2030 ($ Million)	197
	Figure 45: Global Big Data Revenue in Pharmacy Services: 2017 - 2030 ($ Million)	198
	Figure 46: Global Big Data Revenue in Self-Care & Lifestyle Support: 2017 - 2030 ($ Million)	198
	Figure 47: Global Big Data Revenue in Medication Adherence & Management: 2017 - 2030 ($ Million)	199
	Figure 48: Global Big Data Revenue in Vaccine Development & Promotion: 2017 - 2030 ($ Million)	199
	Figure 49: Global Big Data Revenue in Population Health Management: 2017 - 2030 ($ Million)	200
	Figure 50: Global Big Data Revenue in Connected Health Communities & Medical Knowledge Dissemination: 2017 - 2030 ($ Million)	200
	Figure 51: Global Big Data Revenue in Epidemiology & Disease Surveillance: 2017 - 2030 ($ Million)	201
	Figure 52: Global Big Data Revenue in Health Policy Decision Making: 2017 - 2030 ($ Million)	201
	Figure 53: Global Big Data Revenue in Controlling Substance Abuse & Addiction: 2017 - 2030 ($ Million)	202
	Figure 54: Global Big Data Revenue in Increasing Awareness & Accessible Healthcare: 2017 - 2030 ($ Million)	202
	Figure 55: Global Big Data Revenue in Health Insurance Claims Processing & Management: 2017 - 2030 ($ Million)	203
	Figure 56: Global Big Data Revenue in Fraud & Abuse Prevention: 2017 - 2030 ($ Million)	203
	Figure 57: Global Big Data Revenue in Proactive Patient Engagement: 2017 - 2030 ($ Million)	204
	Figure 58: Global Big Data Revenue in Accountable & Value-Based Care: 2017 - 2030 ($ Million)	204
	Figure 59: Global Big Data Revenue in Data-Driven Health Insurance Premiums: 2017 - 2030 ($ Million)	205
	Figure 60: Global Big Data Revenue in Healthcare/Pharmaceutical Marketing & Sales: 2017 - 2030 ($ Million)	205
	Figure 61: Global Big Data Revenue in Healthcare/Pharmaceutical Administrative & Customer Services: 2017 - 2030 ($ Million)	206
	Figure 62: Global Big Data Revenue in Healthcare/Pharmaceutical Finance & Risk Management: 2017 - 2030 ($ Million)	206
	Figure 63: Global Big Data Revenue in Healthcare Data Monetization: 2017 - 2030 ($ Million)	207
	Figure 64: Global Big Data Revenue in Other Healthcare & Pharmaceutical Industry Use Cases: 2017 - 2030 ($ Million)	207
	Figure 65: Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Region: 2017 - 2030 ($ Million)	208
	Figure 66: Asia Pacific Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	208
	Figure 67: Asia Pacific Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Country: 2017 - 2030 ($ Million)	209
	Figure 68: Australia Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	209
	Figure 69: China Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	210
	Figure 70: India Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	210
	Figure 71: Indonesia Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	211
	Figure 72: Japan Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	211
	Figure 73: Malaysia Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	212
	Figure 74: Pakistan Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	212
	Figure 75: Philippines Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	213
	Figure 76: Singapore Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	213
	Figure 77: South Korea Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	214
	Figure 78: Taiwan Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	214
	Figure 79: Thailand Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	215
	Figure 80: Rest of Asia Pacific Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	215
	Figure 81: Eastern Europe Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	216
	Figure 82: Eastern Europe Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Country: 2017 - 2030 ($ Million)	216
	Figure 83: Czech Republic Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	217
	Figure 84: Poland Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	217
	Figure 85: Russia Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	218
	Figure 86: Rest of Eastern Europe Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	218
	Figure 87: Latin & Central America Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	219
	Figure 88: Latin & Central America Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Country: 2017 - 2030 ($ Million)	219
	Figure 89: Argentina Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	220
	Figure 90: Brazil Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	220
	Figure 91: Mexico Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	221
	Figure 92: Rest of Latin & Central America Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	221
	Figure 93: Middle East & Africa Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	222
	Figure 94: Middle East & Africa Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Country: 2017 - 2030 ($ Million)	222
	Figure 95: Israel Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	223
	Figure 96: Qatar Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	223
	Figure 97: Saudi Arabia Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	224
	Figure 98: South Africa Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	224
	Figure 99: UAE Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	225
	Figure 100: Rest of the Middle East & Africa Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	225
	Figure 101: North America Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	226
	Figure 102: North America Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Country: 2017 - 2030 ($ Million)	226
	Figure 103: Canada Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	227
	Figure 104: USA Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	227
	Figure 105: Western Europe Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	228
	Figure 106: Western Europe Big Data Revenue in the Healthcare & Pharmaceutical Industry, by Country: 2017 - 2030 ($ Million)	228
	Figure 107: Denmark Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	229
	Figure 108: Finland Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	229
	Figure 109: France Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	230
	Figure 110: Germany Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	230
	Figure 111: Italy Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	231
	Figure 112: Netherlands Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	231
	Figure 113: Norway Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	232
	Figure 114: Spain Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	232
	Figure 115: Sweden Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	233
	Figure 116: UK Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	233
	Figure 117: Rest of Western Europe Big Data Revenue in the Healthcare & Pharmaceutical Industry: 2017 - 2030 ($ Million)	234 



To request a free sample copy of this report, please complete the form below.

This website is secure and your personal details are safe. Privacy policy

Global non halogenated flame retardants market size is anticipated to be valued at USD 2.54 billion by 2020, as per a new research report by Radiant Insights, Inc. Increasing safety materials demand owing to low heat & smoke emission properties in c

Read More...

Global alpha olefins market size is likely to be valued at USD 10.7 billion by 2020; as per a new research report by Radiant Insights, Inc. Increasing polyethylene demand for use in plastic production is anticipated to drive market growth. Growing ap

Read More...

Global glycerol market size is likely to exceed USD 3 billion by 2022, as per a new research report by Radiant Insights, Inc. Regulatory push for promoting bio-diesel production is expected to boost glycerol demand over the forecast period, with expe

Read More...

Global data center UPS market size is estimated to reach USD 5.7 billion by 2020, as per a new research report by Radiant Insights, Inc. Declining tolerance levels pertaining to data loss along with amplifying acceptance of cloud computing is likely

Read More...

Global automotive relay market is anticipated to reach USD 12 billion by 2020, as per a new research report by Radiant Insights, Inc. Rising need for high-frequency signals in automotive industry is expected to drive demand. These relays enhance driv

Read More...

To learn more about this report, request a free sample copy

Choose License Type
Single User - US $2500
Multi User - US $3500
Why Choose Us

24/5 Research support

Get your queries resolved from an industry expert. Request for a free product review before report purchase.

Phone: 1-415-349-0054

Toll Free: 1-888-928-9744

Email: [email protected]

Custom research service

Speak to the report author to design an exclusive study to serve your research needs.

Quality assurance

A testimonial for service excellence represented in the form of BBB "A" Accreditation.

Information security

Your personal and confidential information is safe and secure.

verify