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市场调查报告书
商品编码
1645135

资料湖 -市场占有率分析、产业趋势与统计、成长预测（2025-2030）

Data Lakes - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 100 Pages | 商品交期: 2-3个工作天内

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简介目录

预测期内，资料湖市场预计将以 22.40% 的复合年增长率成长。

资料湖-市场-IMG1

资料湖是一个中央储存库，资料存储大量资料、资料、半结构化和非结构化资料，对于希望从资料中获取有价值见解的组织来说，它是一项宝贵的资产。

关键亮点

  • 巨量资料的兴起和对高级分析解决方案的需求增加了对资料湖的需求。公司希望有效率地储存和处理大量不同的资料。
  • 由于物联网 (IoT) 的采用而导致的资料快速成长是资料湖市场的主要驱动力。物联网设备会产生大量资料，通常是即时的。资料湖可以处理大量资料涌入，而不会影响效能。
  • 资料湖使组织能够利用高级分析功能在当今资料主导的商业环境中获得竞争优势。随着企业不断认识到资料主导洞察的重要性，对具有高级分析功能的资料湖的需求预计将会增长。
  • 缓慢的入职和资料整合挑战是限制市场资料湖成长和采用的主要因素。将来自各种来源的资料整合到资料湖中是一项复杂且耗时的作业。组织可能以不同的格式、资料库和系统储存资料，需要付出巨大的努力来协调和有效地整合资料。

资料湖市场趋势

BFSI 终端用户部分预计将占据主要市场占有率

  • BFSI 部门产生和处理大量资料，包括客户交易资料、帐户资讯、金融市场资料、保险索赔、信用评分等。资料湖为 BFSI 组织提供了可扩展且灵活的解决方案来管理、处理和分析大量不同的资料。
  • 资料湖使 BFSI 组织能够整合和分析来自多个来源的客户资料，包括银行交易、信用卡使用、线上交易等。这种统一的视图可帮助您深入了解客户的行为、偏好和需求，从而支援个人化的定位和行销。
  • 资料湖是各种类型资料的集中存储，包括交易资料、使用者行为模式、历史记录等。透过应用进阶分析和机器学习演算法，BFSI 组织可以更有效地侦测和防止诈欺活动。
  • 据印度储备银行 (RBI) 称，2023 财年，印度全国发生了 13,000 多起银行诈骗案件。这比上年度有所增长，并扭转了过去十年的趋势。银行诈骗总额从 1.38 兆印度卢比（170 亿美元）下降到 3,020 亿印度卢比（36.8 亿美元）。
  • BFSI 部门面临各种风险，包括信用风险、市场风险和营运风险。资料湖使银行和保险公司能够汇总和分析与风险相关的资料，以便做出明智的决策、管理风险敞口并遵守监管要求。
  • 许多公司正在推出和开发银行和金融解决方案。 2022 年 9 月，为 Web3 公司创建了第一个金融资料湖的 Tres 宣布已在由 Bold Start Ventures主导的种子轮融资中筹集了 760 万美元，其他参投方包括 F2、Mantis、New Form、The Chainsmokers、Blockdaemon Ventures、Kenetic 和 Alchemy。

预计北美将占据较大的市场占有率

  • 北美是资料湖采用的主要地区之一，其推动因素有很多，包括大量精通技术的行业、云端基础设施以及对资料主导决策的高度关注。
  • 北美是许多资料密集型行业的所在地，包括 IT、通讯、BFSI、医疗保健、零售和製造业。这些产业产生的大量资料正在推动对资料湖作为可扩展且灵活的资料储存和处理解决方案的需求。
  • 云端运算在该地区已十分成熟并被广泛采用。云端基础的资料湖具有许多优势，包括成本效益、可扩展性和易于部署，使其成为各种规模企业的理想选择。
  • 北美公司一直是高阶分析和人工智慧（AI）技术的早期采用者。资料湖为大型多样化资料集提供了集中储存库，为这些资料驱动的应用程式提供了基础。
  • 物联网（IoT）和巨量资料技术的发展正在该地区产生大量不同的资料。资料湖非常适合处理来自物联网设备和巨量资料来源的复杂和大量资料。

资料湖产业概览

资料湖市场由微软公司、亚马逊公司、凯捷公司、甲骨文公司和 Teradata 公司等主要企业细分。市场参与企业正在采取联盟和收购等策略来增强其产品供应并获得可持续的竞争优势。

2024 年 6 月企业资料管道解决方案供应商 Fivetran 宣布其最新产品 Fivetran 託管资料湖服务正式上市。新服务旨在透过自动化和简化流程来消除与管理资料湖相关的重复任务。这使得客户可以专注于使用资料进行产品开发。目前支援Amazon S3、Azure Data Lake Storage（ADLS）、Microsoft OneLake，未来将支援Google Cloud。

2023 年 12 月 Panther Labs 是大规模检测和回应网路安全创新的领导者，宣布了其最新功能：安全资料湖搜寻和 Splunk 整合。这些进步代表着我们在解决当今以云端为中心的世界的安全挑战方面迈出了重要一步。 Panther 整合将现代安全资料湖的成本效益与传统 SIEM 介面的易用性结合在一起。这使安全团队能够识别和应对威胁，为广泛分布的云端操作提供额外的防御层。

其他福利

  • Excel 格式的市场预测 (ME) 表
  • 3 个月的分析师支持

目录

第 1 章 简介

  • 研究假设和市场定义
  • 研究范围

第二章调查方法

第三章执行摘要

第四章 市场洞察

  • 市场概况
  • 产业吸引力-波特五力分析
    • 供应商的议价能力
    • 买家的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争对手之间的竞争
  • 产业价值链分析
  • COVID-19 工业影响评估

第五章 市场动态

  • 市场驱动因素
    • 透过物联网实现资料激增
    • 需要进阶分析
  • 市场限制
    • 资料湖存取和资料整合延迟

第六章 市场细分

  • 透过奉献
    • 解决方案
    • 按服务
  • 按部署
    • 云端基础
    • 本地
  • 按行业
    • 资讯科技/通讯
    • BFSI
    • 医疗
    • 零售
    • 製造业
    • 其他最终用户产业
  • 按地区
    • 北美洲
      • 美国
      • 加拿大
    • 欧洲
      • 英国
      • 德国
      • 法国
      • 义大利
    • 亚洲
      • 中国
      • 日本
      • 印度
    • 澳洲和纽西兰
    • 拉丁美洲
      • 墨西哥
      • 巴西
      • 阿根廷
    • 中东和非洲
      • 阿拉伯聯合大公国
      • 沙乌地阿拉伯
      • 南非

第七章 竞争格局

  • 公司简介
    • Microsoft Corporation
    • Amazon.com Inc.
    • Capgemini SE
    • Oracle Corporation
    • Teradata Corporation
    • SAP SE
    • IBM Corporation
    • Solix Technologies Inc.
    • Informatica Corporation
    • Dell EMC
    • Snowflake Computing Inc.
    • Hitachi Data Systems

第八章投资分析

第九章：市场的未来

简介目录
Product Code: 62344

The Data Lakes Market is expected to register a CAGR of 22.40% during the forecast period.

Data Lakes - Market - IMG1

A data lake is a central repository that stores large volumes of raw, structured, semi-structured, and unstructured data, making it a valuable asset for organizations seeking to extract valuable insights from their data.

Key Highlights

  • The rise of big data and the need for advanced analytics solutions fueled the demand for data lakes. Organizations wanted to store and process vast amounts of diverse data types efficiently.
  • The proliferation of data due to adopting the Internet of Things (IoT) has been a significant driver of the data lakes market. IoT devices generate an enormous volume of data, often in real time. Data lakes can handle this massive influx of data without compromising performance.
  • Data lakes enable organizations to leverage advanced analytics capabilities and gain a competitive advantage in today's data-driven business landscape. As businesses continue to recognize the importance of data-driven insights, the demand for data lakes with advanced analytics features is expected to grow.
  • Slow onboarding and data integration challenges have been significant factors restraining the growth and adoption of data lakes in the market. Integrating data from various sources into a data lake can be complex and time-consuming. Organizations may store data in different formats, databases, and systems, requiring significant effort to harmonize and consolidate the data effectively.

Data Lake Market Trends

BFSI End-user Vertical Segment is Expected to Hold Significant Market Share

  • The BFSI sector generates and handles vast amounts of data, including customer transaction data, account information, financial market data, insurance claims, credit scores, etc. Data lakes provide BSI organizations with a scalable and flexible solution for managing, processing, and analyzing this massive volume of diverse data.
  • Data lakes enable BFSI organizations to consolidate and analyze customer data from multiple sources, such as banking transactions, credit card usage, and online interactions. This consolidated view helps gain valuable insights into customer behavior, preferences, and needs, facilitating personalized, targeted marketing.
  • Data lakes are a central repository for diverse data types, including transactional data, user behavior patterns, and historical records. By applying advanced analytics and machine learning algorithms, BFSI organizations can detect and prevent fraudulent activities more effectively.
  • According to the Reserve Bank of India, In the financial year 2023, the Reserve Bank of India (RBI) reported more than 13 thousand bank fraud cases across India. This was an increase compared to the previous year and turned around the last decade's trend. The total value of bank frauds decreased from INR 1.38 trillion (USD 0.017 trillion) to INR 302 billion (USD 3.68 billion).
  • The BFSI Sector faces various risks, including credit, market, and operational risks. Data lakes allow banks and insurance companies to aggregate and analyze risk-related data to make informed decisions, manage exposures, and comply with regulatory requirements.
  • Many companies are launching and developing banking and finance solutions. In September 2022, Tres, the company that made the first financial data lake for Web3 enterprises, announced that it had raised USD 7.6 million in a seed phase led by bold start ventures, with help from F2, Mantis, New Form, The Chainsmokers, Blockdaemon Ventures, Kenetic, and Alchemy.

North America is Expected to Hold Significant Market Share

  • North America is one of the leading regions in data lake adoption, driven by various factors, including numerous tech-savy industries, cloud infrastructure, and a strong focus on data-driven decision-making.
  • North America has many data-intensive industries, such as information technology, telecom, BFSI, healthcare, retail, and manufacturing. The massive volume of data these industries generate drives the demand for data lakes as a scalable and flexible data storage and processing solution.
  • Cloud computing is well-established and widely adopted in this region. Cloud-based data lakes offer numerous advantages, including cost-efficiency, scalability, and ease of implementation, making them an attractive choice for businesses of all sizes.
  • North American enterprises have been early adopters of advanced analytics and artificial intelligence (AI) technologies. Data lakes provide a foundation for these data-driven applications by offering a centralized repository for diverse and large datasets.
  • The growth of the Internet of Things (IoT) and big data technologies in the region generate massive amounts of diverse data. Data lakes are well suited to handle the complexity and volume of data from IoT devices and big data sources.

Data Lake Industry Overview

The Data Lakes Market is fragmented with major players like Microsoft Corporation, Amazon.com Inc., Capgemini SE, Oracle Corporation, and Teradata Corporation. Players in the market are adopting strategies such as partnerships and acquisitions to enhance their product offerings and gain sustainable competitive advantage.

June 2024: Fivetran, a provider of data pipeline solutions for enterprises, has announced the general availability of its latest product, the Fivetran Managed Data Lake Service. This new service is designed to eliminate the repetitive tasks associated with managing data lakes by automating and streamlining the process. This allows clients to focus on leveraging their data for product development. Currently, the service supports Amazon S3, Azure Data Lake Storage (ADLS), and Microsoft OneLake, with future support for Google Cloud on the roadmap.

December 2023: Panther Labs, a leader in cybersecurity innovation for large-scale detection and response, announced the launch of its latest capabilities: Security Data Lake Search and Splunk Integration. These advancements signify a major step forward in addressing security challenges in today's cloud-centric environment. Panther's integration combines the cost-efficiency of modern security data lakes with the user-friendly nature of traditional SIEM interfaces. This enables security teams to identify and respond to threats, strengthening their defenses for extensive, decentralized cloud operations.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Buyers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitutes
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Industry Value Chain Analysis
  • 4.4 Assessment of Impact of COVID-19 on the Industry

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Proliferation of Data due to the Adoption of IoT
    • 5.1.2 Need for Advanced Analytic Capabilities
  • 5.2 Market Restraints
    • 5.2.1 Slow Onboarding and Data Integration of Data Lakes

6 MARKET SEGMENTATION

  • 6.1 By Offering
    • 6.1.1 Solution
    • 6.1.2 Service
  • 6.2 By Deployment
    • 6.2.1 Cloud-based
    • 6.2.2 On-premise
  • 6.3 By End-user Vertical
    • 6.3.1 IT and Telecom
    • 6.3.2 BFSI
    • 6.3.3 Healthcare
    • 6.3.4 Retail
    • 6.3.5 Manufacturing
    • 6.3.6 Other End-user Verticals
  • 6.4 By Geography
    • 6.4.1 North America
      • 6.4.1.1 United States
      • 6.4.1.2 Canada
    • 6.4.2 Europe
      • 6.4.2.1 United Kingdom
      • 6.4.2.2 Germany
      • 6.4.2.3 France
      • 6.4.2.4 Italy
    • 6.4.3 Asia
      • 6.4.3.1 China
      • 6.4.3.2 Japan
      • 6.4.3.3 India
    • 6.4.4 Australia and New Zealand
    • 6.4.5 Latin America
      • 6.4.5.1 Mexico
      • 6.4.5.2 Brazil
      • 6.4.5.3 Argentina
    • 6.4.6 Middle East and Africa
      • 6.4.6.1 United Arab Emirates
      • 6.4.6.2 Saudi Arabia
      • 6.4.6.3 South Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 Microsoft Corporation
    • 7.1.2 Amazon.com Inc.
    • 7.1.3 Capgemini SE
    • 7.1.4 Oracle Corporation
    • 7.1.5 Teradata Corporation
    • 7.1.6 SAP SE
    • 7.1.7 IBM Corporation
    • 7.1.8 Solix Technologies Inc.
    • 7.1.9 Informatica Corporation
    • 7.1.10 Dell EMC
    • 7.1.11 Snowflake Computing Inc.
    • 7.1.12 Hitachi Data Systems

8 INVESTMENT ANALYSIS

9 FUTURE OF THE MARKET