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到 2028 年的增强分析市场预测——按组件、部署、组织规模、最终用户和地区进行的全球分析Augmented Analytics Market Forecasts to 2028 - Global Analysis By Component, Deployment, Organization Size End User and Geography |
根据 Stratistics MRC 的数据,2022 年全球增强分析市场规模将达到 96.7 亿美元,预测期内復合年增长率为 16.4%,预计到 2028 年将达到 240.5 亿美元。 增强分析是指使用机器学习和人工智能等赋能技术来协助数据准备、洞察生成和洞察解释,增强在分析和 BI 系统中探索和理解数据的方式。 它还通过自动化构建、管理和部署数据科学、机器学习和 AI 模型的许多过程来支持专业和公民数据科学家。 增强分析可以帮助企业变得更具适应性,增加对分析的访问,并使人们能够做出更明智的、数据驱动的决策、加速决策制定并降低成本。我不能。
根据 SAS 研究所的数据,预计 2020 年英国的大数据采用率预计将达到 59% 左右。 这显示了增强分析的巨大潜力,因此可以为您在在线零售领域带来巨大优势。
组织已将一些技术方面纳入其操作程序。 结果,产生了大量的数据。 这些数据通常很大且杂乱无章,但包含重要信息。 大多数组织都关心存储数据和提取知识。 对增强型分析工具(例如机器学习和自然语言处理)来分析数据的需求很大。 增强分析允许您探索组织内可用的结构化、半结构化和非结构化数据源。 由于企业流程中数字技术的发展,预计市场将会增长。
组织使用高级分析方法,这些方法本质上很复杂,需要深入的分析技能才能从数据中获得业务洞察力。 由于技术架构,增强分析是一个特别具有挑战性的领域。 采用增强分析需要技术专长、分析思维和批判性思维。 许多最终用户缺乏分析思维所需的资源和知识。 对增强分析的无知也是一个主要障碍。 此外,创建数据驱动决策文化需要业务专业知识以及正确的培训。
机器学习、人工智能和自然语言处理等技术的使用越来越多。
随着大量数据的开发和实时评估,组织被迫采用 AI、ML 和 NLP 等新兴技术。 这些技术促进了从数据中获得洞察力的整个过程。 图表和图形通常用于数据分析。 调查方法对外行人来说并不友好,并且存在误解和不标准判断的可能性。 NLP技术解决了这个问题。 战略性流媒体和这些技术的使用可以理解大型数据集并生成可用于创建独特而有效的解决方案的有洞察力的数据。
确保数据质量和安全是一项挑战,因为海量数据和多样化的数据类型增加了不良数据的可能性,这些不良数据会破坏公司、利润并减慢运营速度。. 在采用增强分析获取洞察力时,数据质量是决定数据可靠性的关键因素。 企业越来越不愿意在云中公开关键业务数据。 共享敏感的公司信息会使系统面临未经授权的访问,这可能导致系统堵塞和系统故障。 企业不愿意将数据迁移到云端,因为它们对数据存储和访问非常敏感,阻碍了市场增长。
在 COVID-19 大流行的时代,增强分析市场有望增长。 随着许多组织应对 COVID-19 流行病带来的挑战,对快速和广泛的更新和说明的需求越来越大。 这场危机为分析和基于人工智能的解决方案提供了一个机会,以支持决策制定,因为企业领导者需要更快的决策制定。 通过标记和构建数据,增强分析可自动为分析准备数据。 人工智能通过加快寻找新见解的过程来帮助分析,并对市场产生了积极影响。
由于增强分析软件,软件行业预计将实现有利可图的增长,增强分析软件是一种尖端分析驱动的应用程序,融合了人工智能等尖端技术。 然而,随着物联网等新技术的发展,对更好的分析解决方案的需求也在增加。 称为增强分析软件的工具在将数据呈现给用户之前收集、组织和分析数据。 将 AI 技术融入 BI 使用户能够快速准备和组织数据,找到有洞察力的信息并与他人共享,从而推动市场增长。
预计 IT 和电信行业在预测期内将以最快的复合年增长率增长。 使用先进的机器学习算法,我们可以扫描大量数据,包括电信呼叫详细记录,以识别模式并发现和预测网络问题。 以最先进的电信增强分析为核心的强大 IT 系统可以以极高的准确性和无差错的性能完成任务。 无监督机器学习算法可以在没有技术支持的情况下自行从数据中学习。 这节省了手动研究趋势的时间,并使营销人员能够快速响应快速变化的市场条件。 电信团队可以使用增强分析来检查技术人员绩效指标、识别不必要的服务请求并改善客户服务。
由于人工智能的广泛使用及其与人类智能竞争或完全取代人类智能的潜力,预计北美在预测期内将占据最大的市场份额。 数据消费者不得不做很多耗时且重复的任务。 这些工作现在可以通过人工智能实现自动化并实时完成,大大提高了人类的生产力。 鑑于该地区企业之间的激烈竞争,最大限度地提高生产率可以提高利润,从而提高整个企业的收入并促进该地区的增长。
预计欧洲在预测期内的复合年增长率最高,因为为新公司提供资金的风险资本可能有利于预测分析领域的扩展。 与增强分析开发相关的方法论和方法的新发展有望为知名公司提供巨大的潜力。 由于增强分析模型在欧洲的重要性和意识日益增强,对这些解决方案的需求非常高,推动了该地区的市场增长。
增强分析市场的主要参与者是: Salesforce.com, Inc, IBM, Microsoft, Sap Oracle, MicroStrategy Incorporated, SAS Institute Inc, QlikTech, TIBCO Software Inc, Sisense Inc, Information Builders, ThoughtSpot Inc, Domo, Inc, Yellowfin International, CognitiveScale, Google LLC 、Amazon Web Services, Inc. 和 Pyramid Analytics。
2023 年 1 月,Salesforce 宣布与 Walmart Commerce Technologies 建立合作伙伴关係,为零售商提供技术和服务,为世界各地的购物者提供顺畅的本地取货和送货服务。. Walmart Store Assist 技术和 Walmart GoLocal 本地交付解决方案通过 AppExchange 提供,以帮助零售商在当今的混合购物世界中取得成功。
2023 年 1 月,Microsoft 和 Qcells 宣布建立战略合作伙伴关係,以遏制碳排放并促进清洁能源经济。 Qcells是美国唯一拥有完整太阳能供应炼和一站式清洁能源解决方案的公司。
2023 年 1 月,Qlik 宣布了其收购 Talend 的意向,从而创建了两个由 Thoma Bravo 支持的行业领导者,共同关注为数据增加价值和为客户提供业务成果。将进行整合。 此外,Qlik 还被 IDC MarketScape 评为领导者。 被选为美国商业智能和分析平台 2022 供应商评估的领导者。
2022 年 12 月,Salesforce 宣布推出 Automation Everywhere Bundle,以帮助公司降低成本、提高生产力并取得成功。 但自动化的最后一英里是困难的,通常涉及更新遗留系统中的数据、扫描纸质文檔、将工作路由到多个人和系统等等。
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According to Stratistics MRC, the Global Augmented Analytics Market is accounted for $9.67 billion in 2022 and is expected to reach $24.05 billion by 2028 growing at a CAGR of 16.4% during the forecast period. The augmented analytics refers to the use of enabling technologies like machine learning and AI to help with data preparation, insight generation, and insight explanation to enhance how people explore and understand data in analytics and BI systems. By automating a lot of data science, machine learning, and AI model building, administration, and deployment processes, it also supports professional and citizen data scientists. Utilizing augmented analytics, businesses may become more adaptable, increase analytics access, and enable people to make smarter, data-driven decisions, accelerate decision-making, and cut expenses.
According to SAS Institute, estimated adoption rates of Big Data in the United Kingdom in 2020 are forecasted at around 59%. This showcases the huge potential for augmented analytics and thus, can provide a great advantage in the online retail segment.
Organizations have begun integrating several technological aspects into their operational procedures. Huge volumes of data have been produced as a result of this. Although this data frequently has a high volume and is not organised, it does contain significant information. Most organisations are concerned with data storage and knowledge extraction. A significant demand exists for augmented analytics tools like machine learning and natural language processing to analyse the data. It is now possible to examine the structured, semi-structured, and unstructured data sources that are available within an organisation thanks to augmented analytics. Due to the evolution of digital technology across company processes, it is anticipated that there would be an encouraging growth in the market.
Organization uses advanced analytics approaches that are complex in nature and call for in-depth analytical skills, to derive business insights from data. Due to the technology's architecture, augmented analytics is a particularly difficult field. A person needs technological expertise, analytical thinking, and critical thinking to employ augmented analytics. Many end consumers lack the resources and knowledge necessary for analytical thinking. Another major obstacle is the ignorance of augmented analytics. Furthermore, in order to create a culture that is data driven and decision-making, business expertise is required, along with the right training.
The use of technology for machine learning, artificial intelligence, and natural language processing is growing.
Organizations have been forced to adopt emerging technologies like AI, ML, and NLP due to the development of enormous amounts of data and the requirement to evaluate it in real time. The entire process of deriving insights from data has been made easier by these technologies. Typically, charts and graphs were used for data analysis. The research methodology was not user-friendly to the untrained eye, and there was a chance of misunderstanding and substandard judgement. The NLP technology fixes this problem. Strategic streaming and the use of these technologies may comprehend large datasets and produce insightful data that can be used to create unique and effective solutions.
Preserving data quality and safety is challenging huge amounts of data and a diversity of data types can raise the possibility of bad data, which can hurt firms and their profits and stymie operations. When employing augmented analytics to get insights, data quality is a crucial determinant of data reliability. Businesses are becoming more reluctant to disclose their vital business data on the cloud. Sharing vital company information exposes systems to unauthorised access, which could sabotage systems or result in system failure. Businesses are reluctant to transfer their data to the cloud because they are so sensitive to data storage and access therefore hindering the market growth.
During the COVID-19 pandemic era, the market for augmented analytics is anticipated to experience growing prospects. As a number of organisations deal with the difficulties brought on by the COVID-19 epidemic, the demand for quick and widespread updates and instructions has grown. The crisis offered an opportunity for analytics and AI-based solutions to support decision making since business leaders demanded that decisions be made quickly. By labelling and structuring the data, augmented analytics automates the preparation of the data for analysis. AI helps analytics by speeding up the process of finding new insights which positively impacted the market.
The Software segment is estimated to have a lucrative growth due to its one of most cutting-edge analytics-driven application that incorporates cutting-edge technology like artificial intelligence is called augmented analytics software. However, as emerging technologies, like the Internet of Things, develop, there is a growing need for better analytic solutions. A tool called augmented analytics software gathers, organises, and analyses data before displaying it to the user. By incorporating AI technology into BI, it enables users to quickly prepare and clean their data, find insightful information, and share it with others thereby propelling the market growth.
The IT & Telecommunication segment is anticipated to witness the fastest CAGR growth during the forecast period, due to the use of sophisticated machine learning algorithms, augmented analytics in telecom can scan huge amounts of data, including call detail records in the telecoms sector, to identify patterns, spot problems in the network, and foresee them. Strong IT systems with cutting-edge Augmented Analytics for telecom at their core can complete tasks with extreme precision and no mistakes. Machine learning algorithms that are unsupervised can learn from data on their own without any further technical support. It frees up time that would otherwise be used to manually research trends, allowing marketers to react more swiftly to the quickly shifting market conditions. Teams in the telecom industry can use augmented analytics to examine technician performance metrics, identify unnecessary service requests, and otherwise enhance customer service.
North America is projected to hold the largest market share during the forecast period owing to the extensive use of artificial intelligence and the acceptance of its potential to compete with or completely replace human intelligence. Data consumers had to do a number of mindless, repetitive activities that took a lot of time. These jobs are now automated and may be completed in real time owing to AI, greatly enhancing human productivity. Given the intense competition among firms in the region, productivity maximisation can be done to generate improved profits, hence increasing their overall income in turn increasing the growth in the region.
Europe is projected to have the highest CAGR over the forecast period, owing to the substantial money offered by venture capitalists to new companies is probably going to have a favourable effect on the expansion of the predictive analytics sector. For well-known players, emerging developments in methods and approaches related to the development of augmented analytics are projected to present significant potential. In Europe, there is a substantial need for these solutions because to the growing significance and awareness of augmented analytics models which are driving the market growth in this region.
Some of the key players profiled in the Augmented Analytics Market include: Salesforce.com, Inc, IBM, Microsoft, Sap Oracle, MicroStrategy Incorporated, SAS Institute Inc, QlikTech, TIBCO Software Inc, Sisense Inc, Information Builders, ThoughtSpot Inc, Domo, Inc, Yellowfin International, CognitiveScale, Google LLC, Amazon Web Services,Inc and Pyramid Analytics.
In Jan 2023, Salesforce has announced a partnership with Walmart Commerce Technologies to provide retailers with technologies and services that power frictionless local pickup and delivery for shoppers everywhere. Walmart Store Assist technology and Walmart GoLocal local delivery solutions will be available through AppExchange to help retailers thrive in today's hybrid shopping world.
In Jan 2023, Microsoft and Qcells announce strategic alliance to curb carbon emissions and power the clean energy economy, Qcells is the only company in the U.S. that will have a complete solar supply chain and provides one-stop clean energy solutions.
Inj Jan 2023, Qlik announced its intention to acquire Talend, which would bring together two Thoma Bravo-backed industry leaders with a shared focus on adding value to data to deliver business outcomes for customers. Additionally, Qlik has been named a leader in the IDC MarketScape: U.S. Business Intelligence and Analytics Platforms 2022 Vendor Assessment.
In Dec 2022, Salesforce Launches Automation Everywhere Bundle to Help Companies Lower Costs, Boost Productivity, and Deliver Success Now, However, the last mile of automation is challenging and often includes updating data in legacy systems, scanning paper documents, and routing work to multiple people and systems.
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