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Corporate Training Services Market Key Drivers & Forecast by Fact MR The corporate training services market (기업 교육 서비스 시장) is anticipated to be valued US$ 361.7 billion in 2023 and grow at a compound annual growth rate (CAGR) of 6.4% to surpass US$ 672.7 billion by 2033. The market for corporate training services is leading organisational development and offering a complete framework for improving workers' abilities. This synopsis delves into the history of corporate training services and highlights their importance in the quickly changing business environment of today. Businesses looking to empower their workers and maintain competitiveness in the global marketplace must grasp the fundamentals of the corporate training services market, which includes everything from the rise of e-learning to customised training programmes. Want Full Report? Enquire Here-https://www.factmr.com/report/corporate-training-services-market Market Insights Unlocking the potential of the Corporate Training Services Market (Pasaran Perkhidmatan Latihan Korporat) requires a deep dive into the insights that shape its dynamics. This section explores the latest trends, learning methodologies, and technological advancements driving the industry. From the rise of virtual training modules to the integration of artificial intelligence in personalized learning paths, these insights provide a holistic understanding of the evolving landscape and help organizations tailor their training strategies to meet the diverse needs of modern learners.

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Everything You Need to Know About Customer Data Platform A customer data platform is a technology that enables companies to collect customer data from various systems, data streams, or channels to create an integrated profile of the customer. These technologies generally comprise customer automation and database, along with resources for the management of real-time customer interactions, connected data, and multichannel campaigns. A customer data platform incorporates all of that data in real-time for businesses, enabling them to provide advanced-personalized experiences for consumers. Customer data platforms are beneficial as a central database for data at the user level. They combine databases that conventionally don’t share data, such as service software, e-commerce engines, and marketing platforms. This enables businesses to easily access the insights they required to connect with customers. Capabilities of Customer Data Platform The major capabilities customer data platform comprises are: • Integrate data of customers from external and internal sources in various formats, such as unstructured and structured data, to generate a single profile for every consumer. • Combines customer data in a central location so it can be easily accessed by the sales, marketing, finance, and customer support teams. • Provides tools for operations and data management, as well as additional features, for instance, reporting and analytics. • Can utilize machine learning and artificial intelligence in its set of features. Additionally, customer data platforms are majorly used by businesses for the campaign as they can gather customer information from numerous sources, allowing segmentation of customers based on several parameters, and offering real-time understandings for targeted marketing. Read More: https://www.psmarketresearch.com/market-analysis/customer-data-platform-market

North America Leading AI in Agriculture Market The size of the AI in agriculture market was USD 1,254.6 million in 2022, and it will advance at a CAGR of 26.7% in the years to come, to reach USD 8,308.5 million by 2030, as per a market research company P&S Intelligence. The service category will experience the faster growth because of the increasing requirement for managed services by farmers for tracking the processes and activities of sensors and managing large data sets associated with crop health. The product category dominates the industry because of the surging necessity for software to control and guide the devices fitted in an agronomical environment for performing numerous advanced cultivation practices. The machine learning category has the largest share, of about 60%. This is because of the growing acceptance of this technology by organizations and farmers for enhancing crop productivity with a combination of agronomical sciences and data technologies. It will hold the same position in the years to come, because of its rising usage in agricultural applications, including crop and field management. Read More: https://www.psmarketresearch.com/market-analysis/artificial-intelligence-in-agriculture-market