Big data in healthcare market revenue is expected to grow at lucrative rate over the forecast period primarily due to increased digitalization in industrial process. Digitization is transforming industrial processes, functions, products, and services. Advent of e-commerce has resulted in a sudden spurt in data being generated by various companies. Also, with decades of research and development activities across the healthcare industry, there is a large amount of data, referred to as ‘big data’, piled up with host organizations. It is therefore essential to ensure optimum utilization of this data for reducing costs, providing targeted products and services, and avoiding duplication of work. Big data solution helps simplifying and analyze complex and diverse data, a task that cannot be achieved using conventional software and hardware. Moreover, such kind of data cannot be managed with trivial data management tools and methods. Various tools such as Pentaho, Hadoop, Cloudera, and MongoDB are available in the market for the same. These tools help in data cleaning, mining, and analyzing of big data. There are also various data visualization tools such as Tableau, Silk, and Chartio that help in presenting the data in a more convenient and readable form.
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Big data helps healthcare companies to mitigate the risk of losing millions of dollars in revenue and profits through their conventional strategic decision making methods. Globally, big data in healthcare market scenario can be segmented on the basis of application, analytics type, delivery model, and end users.
- Big Data in Healthcare Market, by Analytics Type
- Descriptive Analytics
- Predictive Analytics
- Prescriptive Analytics
- by Application
- Clinical Analytics
- Financial Analytics
- Operational and Administrative Analytics
- Population Health Analytics
- by Delivery Model
- by End User
- Third party care organizations
Pharmaceutical companies, payers, and experts are using big data analytics/solutions to analyze and obtain insights about industry trends and accordingly make detailed and accurate projections about the market. Based on the insights from big data solutions, various recipients can make informed decisions to improve their products or services.
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Dearth of Skilled Manpower to Inhibit Growth of Big Data in Healthcare
Although, the market is huge in the developed nations, particularly in the U.S., dearth of trained personnel for analyzing big data is projected to limit the growth of this market in North America. Moreover, factors such as decreasing profit margins, slowdown in the global economy, and lack of skilled manpower is inhibiting growth of big data implementation in the healthcare industry. Some of the other challenges for big data in healthcare include data fragmentation, security issues, and lack of standardization. Furthermore, big data solution providers need to ensure compliance with regulations laid by the Health Insurance Portability and Accountability Act of 1996 (HIPAA). These factors are especially prevalent in developing economies of Asia Pacific and Latin America due to lack of effective healthcare infrastructure and inadequate supportive government regulations. Increasing cost pressure and lack of trained professionals dissuades healthcare providers from implementing expensive systems supporting big data solutions. However, improvement in IT infrastructure in developing economies over the near future is expected to be a major contributor for increase in demand for big data.
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There are various small and global players offering big data software and services. The small regional players offer big data services at low costs, which creates a high entry barrier for global players looking to establish their footprint in emerging markets. The market is highly fragmented, with various players offering services differentiated in terms of pricing and inclusions. Some of the key companies in the global big data in healthcare market include Hewlett-Packard Co., Teradata Corporation, Opera Solutions, Cognizant Technology Solutions, Siemens Healthcare Gmbh, Mu Sigma, Splunk Inc., Cloudera, EMC, IBM, Calpont Corporation, and Oracle Corporation.
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