The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.
Latest report," Big Data: Embracing Data to Transform Healthcare and Pharma Commercial Strategy - Featuring Expert Panel Views from Industry Survey 2016" provides a comprehensive analysis of the Big Data landscape. GBI Research conducted an extensive industry survey of 73 experts from the pharmaceutical and healthcare industries - including both organizations that already utilize Big Data and those that do not.
Our survey gathered experience and opinion on the use of Big Data, and insights on key trends for the present and future use of the technology within healthcare.
The findings from the survey and results from secondary research efforts have been amalgamated with GBI’s own analytical views to provide an assessment that is comprehensive in outlook.
Big Data refers to any data set that is too large to store, process or analyze using traditional database software and hardware. It can have a significant impact on all aspects of the pharmaceutical and healthcare sector, and companies are making large investments to leverage the technology more effectively.
Big Data has been a buzzword for many years, but it is no longer merely an abstract concept that could provide future benefits, as it is already providing competitive advantages for a variety of organizations. As such, companies that ignore its potential may fall behind their peers in our increasingly data-intensive world.
The report features an overview of Big Data and its place within healthcare. It examines the factors driving and necessitating the use of the technology within this industry, and provides detailed examples of how different Big Data sources and analytics techniques could be used to provide direct benefits to pharmaceutical companies, healthcare institutions and patients.
There is also an analysis of the main challenges surrounding the technology, as well as detailed real-world case studies of how major companies already implement Big Data and deal with some of the challenges. Finally, based upon the totality of our survey results and research, strategic recommendations and guidelines are provided for the effective implementation of Big Data within healthcare.
The results of GBI’s latest industry survey provide insightful analyses from different expert panels, including those that already use Big Data and those that do not, key regional markets, and respondents from within the pharmaceutical industry and those from the wider healthcare industry. The survey examined key issues, such the areas where organizations are currently utilizing Big Data, where they believe it can have the most impact, the main barriers to use and driving factors, likelihood of increasing investment within the next five years, and overall stance on the use of the technology within healthcare.
GBI Research conducted extensive research in order to provide a comprehensive view of Big Data for healthcare landscape. This new report adds to our unique portfolio of trusted industry analyses that enable our clients to assess the most promising areas in the market and exploit key business opportunities.
Report at: www.orbisresearch.com/contact/179457
- What is Big Data? What is its place within healthcare, and what are the main data sources?
- How prevalent is the use of Big Data in healthcare?
- What are the main driving factors necessitating the use of Big Data in healthcare? What is the relative importance of these factors according to industry?
- What are examples of the commercial benefits that the use of Big Data and analytics can provide, in different aspects of the industry?
- In which areas are organizations currently using Big Data, and where do they feel it will have the most impact in the next five years?
- What are the main challenges associated with Big Data in healthcare? What is the relative importance of these factors according to industry? For the organizations that do not yet utilize Big Data, what specific reasons have led to their decision not to do so?
- How do major pharmaceutical and healthcare companies use Big Data in the real world? What are some of the main partnerships between Big Pharma and technology companies? What is the underlying technical architecture of Big Data in healthcare?
- What is the likelihood that organizations that already use Big Data will increase their investment within the next five years? Will those that do not currently invest in the technology begin doing so in the next five years?
- How can Big Data be effectively implemented within an organization?
- What is the overall stance of various experts in the healthcare field on the use of Big Data in healthcare?
Key Reasons to Access
This report will allow you to -
- Gain insightful analyses and comprehensive understanding of Big Data in healthcare
- Understand the key drivers necessitating the use of Big Data and the main barriers to implementation
- Understand the views of 73 organizations within the industry on Big Data, and assess real-world case studies
- Assess the most relevant uses of Big Data within your company, and effective ways of implementing Big Data strategies
Some Points From TOC:
1 Table of Contents
1 Table of Contents 5
1.1 List of Tables 7
2 Big Data Overview 9
2.1 What is Big Data? 9
2.2 The ‘Three Vs’ of Big Data: Volume, Velocity and Variety 9
2.3 The Sources of Big Data in Healthcare 10
3 Drivers of Big Data in Healthcare 17
3.1 Advances in Technology: Explosion in Data Generation 17
3.1.1 Next-Generation Sequencing Technologies: Outpacing Moore’s Law 17
3.1.2 Proteomic Databases: ProteomicsDB Designed with Big Data Analytics in Mind 18
4 Commercial Implications of Big Data in Healthcare 27
4.1 Predictive Modeling: Fundamental Source of Big Data’s Power 27
4.1.1 Using Big Data for Patient-Specific Modeling: Potential for Huge Healthcare Savings 28
4.2 Big Data Unlocks the Potential of Personalized Medicine and Targeted Therapies 28
5 Challenges Associated with Big Data in Healthcare 38
5.1 Data Quality: Analysis Output Can Only Be as Good as the Data Input 38
5.1.1 Does “Messy” Real-World Data Have a Place in Evidence-Based Medicine? 38
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