Global Data Science Platform Market business opportunities including key players forecast till 2029

February 01, 2023

The use of data science platforms by medium-sized and small-sized businesses has grown significantly in recent years. Additionally, firms are increasingly inclined to use cutting-edge technologies, such as automation and digitalization, which create a tons of data as well as complicated business procedures. As a result, the need for data science platform solutions is increasing, opening up profitable opportunities for businesses in the market.

Global data science platform market was valued at USD 95.30 billion in 2021 and is expected to reach USD 686.71 billion by 2029, registering a CAGR of 28.00% during the forecast period of 2022-2029. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.

Global Data Science Platform Market, By Component Type (Platform, Services), Function Division (Marketing, Sales, Logistics, Finance and Accounting, Customer Support, Business Operations, Others), Deployment Model (On-Premises, Cloud based), Organization Size (Small and Medium-sized Enterprises (SMEs), Large Enterprises), End User Application (Banking, Financial Services, and Insurance (BFSI), Telecom and IT, Retail and E-commerce, Healthcare and Life sciences, Manufacturing, Energy and Utilities, Media and Entertainment, Transportation and Logistics, Government, Others) – Industry Trends and Forecast to 2029.

A data science platform is a pre-packaged software program that offers the capabilities necessary for a data science project's whole life cycle. Platforms for data science are essential tools for data scientists. It makes model creation, model distribution, and data exploration possible. It offers a large-scale computing infrastructure and makes data preparation and visualization easier. Data science platforms offer a centralized platform that encourages user collaboration. Data science platforms act as a one-stop shop for data modelling since they include the APIs necessary for model creation and testing with little help from outside engineers.

The data science platform market is segmented on the basis of component type, function division, deployment model, organization size and end user application. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

The data science platform market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to data science platform market.