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市場調查報告書
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1615886

記憶體內分析的全球市場規模:各零件，各用途，各組織規模，各業界，地區範圍及預測

Global In-Memory Analytics Market Size By Components, By Application, By Organization Size, By Industry Vertical, By Geographic Scope And Forecast
出版日期: | 出版商: Verified Market Research | 英文 202 Pages | 商品交期: 2-3個工作天內

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簡介目錄

記憶體分析市場規模與預測

2023 年記憶體分析市場規模為 29.8 億美元，2024-2030 年預測期間複合年增長率為 18.38%，到 2030 年將達到 69.3 億美元。

全球記憶體分析市場驅動因素

記憶體分析市場的市場驅動因素可能受到多種因素的影響。

加速商業決策

更快地制定業務決策：即時資料處理對於企業快速做出洞察和決策變得越來越必要。記憶體分析的採用是由於其比傳統的基於磁碟的方法更快地分析資料的能力。

大數據的成長：

隨著大數據繼續呈指數級增長，公司面臨著尋找更快、更有效的方法來分析大量數據的壓力。大數據管理需要記憶體分析提供的速度和可擴展性。

技術進步：

由於技術的進步，例如更低的 RAM 價格和更快的運算速度，記憶體分析變得更加經濟實惠且廣泛使用。

增加商業智慧 (BI) 工具的使用：

組織越來越依賴 BI 工具，這些工具利用記憶體分析來改善報表、資料視覺化和決策。

雲採用：

遷移到雲端運算使記憶體分析和解決方案的實施變得更加容易，因為雲端平台提供了必要的規模和基礎設施。

競爭優勢：

透過提高資料處理速度並實現更靈活、更明智的業務策略，企業正在部署記憶體分析以獲得競爭優勢。

與物聯網整合：

隨著物聯網 (IoT) 的發展，它將產生大量必須即時處理的資料。有效分析物聯網資料需要記憶體分析。

增強的預測分析：

作為預測模式和行為的手段，預測分析的需求日益增長。記憶體分析可以加快資料處理速度，從而提高預測模型的效能。

全球記憶體分析市場的限制因素

實施成本高：

引入記憶體分析/解決方案需要大量的前期投資。這包括專用軟體、具有大量 RAM 的硬件，以及將這些系統與您目前的 IT 基礎架構整合的價格。對於中小企業（SME）來說，這樣的費用可能難以負擔。

整合複雜度：

將記憶體分析與目前的遺留系統和資料庫整合可能既困難又耗時。組織經常面臨挑戰，因為無縫整合需要特定的技能和經驗。

資料安全性問題：

記憶體分析需要即時管理大量數據，因此保護此類數據的隱私和安全至關重要。由於資料外洩的可能性以及嚴格安全協議的需要，企業可能會猶豫是否要實施此類解決方案。

可擴充性問題：

雖然記憶體分析可以實現快速資料處理，但擴展系統以管理大量資料可能既昂貴又困難。這些系統的可擴充性可能會受到 RAM 硬體限制的影響。

硬體依賴

：特別大的 RAM 對於可用於記憶體分析的高效能硬體至關重要。這種依賴性可能會導致維護和硬體故障問題，並影響系統可靠性。

缺乏熟練勞動力：

採用記憶體分析需要知識淵博的專業人員，他們了解該技術以及如何將其應用到業務環境中。缺乏合格的人員可能會阻礙這些解決方案的採用和有效使用。

監理與合規問題：

有關資料處理、儲存和隱私的規定因行業和地區而異。這些法規可能很難克服，並且可能會阻止記憶體分析工具在某些市場的使用。

市場理解與意識：

儘管記憶體分析有許多好處，但潛在使用者仍然沒有完全理解記憶體分析，並且對記憶體分析的認知度較低。關於其成本和複雜性的迷思可能會阻礙市場擴張。

替代技術的衝突：

許多技術在資料分析產業中競爭，包括基於雲端的分析、機器學習解決方案和傳統資料倉儲。記憶體分析的成長可能會受到各種替代技術的競爭的限制。

目錄

第1章 記憶體內分析的全球市場:簡介

  • 市場概要
  • 調查範圍
  • 前提條件

第2章 摘要整理

第3章 VERIFIED MARKET RESEARCH的調查手法

  • 資料探勘
  • 檢驗
  • 主要採訪
  • 資料來源一覽

第4章 記憶體內分析的全球市場展望

  • 概要
  • 市場動態
    • 促進因素
    • 阻礙因素
    • 機會
  • 波特的五力分析
  • 價值鏈分析

第5章 記憶體內分析的全球市場:各零件

  • 概要
  • 服務
  • 軟體

第6章 記憶體內分析的全球市場:各組織規模

  • 概要
  • 中小企業(SMB)
  • 大企業

第7章 記憶體內分析的全球市場:各業界

  • 概要
  • 通訊·IT
  • 銀行，金融服務，保險(BFSI)
  • 醫療保健，生命科學
  • 製造，政府，防衛
  • 能源·公共產業
  • 零售·電子商務
  • 運輸·物流
  • 媒體·娛樂
  • 其他

第8章 記憶體內分析的全球市場:各用途

  • 概要
  • 風險管理和詐欺偵測
  • 銷售和行銷的最佳化
  • 財務管理
  • 供應鏈的最佳化
  • 預測的資產管理
  • 產品·流程管理
  • 其他

第9章 記憶體內分析的全球市場:各地區

  • 概要
  • 北美
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 法國
    • 其他歐洲
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 其他亞太地區
  • 全球其他地區
    • 南美
    • 中東·非洲

第10章 全球記憶體內分析市場競爭情形

  • 概要
  • 各公司的市場排行榜
  • 主要的發展策略

第11章 企業簡介

  • SAP(Germany)
  • Oracle(US)
  • Kognitio(UK)
  • MicroStrategy(US)
  • SAS Institute(US)
  • ActiveViam(UK)
  • IBM(US)
  • Information Builders(US)
  • Hitachi(Japan)
  • Software AG(Germany)

第12章 主要發展

  • 產品的上市/開發
  • 合併和收購
  • 事業擴大
  • 夥伴關係和合作

第13章 附錄

  • 相關調查
簡介目錄
Product Code: 4733

In-Memory Analytics Market Size And Forecast

In Memory Analytics Market size was valued at USD 2.98 Billion in 2023 and is projected to reach USD 6.93 Billion by 2030 , growing at a CAGR of 18.38% during the forecast period 2024-2030.

Global In-Memory Analytics Market Drivers

The market drivers for the In-Memory Analytics Market can be influenced by various factors. These may include: Accelerating Business Decisions: Real-time data processing is becoming more and more necessary for businesses in order to obtain fast insights and make choices. Adoption of in-memory analytics is fueled by its ability to analyze data more quickly than with conventional disk-based techniques.

Big Data Growth:

As big data continues to expand exponentially, businesses are under pressure to come up with faster, more effective methods for analyzing vast amounts of data. Big data management requires speed and scalability, which in-memory analytics offers.

Technological Advancements:

In-memory analytics is now more affordable and widely available thanks to improvements in technology, including lower RAM prices and faster computation.

Growing Use of Business Intelligence (BI) Tools:

Organizations are utilizing BI tools more and more, which make use of in-memory analytics to improve reporting, data visualization, and decision-making.

Cloud Adoption:

As cloud platforms offer the required scale and infrastructure, the move to cloud computing has made it easier to implement in-memory analytics solutions.

Competitive Advantage:

By boosting their data processing speeds and enabling more flexible and knowledgeable business strategies, organizations are implementing in-memory analytics to obtain a competitive advantage.

Integration with IoT:

As the Internet of Things (IoT) grows, enormous volumes of data are produced that require processing in real time. Efficient analysis of Internet of Things data requires in-memory analytics.

Enhancing Predictive Analytics:

Predictive analytics is becoming more and more in demand as a means of predicting patterns and behavior. Predictive models perform better when using in-memory analytics since it allows for faster data processing.

Global In-Memory Analytics Market Restraints

High Expenses of Implementation:

Implementing in-memory analytics solutions comes with a hefty upfront investment. This covers the price of specialized software, hardware with lots of RAM, and integrating these systems with the current IT infrastructure. For small and medium-sized businesses (SMEs), these expenses could be unaffordable.

Integration Complexity:

It might be difficult and time-consuming to integrate in-memory analytics with current legacy systems and databases. Organizations frequently face difficulties because seamless integration requires specific skills and experience.

Data Security Issues:

As in-memory analytics requires managing massive amounts of data in real-time, protecting the privacy and security of such data is crucial. Organizations may be discouraged from implementing these solutions by the possibility of data breaches and the requirement for strict security protocols.

Problems with Scalability:

Although in-memory analytics provides fast data processing, scaling these systems to manage large amounts of data can be expensive and difficult. The scalability of these systems may be impacted by the RAM's hardware constraints.

Hardware Dependency

: Large RAM sizes, in particular, are essential for high-performance hardware to be available for in-memory analytics. This dependence may affect the system's dependability by causing problems with maintenance and hardware malfunctions.

Absence of Skilled Workers:

Adoption of in-memory analytics necessitates knowledgeable experts who comprehend the technology as well as how business contexts apply it. The adoption and efficient use of these solutions may be hampered by the lack of such qualified workers.

Concerns about Regulation and Compliance:

Regulations pertaining to data processing, storage, and privacy differ between sectors and geographical areas. It can be difficult to navigate these rules, and doing so may prevent the use of in-memory analytics tools in some markets.

Understanding and Perception of the Market:

Potential users still don't fully comprehend or are aware of in-memory analytics, despite its benefits. Myths regarding its expense and complexity may impede the expansion of the market.

Alternative Technologies' Competition:

Numerous technologies, including cloud-based analytics, machine learning solutions, and traditional data warehousing, are competing in the data analytics industry. The growth of in-memory analytics may be limited by the competition from various alternatives.

Global In-Memory Analytics Market Segmentation Analysis

The Global In-Memory Analytics Market is segmented on the basis of Components, Applications, Organizational Size, Industry Vertical, and Geography.

In-Memory Analytics Market, By Components

  • Softwares
  • Services

Based on Components, the in-memory analytics market is bifurcated into Services and Software. The Software segment is anticipated to dominate the global market during the forecasted period, attributing to the factors such as increased speed, quick data analysis, and achieving real-time intuitions from the stored data. The reduced prices in RAM and technological advancements in computing power will help the Software segment prosper during the forecasted period.

In-Memory Analytics Market, By Organization Size

  • Small and Medium-Sized Businesses (SMBs)
  • Large Enterprises

Based on Organization Size, the in-memory analytics market is bifurcated into Small and Medium-Sized Businesses (SMBs) and Large Enterprises. Small and Medium-Sized Businesses are anticipated to witness the highest CAGR growth during the forecast period. It is due to small enterprises' advancement from outdated analytical tools to advanced in-memory analytical tools. The intense competition among the business further aids the segment growth.

In-Memory Analytics Market, By Industry Vertical

  • Banking, Financial Services, and Insurance (BFSI)
  • Telecommunications and IT
  • Retail and eCommerce
  • Healthcare and Life sciences
  • Manufacturing, Government, and Defense
  • Energy and Utilities
  • Media and Entertainment
  • Transportation and logistics
  • Others

Based on Industry Vertical, The In-Memory Analytics Market is bifurcated into Banking, Financial Services, and Insurance (BFSI), Telecommunications and IT, Retail and eCommerce, Healthcare and Life sciences, Manufacturing, Government, and Defense, Energy and Utilities, Media and Entertainment, Transportation and logistics, and Others. Banking, Financial Services, and Insurance (BFSI) will dominate the market during the forecasted period. It is because BSFI assembles large amounts of data from many sources; in-memory analytics also allows the user to manage fraud detection in real time, easing the user to make quick decisions.

In-Memory Analytics Market, By Applications

  • Risk management and fraud detection
  • Sales and marketing optimization
  • Financial management
  • Supply chain optimization
  • Predictive asset management
  • Product and process management
  • Others

Based on Applications, The In-Memory Analytics Market is bifurcated into Risk management and fraud detection, Sales and marketing optimization, Financial Management, Supply chain optimization, Predictive asset management, Product and process management, and Others. The Risk Management and Fraud Detection segment will lead the market during the forecast period. The domination can be attributed to the rapid risk intelligence capabilities to fight financial and operational risks. The companies use advanced analytical tools to identify, monitor, analyze, address, and quickly recuperate from significant risk events.

In-Memory Analytics Market, By Geography

  • North America
  • Europe
  • Asia Pacific
  • Rest of the world
  • On the basis of Geography, The Global In-Memory Analytics Market is classified into North America, Europe, Asia Pacific, and the Rest of the world. North America is anticipated to lead the global market for in-memory analytics, owing to the massive number of in-memory analytics vendors in the region. The early adoption of new technologies and the increased focus on data analytics by several leading organizations further aid the market growth in the given area.

Key Players

  • The major players in the In-Memory Analytics Market are:
  • Oracle
  • SAP
  • MicroStrategy
  • ActiveViam
  • Information Builders
  • Hitachi
  • International Business Machines
  • Software
  • SAS Institute

TABLE OF CONTENTS

1 INTRODUCTION TO THE GLOBAL IN-MEMORY ANALYTICS MARKET

  • 1.1 Overview of the Market
  • 1.2 Scope of Report
  • 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

  • 3.1 Data Mining
  • 3.2 Validation
  • 3.3 Primary Interviews
  • 3.4 List of Data Sources

4 GLOBAL IN-MEMORY ANALYTICS MARKET OUTLOOK

  • 4.1 Overview
  • 4.2 Market Dynamics
    • 4.2.1 Drivers
    • 4.2.2 Restraints
    • 4.2.3 Opportunities
  • 4.3 Porter's Five Force Model
  • 4.4 Value Chain Analysis

5 GLOBAL IN-MEMORY ANALYTICS MARKET, BY COMPONENTS

  • 5.1 Overview
  • 5.2 Services
  • 5.3 Softwares

6 GLOBAL IN-MEMORY ANALYTICS MARKET, BY ORGANIZATION SIZE

  • 6.1 Overview
  • 6.2 Small and Medium-Sized Businesses (SMBs)
  • 6.3 Large Enterprises

7 GLOBAL IN-MEMORY ANALYTICS MARKET, BY INDUSTRY VERTICAL

  • 7.1 Overview
  • 7.2 Telecommunications and IT
  • 7.3 Banking, Financial Services, and Insurance (BFSI)
  • 7.4 Healthcare and Life sciences
  • 7.5 Manufacturing, Government, and Defense
  • 7.6 Energy and Utilities
  • 7.7 Retail and eCommerce
  • 7.8 Transportation and logistics
  • 7.9 Media and Entertainment
  • 7.10 Others

8 GLOBAL IN-MEMORY ANALYTICS MARKET, BY APPLICATION

  • 8.1 Overview
  • 8.2 Risk management and fraud detection
  • 8.3 Sales and marketing optimization
  • 8.4 Financial management
  • 8.5 Supply chain optimization
  • 8.6 Predictive asset management
  • 8.7 Product and process management
  • 8.8 Others

9 GLOBAL IN-MEMORY ANALYTICS MARKET, BY GEOGRAPHY

  • 9.1 Overview
  • 9.2 North America
    • 9.2.1 The US.
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 The UK.
    • 9.3.3 France
    • 9.3.4 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 Japan
    • 9.4.3 India
    • 9.4.4 Rest of Asia Pacific
  • 9.5 Rest of the World
    • 9.5.1 Latin America
    • 9.5.2 The Middle East and Africa

10 GLOBAL IN-MEMORY ANALYTICS MARKET COMPETITIVE LANDSCAPE

  • 10.1 Overview
  • 10.2 Company Market Ranking
  • 10.3 Key Development Strategies

11 COMPANY PROFILES

  • 11.1 SAP (Germany)
    • 11.1.1 Overview
    • 11.1.2 Financial Performance
    • 11.1.3 Product Outlook
    • 11.1.4 Key Developments
  • 11.2 Oracle (US)
    • 11.2.1 Overview
    • 11.2.2 Financial Performance
    • 11.2.3 Product Outlook
    • 11.2.4 Key Developments
  • 11.3 Kognitio (UK)
    • 11.3.1 Overview
    • 11.3.2 Financial Performance
    • 11.3.3 Product Outlook
    • 11.3.4 Key Developments
  • 11.4 MicroStrategy (US)
    • 11.4.1 Overview
    • 11.4.2 Financial Performance
    • 11.4.3 Product Outlook
    • 11.4.4 Key Developments
  • 11.5 SAS Institute (US)
    • 11.5.1 Overview
    • 11.5.2 Financial Performance
    • 11.5.3 Product Outlook
    • 11.5.4 Key Developments
  • 11.6 ActiveViam (UK)
    • 11.6.1 Overview
    • 11.6.2 Financial Performance
    • 11.6.3 Product Outlook
    • 11.6.4 Key Development
  • 11.7 IBM (US)
    • 11.7.1 Overview
    • 11.7.2 Financial Performance
    • 11.7.3 Product Outlook
    • 11.7.4 Key Developments
  • 11.8 Information Builders (US)
    • 11.8.1 Overview
    • 11.8.2 Financial Performance
    • 11.8.3 Product Outlook
    • 11.8.4 Key Developments
  • 11.9 Hitachi (Japan)
    • 11.9.1 Overview
    • 11.9.2 Financial Performance
    • 11.9.3 Product Outlook
    • 11.9.4 Key Development
  • 11.10 Software AG (Germany)
    • 11.10.1 Overview
    • 11.10.2 Financial Performance
    • 11.10.3 Product Outlook
    • 11.10.4 Key Development

12 KEY DEVELOPMENTS

  • 12.1 Product Launches/Developments
  • 12.2 Mergers and Acquisitions
  • 12.3 Business Expansions
  • 12.4 Partnerships and Collaborations

13 Appendix

  • 13.1 Related Research