Published on : Jul 30, 2018
Albany, New York, July 30, 2018: Applications of data mining and big data analytics for procurement of relevant data pertaining to research and development of drugs, patient information, and drug pricing, articulate growth of big data in healthcare and pharmaceutical industry. In its recent report addition titled, ‘Big Data in the Healthcare & Pharmaceutical Industry: 2018 - 2030 - Opportunities, Challenges, Strategies & Forecasts’ Market Research Hub (MRH) offers crucial insights on the implications of current developments on the growth of big data in pharmaceutical and healthcare industry.
Digital Analysis Forms the Core of Big Data in Healthcare and Pharmaceutical Industry
To pace up with evolving end-use industry demands of accurate management of data, service providers are eyeing on developing apt big data platform that streamlines operations in pharmaceutical sector. Digital analysis of patient condition lends a significant push towards adoption of big data in healthcare and pharmaceutical industry.
In a path breaking development, leading pharmaceutical stalwart Roche has recently acquired Viewics, best known for offering big data solutions for acquiring actionable medical data and conversion of the same into crucial insights. With this major acquisition, Roche aims to enhance its digital capabilities. The development is a milestone in the burgeoning success stories of big data applications in pharmaceuticals, thus reflecting growth traces in big data in healthcare and pharmaceutical industry market.
Further, to propel growth in big data applications in healthcare and pharmaceutical industry, market player Accenture has sealed a deal to acquire Kogentix. The latter is a veteran in offering apt solutions in Hadoop, Spark, and Python. The deal is envisioned to impact data engineering processes of Accenture, and enhance its portfolio of big data offerings in healthcare and pharmaceutical industry.
Veritable research findings encompassed in the report provide an overview of market segments. This section of the report identifies type and applications as major segments prevailing in healthcare and pharmaceutical industry. Based on type the market is segregated as hardware, software, and professional services. Based on applications, big data in healthcare and pharmaceutical industry market is fragmented as pharmaceutical & medical products, operations, awareness and disease prevention programs, health insurance, and marketing. Elaborate account of market segmentation contained in the report allow readers to gauge the impact of these segments in prompting growth in big data in healthcare and pharmaceutical market. Also, these report findings allow readers to identify the segment associated with revenue maximization in the market.
Additionally, the report also offers a holistic view of regional distribution of big data in healthcare and pharmaceutical industry market. Based on region, the market is categorized as Europe, North America, Latin and Central America, Asia Pacific, and Middle East and Africa. Through research components contained in the report allow readers to determine various marketing practices employed by market players in various regions of data in healthcare and pharmaceutical industry market. Readers are also enlightened about the impact of these strategies on customer behavior.
Competitive Landscape: Big Data in Healthcare and Pharmaceutical Industry Market
Exhaustive research findings recorded in the report allow readers to decipher the impact of these marketing practices in steering positive end-user response such as their purchase preferences and buying behavior. Market players in big data in healthcare and pharmaceutical industry market can analyze these winning strategies to incur relevant insights. Based on these insights market players can facilitate profit oriented marketing objectives and business strategies that fetch sustenance and increased revenues in the market. Key players identified in big data in healthcare and pharmaceutical market consist of Absolutdata, Big Panda, Cisco Systems, Databricks, and HCL Technologies amongst several others.
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