Prescriptive analytics is a type of advanced analytics that helps organizations make better decisions by taking into account all of the available data and information. This type of analytics goes beyond simply descriptive or predictive analytics, which only give organizations a limited view of what has happened or what could happen in the future. Prescriptive analytics takes into account all of the available data and information, as well as the organization’s goals and constraints, to help organizations make the best possible decisions.
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Key Trends and Drivers
The prescriptive analytics market is growing at a rapid pace due to the increasing adoption of data-driven decision making by organizations across various industry verticals. The market is being propelled by the need to reduce operational costs, improve process efficiency, and gain a competitive edge over rivals.
Restraints & Challenges
The restraints in the prescriptive analytics market are data quality and the lack of skilled resources. Data quality is a challenge because it can be difficult to obtain accurate and timely data. The lack of skilled resources is a challenge because prescriptive analytics requires specialized skills and knowledge.
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Market Segments
The Prescriptive Analytics Market has been segmented into Component, Deployment Mode, and Region. Based on the Component, the Prescriptive Analytics Market is bifurcated into Software and Services. On the basis of Deployment Mode, the market is bifurcated into Cloud and On-Premises. Region-wise, the market is analyzed across North America, Europe, Asia-Pacific, and the Rest of the World.
Key Players
Some major key players of Prescriptive Analytics Market are IBM (US), Microsoft (US), Salesforce (US), SAP (Germany), SAS Institute (US), Talend (Germany), FICO (US), Ayata (Canada), Altair (US), and Alteryx (US).
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