Data Science Platform Market Size & Business Planning, Innovation to See Modest Growth

The global data science platform market (henceforth, referred to as the market studied) was valued at USD 31.05 billion in 2019, and it is expected to reach USD 230.80 billion by 2025, registering a CAGR of 39.7 % during the forecast period. The data science platform comprises the software hub around which all the types of data science work takes place, including integrating and exploring data from various sources, coding, and building models. It also leverages the data, deploys models into production, and serves up results through model-powered applications or reports. It allows data scientists within a single environment to discover actionable insights from data, plan a strategy, and in communicating the collected ideas throughout an enterprise.

– IT managers who support a large team of data scientists in an enterprise setting are tasked with data governance and providing the infrastructure and tools that data scientists need. The proliferation of data science tools and applications available provides opportunities along with challenges.
– Data science encompasses many job titles across different industries and organizations, starting from analytics officer, to actuary, to research scientist. But regardless of all title posts, all the roles are united in unlocking strategic insights from data, for which business demand is stronger than ever before. IBM estimated that the need for data scientists would soar 28% by 2020. The increased usage of large amounts of structured and unstructured data in the various end-user industry is boosting the adoption of big data. For instance, according to Seagate Technology PLC, the global volume of data is expected to increase to 47 zettabytes and 163 zettabytes in 2020 and 2025, respectively, from 12 zettabytes in 2015.

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Key Market Trends

Healthcare Sector to Dominate the Market over the Forecast Period

– Health care is a segment where individual pieces of data provide life-or-death importance, and many organizations fail to aggregate data adequately to gain insights into broader care processes. Drawing conclusions and making decisions based on data and efficiently using medical knowledge to improve safety and quality is impossible without a comprehensive data science strategy.
– The data science platform provides various medical research communities that can broadly share, integrate, and analyze historical, patient-level data from academic and industry phase III clinical trials. Such a rich data set is a part of data science and undoubtedly will help the pharmaceutical research and development segment.
– Further, players are offering new platforms that are cloud-agnostic and can be deployed as a single-tenant Platform on AWS, GCP, Azure, or Private Cloud. In June 2020, Aigenpulse introduced a new data intelligence platform designed to expedite drug discovery and development. Aigenpulse platform harnesses the latest artificial intelligence (AI) and machine learning tools to deliver advanced analytics to underpin scientific decision making.
– Also, scientists can process hundreds of datasets simultaneously and at scale, making them free for higher-value tasks. The platform easily integrates with ELNs and LIMSs, in-house data lakes for sample/experiment meta-data, and public data sources, such as TRON, TCGA, and GTeX.

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