Site icon

What are the Long-Term Changes We are Likely to See in the Global Big Data in the Healthcare & Pharmaceutical Market?

Prince

“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.

Download PDF Brochure for Latest Research Study: https://www.researchmoz.us/enquiry.php?type=S&repid=1293483

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.

The report covers the following topics:

Forecast Segmentation

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

Hardware, Software & Professional Services

Horizontal Submarkets

Application Areas

Make An Enquiry for Discount Before Buying The Report: https://www.researchmoz.us/enquiry.php?type=D&repid=1293483

Use Cases

Regional Markets

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:

Key Findings

The report has the following key findings:

List of Companies Mentioned

Inquire More About This Report: https://www.researchmoz.us/enquiry.php?type=E&repid=1293483

Table of Contents

1 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

2 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

3 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

Continue..

For More Information Kindly Contact: 
ResearchMoz
Mr. Rohit Bhisey,
Tel: +1-518-621-2074
USA-Canada Toll Free: 866-997-4948
Email: sales@researchmoz.us
Follow us on LinkedIn @ http://bit.ly/1TBmnVG
Media Release: https://www.researchmoz.us/pressrelease
Follow me on : http://marketresearchlatestreports.blogspot.com/

Exit mobile version