Data Science Platform Market

According to a research report "Data Science Platform Market with COVID-19 Impact Analysis by Component (Platform & Services), Business Function (Marketing, Sales, Logistics, & Customer Support), Deployment Mode, Organization Size, Industry Vertical & Region - Global Forecast to 2026" published by MarketsandMarkets, the Data Science Platform market size is projected to grow from USD 95.3 billion in 2021 to 322.9 USD billion in 2026, at a Compound Annual Growth Rate (CAGR) of 27.7% during the forecast period. The Data Science Platform industry is driven by Astonishing growth of big data, however, Rising in adoption of cloud-based solutions, Rising application of the data science platform in various industries and Growing need to extract in-depth insights from voluminous data to gain competitive advantage.

Browse 310 market data Tables and 57 Figures spread through 349 Pages and in-depth TOC on "Data Science Platform Market with COVID-19 Impact Analysis by Component (Platform & Services), Business Function (Marketing, Sales, Logistics, & Customer Support), Deployment Mode, Organization Size, Industry Vertical & Region - Global Forecast to 2026"
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Based on the Component, platform segment to account for a larger market size during the forecast period

The Data Science Platform market has been segmented by two components: platform and services. The deployment of Data Science Platform has witnessed an increase in adoption, as serves a variety of purposes, such as ML modeling and predictive analytics. The growing adoption of Data Science Platform across all major verticals, such as BFSI, Retail and eCommerce, Telecom and IT, Media and Entertainment, Healthcare and Life Sciences, Government and Defense, Manufacturing, Transportation and Logistics, Energy and Utilities, Other Verticals ( travel and hospitality, and education and research).

Based on deployment mode, cloud segment to grow at a higher CAGR during the forecast period

Cloud computing refers to the storage, management, and processing of data via networks of remote servers, which are typically accessed via the Internet. According to Statista, cloud computing would generate more than USD 300 billion in revenue in 2020 as a component of IT services. At the same time, PwC shows the COVID-19 crisis has accelerated the cloud transition even further as per data during the first quarter of 2020, cloud spending increased by 37% to USD 29 billion. The increasing generation of data leads to various challenges for several organizations. These challenges include storage, privacy, and affordability.

Based on services, professional services segment to hold the largest market size during the forecast period

Customized, knowledge-based services that are offered to clients fall under the professional services category. These services include network deployment and customization, maintenance and support services, consulting services, designing, installation, training, network planning, network analysis, and outsourcing services. Online support, live chat for real-time answers, other real-time support options, and community portals are established so that clients can meet and exchange ideas with people in other organizations.

Based on business function, Finance and Accounting segment to grow at a higher CAGR during the forecast period

Financial services firms and banks, for example, use financial data science: Forward-thinking banks and FinTech’s improve customer service by evaluating transactional and behavioral data using various data science methods. Data science is already being used by some of the worlds largest banks to acquire insights from previous customer purchases, engagements, and accounts that are most relevant to them. Investing items, insurance coverage, bank accounts, and mortgages are now the most common notices they receive. Data science is also providing insights into how well a product sells or to whom it sells, allowing financial services organizations and banks to build consumer products, policies, and investment instruments that will sell well in the future.

Based on vertical, the healthcare and life science segment is expected to grow at a higher CAGR during the forecast period

Data Science Platform are gaining acceptance among all verticals to improve profitability and reduce overall costs. The major verticals adopting Data Science Platform are BFSI, Retail and eCommerce, Telecom and IT, Media and Entertainment, Healthcare and Life Sciences, Government and Defense, Manufacturing, Transportation and Logistics, Energy and Utilities, Other Verticals ( travel and hospitality, and education and research). Healthcare and life science, by vertical segment, is expected to grow at a higher CAGR during the forecast period

Based on organization size, SMEs segment to grow at the highest CAGR during the forecast period

The Despite contributing a major share to the world’s economy, SMEs are more open toward the adoption of new technologies to smoothen and enhance the business processes, but SMEs are under constant pressure to adopt cost-effective and reliable strategies that effectively support their business goals and help them grow. Small businesses can use Data Science Platform to better understand their customers, including what motivates them to buy, how they prefer to shop, why they switch, what they will buy next, and what variables cause them to promote a firm to others.

North America to hold the largest market size during the forecast period

North America is estimated to account for the largest market share during the forecast period. In North America, data discovery and Data Science Platform are considered highly effective by most organizations and verticals. On the other hand, Europe is gradually incorporating these advanced solutions within its enterprises. APAC is witnessing a substantial rise in the adoption of Data Science Platform owing to the increasing digitalization and rising demand for centrally managed systems.

Major Data Science Platform vendors include IBM (US), Google (US), Microsoft (US), SAS (US), AWS (US), MathWorks (US), Cloudera (US), Teradata (US), TIBCO (US), Alteryx (US), RapidMiner (US), Databricks (US), Snowflake (US), H2O.ai (US), Altair (US), Anaconda (US), SAP (US), Domino Data Lab (US), Dataiku (US), DataRobot (US), Apheris (Germany), Comet (US), Databand (US), dotData (US), Explorium (US), Noogata (US), Tecton (US), Spell (US), Arrikto (US), and Iterative (US). These market players have adopted various growth strategies, such as partnerships, collaborations, and new product launches, to expand have been the most adopted strategies by major players from 2018 to 2022, which helped companies innovate their offerings and broaden their customer base.

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