![]() ![]() ![]() Growing concerns of data security and protectionģ.5.3.1. Advancement of big data technologiesģ.5.2.1. Increase in data collection and analysis from mobile devicesģ.5.1.5. Increase in focus on Return on Investment (ROI)ģ.5.1.4. Realization of importance of data science platform by organizationsģ.5.1.3. Moderate bargaining power among buyersģ.5.1.2. Moderate bargaining power of suppliersģ.3.5. KEY MARKET PLAYERS PROFILED IN THE REPORTģ.3.1. Others (retail, education, government, energy, and utilities).The data science platform market is segmented based on type, end user, and geography. The quantitative analysis of the global data science market from 2017 to 2023 has been provided to determine the market potential.Porter’s five forces analysis illustrates the potency of buyers and suppliers that operate in the industry.Information regarding key drivers, restraints, and opportunities, along with their impact analysis on the data science platform market size has been provided.This study provides an in-depth analysis of the global data science platform market, along with the current and future trends to elucidate the imminent investment pockets.The data science platform industry comprises solutions and service providers such as Microsoft Corporation, IBM Corporation, SAS Institute, Inc., SAP SE, RapidMiner, Inc., Dataiku SAS, Alteryx, Inc, Fair Issac Corporation, MathWorks, Inc, and Teradata, Inc. The data science platform market is analyzed based on four regions-North America, Europe, Asia-Pacific, and LAMEA. Based on end users, the market is classified into banking and financial services, insurance (BFSI) telecommunication healthcare transportation & logistics manufacturing, and others (retail, education, government, energy, & utilities). Based on type, it is categorized into solutions and services. The data science platform market is segmented on the basis of type, end user, and region. However, high investment costs, data privacy & security, and reliability issues observed by the employees are projected to hamper the data science platform market growth. The advancement of big data technology and a realization of the importance of collecting and using data for decision making are anticipated to drive the data science platform market growth during the forecast period. It helps data scientists enhance their analysis by helping them track, share, reproduce, run, and deploy analytical models faster. It contains all the tools required to execute a lifecycle that spans different phases such as data ideation, model development, and model deployment. ![]() Data science platform is a framework that governs the lifecycle of any data science project, which employs techniques and theories drawn from various fields such as mathematics, statistics, information science, etc. ![]()
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