市場調查報告書
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1235862
到 2028 年的增強分析市場預測——按組件、部署、組織規模、最終用戶和地區進行的全球分析Augmented Analytics Market Forecasts to 2028 - Global Analysis By Component, Deployment, Organization Size End User and Geography |
根據 Stratistics MRC 的數據,2022 年全球增強分析市場規模將達到 96.7 億美元,預測期內復合年增長率為 16.4%,預計到 2028 年將達到 240.5 億美元。 增強分析是指使用機器學習和人工智能等賦能技術來協助數據準備、洞察生成和洞察解釋,增強在分析和 BI 系統中探索和理解數據的方式。 它還通過自動化構建、管理和部署數據科學、機器學習和 AI 模型的許多過程來支持專業和公民數據科學家。 增強分析可以幫助企業變得更具適應性,增加對分析的訪問,並使人們能夠做出更明智的、數據驅動的決策、加速決策制定並降低成本。我不能。
根據 SAS 研究所的數據,預計 2020 年英國的大數據採用率預計將達到 59% 左右。 這顯示了增強分析的巨大潛力,因此可以為您在在線零售領域帶來巨大優勢。
組織已將一些技術方面納入其操作程序。 結果,產生了大量的數據。 這些數據通常很大且雜亂無章,但包含重要信息。 大多數組織都關心存儲數據和提取知識。 對增強型分析工具(例如機器學習和自然語言處理)來分析數據的需求很大。 增強分析允許您探索組織內可用的結構化、半結構化和非結構化數據源。 由於企業流程中數字技術的發展,預計市場將會增長。
組織使用高級分析方法,這些方法本質上很複雜,需要深入的分析技能才能從數據中獲得業務洞察力。 由於技術架構,增強分析是一個特別具有挑戰性的領域。 採用增強分析需要技術專長、分析思維和批判性思維。 許多最終用戶缺乏分析思維所需的資源和知識。 對增強分析的無知也是一個主要障礙。 此外,創建數據驅動決策文化需要業務專業知識以及正確的培訓。
機器學習、人工智能和自然語言處理等技術的使用越來越多。
隨著大量數據的開發和實時評估,組織被迫採用 AI、ML 和 NLP 等新興技術。 這些技術促進了從數據中獲得洞察力的整個過程。 圖表和圖形通常用於數據分析。 調查方法對外行人來說並不友好,並且存在誤解和不標準判斷的可能性。 NLP技術解決了這個問題。 戰略性流媒體和這些技術的使用可以理解大型數據集並生成可用於創建獨特而有效的解決方案的有洞察力的數據。
確保數據質量和安全是一項挑戰,因為海量數據和多樣化的數據類型增加了不良數據的可能性,這些不良數據會破壞公司、利潤並減慢運營速度。. 在採用增強分析獲取洞察力時,數據質量是決定數據可靠性的關鍵因素。 企業越來越不願意在雲中公開關鍵業務數據。 共享敏感的公司信息會使系統面臨未經授權的訪問,這可能導致系統堵塞和系統故障。 企業不願意將數據遷移到雲端,因為它們對數據存儲和訪問非常敏感,阻礙了市場增長。
在 COVID-19 大流行的時代,增強分析市場有望增長。 隨著許多組織應對 COVID-19 流行病帶來的挑戰,對快速和廣泛的更新和說明的需求越來越大。 這場危機為分析和基於人工智能的解決方案提供了一個機會,以支持決策制定,因為企業領導者需要更快的決策制定。 通過標記和構建數據,增強分析可自動為分析準備數據。 人工智能通過加快尋找新見解的過程來幫助分析,並對市場產生了積極影響。
由於增強分析軟件,軟件行業預計將實現有利可圖的增長,增強分析軟件是一種尖端分析驅動的應用程序,融合了人工智能等尖端技術。 然而,隨著物聯網等新技術的發展,對更好的分析解決方案的需求也在增加。 稱為增強分析軟件的工具在將數據呈現給用戶之前收集、組織和分析數據。 將 AI 技術融入 BI 使用戶能夠快速準備和組織數據,找到有洞察力的信息並與他人共享,從而推動市場增長。
預計 IT 和電信行業在預測期內將以最快的複合年增長率增長。 使用先進的機器學習算法,我們可以掃描大量數據,包括電信呼叫詳細記錄,以識別模式並發現和預測網絡問題。 以最先進的電信增強分析為核心的強大 IT 系統可以以極高的準確性和無差錯的性能完成任務。 無監督機器學習算法可以在沒有技術支持的情況下自行從數據中學習。 這節省了手動研究趨勢的時間,並使營銷人員能夠快速響應快速變化的市場條件。 電信團隊可以使用增強分析來檢查技術人員績效指標、識別不必要的服務請求並改善客戶服務。
由於人工智能的廣泛使用及其與人類智能競爭或完全取代人類智能的潛力,預計北美在預測期內將佔據最大的市場份額。 數據消費者不得不做很多耗時且重複的任務。 這些工作現在可以通過人工智能實現自動化並實時完成,大大提高了人類的生產力。 鑑於該地區企業之間的激烈競爭,最大限度地提高生產率可以提高利潤,從而提高整個企業的收入並促進該地區的增長。
預計歐洲在預測期內的複合年增長率最高,因為為新公司提供資金的風險資本可能有利於預測分析領域的擴展。 與增強分析開發相關的方法論和方法的新發展有望為知名公司提供巨大的潛力。 由於增強分析模型在歐洲的重要性和意識日益增強,對這些解決方案的需求非常高,推動了該地區的市場增長。
增強分析市場的主要參與者是: 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 宣布與 Walmart Commerce Technologies 建立合作夥伴關係,為零售商提供技術和服務,為世界各地的購物者提供順暢的本地取貨和送貨服務。. Walmart Store Assist 技術和 Walmart GoLocal 本地交付解決方案通過 AppExchange 提供,以幫助零售商在當今的混合購物世界中取得成功。
2023 年 1 月,Microsoft 和 Qcells 宣佈建立戰略合作夥伴關係,以遏制碳排放並促進清潔能源經濟。 Qcells是美國唯一擁有完整太陽能供應鍊和一站式清潔能源解決方案的公司。
2023 年 1 月,Qlik 宣布了其收購 Talend 的意向,從而創建了兩個由 Thoma Bravo 支持的行業領導者,共同關注為數據增加價值和為客戶提供業務成果。將進行整合。 此外,Qlik 還被 IDC MarketScape 評為領導者。 被選為美國商業智能和分析平台 2022 供應商評估的領導者。
2022 年 12 月,Salesforce 宣布推出 Automation Everywhere Bundle,以幫助公司降低成本、提高生產力並取得成功。 但自動化的最後一英裡是困難的,通常涉及更新遺留系統中的數據、掃描紙質文檔、將工作路由到多個人和系統等等。
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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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