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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

North America Is Dominating Automated Machine Learning Market In 2022, the automated machine learning market size stood at USD 631.0 million, which is projected to witness a 49.2% CAGR during 2022–2030, reaching USD 15,499.3 million by 2030 as per P&S Intelligence. Read More: https://www.psmarketresearch.com/market-analysis/automated-machine-learning-market

How Is 5G Adoption Boosting Data Center Infrastructure Management Demand? Data center strategy needs to be planned in such a manner that the systems never malfunction in any circumstance. As a result, data center managers are opting for data center infrastructure management (DCIM) solutions as they offer insights and visibility by monitoring different parameters, such as the performance of data center computers and servers, network operations, and security uptime, and resolving network issues as they arise. Owing to these advantages, DCIM solutions are being increasingly adopted by organizations for improving their decision-making process and by data centers for enhancing their uptime with better energy services. The surging use of such solutions can be credited to the increasing deployment of 5G network, which enables smooth movement of data between locations. This novel communication technology will offer support for extensive machine-to-machine communications, with around 100,000 connections per square kilometer. 5G also plays a significant role in establishing smart cities, which generate a huge volume of data that needs to be managed efficiently. Thus, the rising penetration of the 5G network, will steer the data center infrastructure management market growth during 2021–2030. According to P&S Intelligence, the market reached $1,425.6 million revenue in 2020. At present, DCIM solutions offered by Panduit Corporation, Infosys Ltd., ABB Ltd., IBM Corporation, Huawei Technologies Co. Ltd., Modius Inc., CommScope Inc., Nlyte Software, Delta Electronics Inc., NTT DATA Corporation, Hewlett-Packard Enterprise, Raritan Inc., and Cisco Systems Inc. are mostly used for asset management application. In recent years, information technology (IT) asset management has become very difficult due to the surging complexities of the systems. Many small organizations use paper and pen and spreadsheet-based solutions to track their IT assets, which cannot deal with the accelerating pace of IT infrastructure development. Currently, DCIM solution proving companies are mostly focusing on product development and launches to cater to the evolving needs of customers. For instance, in March 2020, ABB Ltd. introduced MegaFlex, a compact and resilient uninterruptible power supply (UPS) system, for continuous data center operations. This system was introduced to meet the burgeoning demand for infrastructure as a service (IaaS) and software as a service (SaaS) applications in business organizations, owing to which, data centers have become extensively crucial. Such novel products are being utilized by the banking, financial services, and insurance (BFSI), manufacturing, telecommunications, government and public sector, healthcare and life sciences, and IT and information technology-enabled services (ITeS) sectors for managing their data centers. All these sectors prefer on-premises solutions over the cloud-enabled ones, as monitoring data on infrastructure availability, humidity, power consumption, temperature, airflow, and other aspects has become very important, which can be efficiently done through such solutions. In the coming years, the Asia-Pacific (APAC) data center infrastructure management market will record the fastest sales of DCIM solutions, due to the accelerating adoption rate of advanced digital technologies, such as the internet of things (IoT) and machine learning, in Japan, China, and India. Moreover, the mounting investments being made in infrastructure development in these countries and escalating interest of regional governments on developing data centers will fuel the adoption of DCIM solutions in the region in the foreseeable future. Thus, the growing penetration of 5G network and soaring need for managing high volumes of data generated by several end-use industries will augment the need for DCIM solutions in the forthcoming years. Read More: https://www.psmarketresearch.com/market-analysis/data-center-infrastructure-management-dcim-market

Deep Learning Market To Grow by almost $100.0 Billion during 2020–2030 A number of factors, such as the rising focus of companies on reducing their operational costs and surging adoption of deep learning solutions in contact centers, are projected to boost the growth of the deep learning market at a CAGR of 35.2% during the forecast period (2020–2030). According to P&S Intelligence, the market generated $3.7 billion revenue in 2019, which is expected to reach $102.4 billion by 2030. Moreover, the market is witnessing the surging deployment of deep learning solutions in the healthcare sector. One of the prime factors propelling the demand for deep learning solutions is their surging adoption in contact centers. These centers are the largest users of such algorithms, which help them in enhancing first-call resolution, shortening the call duration, improving the customer satisfaction, and reducing the call volume, which, in turn, increases the revenue of companies. On the basis of the nature of the solutions, the calls are efficiently routed to the concerned people possessing satisfactory knowledge, and these algorithms help in decreasing the time taken for issue resolution. The application segment of the deep learning market is categorized into signal recognition, data mining, image recognition, recommendation engine, and natural language processing (NLP). Among these, the NLP category is projected to witness the highest CAGR in the coming years due to the surging demand for assimilating deep learning solutions with NLP to improve machine–human interactions. NLP with deep learning algorithms allows voice assistants and chatbots to better recognize the queries of customers and reply accordingly, without the intervention of human beings. Additionally, based on industry, the deep learning market is classified into banking, financial services, and insurance (BFSI), healthcare, manufacturing, automotive, retail, and others. Among these, the healthcare industry is projected to generate the largest demand for deep learning solutions in the coming years. This can be ascribed to the surging deployment of artificial intelligence (AI) technologies, such as deep learning, machine learning (ML), and big data, in the healthcare sector to support medical researchers and professionals in the analysis and extraction of data, for improved medical results. Geographically, the North American deep learning market accounted for the largest revenue share in 2019. This is attributed to the developed IT infrastructure, technological advancements, presence of several key market players, and rapid implementation of these solutions for product recommendations, voice assistance, and image recognition on social networks. The Asia-Pacific (APAC) market is set to witness the swiftest growth during the foreseeable period owing to the swift economic growth, increasing deployment of advanced technologies, rising IT investments, and mounting number of AI startups in the region. Thus, the surging adoption of deep learning solutions in contact centers and rising focus of companies on reducing their operational costs are expected to propel the market growth across the world during the forecast period. Read More: https://www.psmarketresearch.com/market-analysis/deep-learning-market-report