데이터 레이크 시장 보고서 : 컴포넌트, 도입 형태, 조직 규모, 비즈니스 펑션, 최종 용도 산업, 지역별(2024-2032년)

The global data lakes market size reached US$ 12.0 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 78.8 Billion by 2032, exhibiting a growth rate (CAGR) of 22.6% during 2024-2032. The rising number of businesses concerning the management of large amounts of digital data is bolstering the market.

Data Lakes Market Analysis:

• Major Market Drivers: The inflating need for proactively maintaining devices and making informed decisions is one of the key trends bolstering the market.
• Key Market Trends: Extensive applications in the healthcare industry to design products and perform genomic research are among the primary trends positively influencing the market.
• Competitive Landscape: Some of the prominent players in the global market include Amazon Web Services Inc. (Amazon.com Inc), Atos SE, Capgemini, Cloudera Inc., Dell Technologies Inc., Google LLC (Alphabet Inc.), Hewlett Packard Enterprise Development LP, International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, SAP SE, SAS Institute Inc., Snowflake Inc., Tata Consultancy Services Limited, and Teradata Corporation, among many others.
• Geographical Trends: The widespread integration of customer relationship management (CRM) platforms with social media analytics is propelling the market in North America. Besides this, the rising focus of key players on reducing operational costs is also bolstering the market in Asia Pacific. On the other hand, extensive investments in R&D activities will continue to catalyze the market in Europe over the forecasted period.
• Challenges and Opportunities: One of the limitations hindering the market is the lack of proper governance. However, the implementation of robust data management practices is expected to catalyze the market in the coming years.

Data Lakes Market Trends:

Rising Integration of AI

One of the key factors bolstering the market is the growing integration of AI and ML, which can extract deeper insights and predictive analytics from data. Moreover, AI-powered data lakes can automate data classification, anomaly detection, and pattern recognition. Companies like Databricks and IBM are leading this trend by offering AI and ML capabilities integrated with their data lake solutions. For instance, in June 2024, Fivetran, a company that helps enterprises build their data pipelines, announced the general availability of its newest product, the Fivetran Managed Data Lake Service, which aims to remove the repetitive work of managing data lakes by automating and streamlining it for clients.

Increasing Emphasis on Data Governance

The growing focus on data governance and security is bolstering the market. As organizations store vast amounts of sensitive data, thereby ensuring its confidentiality, integrity, and compliance with regulatory requirements becomes paramount. Effective data governance frameworks help manage metadata, data quality, and lineage, thereby providing transparency and control over data assets. For instance, in July 2024, a research team at Flinders University introduced an integrated and AI-driven public health and clinical data repository in Australia for public health surveillance and emergency response.

Growing Multi-cloud Strategies

Multi-cloud strategies usually involve using multiple cloud providers to avoid vendor lock-in and enhance redundancy. This approach also provides organizations with the agility to distribute workloads based on specific needs and leverage best-of-breed services from numerous vendors. For example, a company might use Google Cloud for its advanced AI capabilities while relying on AWS for its extensive ecosystem of data analytics tools. Moreover, vendors like Snowflake and Cloudera are facilitating these strategies by offering platforms that seamlessly integrate with several cloud and on-premises infrastructures.

Global Data Lakes Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the market, along with the data lakes market forecast at the global, regional, and country levels for 2024-2032. Our report has categorized the market based on the component, deployment mode, organization size, business function, and end use industry.

Breakup by Component:

• Solutions
  • Data Discovery
  • Data Integration and Management
  • Data Lake Analytics
  • Data Visualization
• Services
  • Managed Services
  • Professional Services

The report has provided a detailed breakup and analysis of the market based on the component. This includes solutions (data discovery, data integration and management, data lake analytics, and data visualization) and services (managed services and professional services).

The solutions segment includes key areas such as data discovery, data integration and management, data lake analytics, and data visualization. Data discovery tools help organizations identify and understand their data assets, while data integration and management solutions streamline the process of consolidating disparate data sources. Data lake analytics enable the processing and analysis of large datasets to extract valuable insights, and data visualization tools facilitate the representation of data in graphical formats for better comprehension and decision-making. The services segment is divided into managed services and professional services. Managed services offer ongoing support and maintenance of data lake infrastructure, ensuring optimal performance and reliability. Professional services provide specialized expertise, including consulting, implementation, and training, to help organizations effectively deploy and utilize data lake solutions. This detailed segmentation underscores the diverse range of components driving the data lakes market and their critical roles in enabling data-driven business strategies.

Breakup by Deployment Mode:

• On-premises
• Cloud-based

The report has provided a detailed breakup and analysis of the market based on the deployment mode. This includes on-premises and cloud-based.

On-premises data lakes involve deploying the infrastructure within an organization's own data centers, providing complete control over data security, customization, and compliance with internal policies. Industries particularly favor this mode with stringent regulatory requirements, such as finance and healthcare. Conversely, cloud-based data lakes, hosted on platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, offer scalability, flexibility, and cost-efficiency. They enable organizations to handle massive data volumes without significant upfront investment in physical infrastructure.

Breakup by Organization Size:

• Small and Medium-sized Enterprises
• Large Enterprises

The report has provided a detailed breakup and analysis of the market based on the organization size. This includes small and medium-sized enterprises and large enterprises.

For SMEs, data lakes offer a cost-effective solution to manage and analyze large datasets, helping these organizations gain insights without the need for extensive IT infrastructure. Solutions tailored for SMEs typically emphasize ease of use, scalability, and integration with existing systems to support their growth and innovation needs. On the other hand, large enterprises benefit from data lakes' ability to handle vast amounts of data from diverse sources, facilitating complex analytics, machine learning, and real-time data processing. These enterprises often require advanced features like robust security, compliance, and customization to meet their extensive operational demands. By segmenting the market based on organization size, the report highlights the distinct needs and advantages of data lakes for both SMEs and large enterprises, reflecting their critical role in enhancing data-driven decision-making across different business scales.

Breakup by Business Function:

• Marketing
• Sales
• Operations
• Finance
• Human Resources

The report has provided a detailed breakup and analysis of the market based on the business function. This includes marketing, sales, operations, finance, and human resources.

In marketing, data lakes facilitate comprehensive customer insights, enabling targeted campaigns and personalized customer experiences through the integration of vast amounts of behavioral and demographic data. For sales, data lakes enhance performance tracking, forecasting, and customer relationship management by consolidating data from various touchpoints. In operations, data lakes improve efficiency and decision-making by providing real-time analytics and process optimization insights. The finance function benefits from data lakes by gaining accurate financial reporting, risk management, and fraud detection capabilities through the aggregation and analysis of transactional and historical data. In human resources, data lakes support talent management, employee engagement, and workforce analytics by integrating data from recruitment, performance evaluations, and employee feedback. By segmenting the market based on business function, the report underscores the versatile applications of data lakes in driving strategic decisions and operational excellence across different organizational domains.

Breakup by End Use Industry:

• BFSI
• IT and Telecom
• Retail and E-Commerce
• Healthcare and Life Sciences
• Manufacturing
• Energy and Utilities
• Media and Entertainment
• Government
• Others

The report has provided a detailed breakup and analysis of the market based on the end use industry. This includes BFSI, IT and telecom, retail and e-commerce, healthcare and life sciences, manufacturing, energy and utilities, media and entertainment, government, and others.

In the BFSI sector, data lakes enable enhanced fraud detection, risk management, and customer analytics by consolidating vast amounts of transactional data. The IT and telecom industry leverages data lakes for network optimization, customer service improvements, and big data analytics. Retail and e-commerce businesses use data lakes to gain insights into customer behavior, inventory management, and personalized marketing. In healthcare and life sciences, data lakes support clinical data analysis, patient care optimization, and research. The manufacturing sector benefits from improved supply chain management, predictive maintenance, and quality control. Energy and utilities companies use data lakes for operational efficiency, predictive maintenance, and energy consumption analysis. Media and entertainment industries utilize data lakes for audience analytics, content personalization, and trend analysis. Government agencies adopt data lakes for improved public service delivery, policy-making, and data transparency. This is expanding the data lakes market share.

Breakup by Region:

• North America
  • United States
  • Canada
• Asia-Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Indonesia
  • Others
• Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
  • Russia
  • Others
• Latin America
  • Brazil
  • Mexico
  • Others
• Middle East and Africa

The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa.

North America, particularly the United States, leads the market due to its advanced technological infrastructure, high adoption rates of big data solutions, and the presence of major technology firms like AWS, Microsoft, and Google. The Asia Pacific region is experiencing rapid market expansion driven by increasing digital transformation initiatives, a burgeoning IT sector, and significant investments in data analytics across countries like China, India, and Japan. Europe follows closely, with a strong emphasis on data privacy and regulatory compliance, which fuels the demand for sophisticated data management solutions. In Latin America, growing awareness of the benefits of big data and rising investments in technology infrastructure are propelling market growth, particularly in countries like Brazil and Mexico. The Middle East and Africa region, although at an earlier stage of adoption, is witnessing increasing interest in data lakes due to emerging smart city projects, digital initiatives, and investments in IT infrastructure.

Competitive Landscape:

The market research report has provided a comprehensive analysis of the competitive landscape. Detailed profiles of all major market companies have also been provided. Some of the key players in the market include:

• Amazon Web Services Inc. (Amazon.com Inc)
• Atos SE
• Capgemini
• Cloudera Inc.
• Dell Technologies Inc.
• Google LLC (Alphabet Inc.)
• Hewlett Packard Enterprise Development LP
• International Business Machines Corporation
• Microsoft Corporation
• Oracle Corporation
• SAP SE
• SAS Institute Inc.
• Snowflake Inc.
• Tata Consultancy Services Limited
• Teradata Corporation

(Please note that this is only a partial list of the key players, and the complete list is provided in the report.)

Data Lakes Market Recent Developments:

• July 2024: A research team at Flinders University introduced an integrated and AI-driven public health and clinical data repository in Australia for public health surveillance and emergency response.
• June 2024: Fivetran, a company that helps enterprises build their data pipelines, announced the general availability of its newest product, the Fivetran Managed Data Lake Service, which aims to remove the repetitive work of managing data lakes by automating and streamlining it for clients.
• February 2024: The Huawei Product and Solution launched three innovative solutions aimed at helping carriers worldwide build leading data infrastructure.

Key Questions Answered in This Report:

• How has the global data lakes market performed so far, and how will it perform in the coming years?
• What has been the impact of COVID-19 on the global data lakes market?
• What are the key regional markets?
• What is the breakup of the market based on the component?
• What is the breakup of the market based on the deployment mode?
• What is the breakup of the market based on the organization size?
• What is the breakup of the market based on the business function?
• What is the breakup of the market based on the end use industry?
• What are the various stages in the value chain of the industry?
• What are the key driving factors and challenges in the industry?
• What is the structure of the global data lakes market, and who are the key players?
• What is the degree of competition in the industry?

Table of Contents

1 Preface

2 Scope and Methodology

• 2.1 Objectives of the Study
• 2.2 Stakeholders
• 2.3 Data Sources
  • 2.3.1 Primary Sources
  • 2.3.2 Secondary Sources
• 2.4 Market Estimation
  • 2.4.1 Bottom-Up Approach
  • 2.4.2 Top-Down Approach
• 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

• 4.1 Overview
• 4.2 Key Industry Trends

5 Global Data Lakes Market

• 5.1 Market Overview
• 5.2 Market Performance
• 5.3 Impact of COVID-19
• 5.4 Market Forecast

6 Market Breakup by Component

• 6.1 Solutions
  • 6.1.1 Market Trends
  • 6.1.2 Key Segments
    • 6.1.2.1 Data Discovery
    • 6.1.2.2 Data Integration and Management
    • 6.1.2.3 Data Lake Analytics
    • 6.1.2.4 Data Visualization
  • 6.1.3 Market Forecast
• 6.2 Services
  • 6.2.1 Market Trends
  • 6.2.2 Key Segments
    • 6.2.2.1 Managed Services
    • 6.2.2.2 Professional Services
  • 6.2.3 Market Forecast

7 Market Breakup by Deployment Mode

• 7.1 On-premises
  • 7.1.1 Market Trends
  • 7.1.2 Market Forecast
• 7.2 Cloud-based
  • 7.2.1 Market Trends
  • 7.2.2 Market Forecast

8 Market Breakup by Organization Size

• 8.1 Small and Medium-sized Enterprises
  • 8.1.1 Market Trends
  • 8.1.2 Market Forecast
• 8.2 Large Enterprises
  • 8.2.1 Market Trends
  • 8.2.2 Market Forecast

9 Market Breakup by Business Function

• 9.1 Marketing
  • 9.1.1 Market Trends
  • 9.1.2 Market Forecast
• 9.2 Sales
  • 9.2.1 Market Trends
  • 9.2.2 Market Forecast
• 9.3 Operations
  • 9.3.1 Market Trends
  • 9.3.2 Market Forecast
• 9.4 Finance
  • 9.4.1 Market Trends
  • 9.4.2 Market Forecast
• 9.5 Human Resources
  • 9.5.1 Market Trends
  • 9.5.2 Market Forecast

10 Market Breakup by End Use Industry

• 10.1 BFSI
  • 10.1.1 Market Trends
  • 10.1.2 Market Forecast
• 10.2 IT and Telecom
  • 10.2.1 Market Trends
  • 10.2.2 Market Forecast
• 10.3 Retail and E-Commerce
  • 10.3.1 Market Trends
  • 10.3.2 Market Forecast
• 10.4 Healthcare and Life Sciences
  • 10.4.1 Market Trends
  • 10.4.2 Market Forecast
• 10.5 Manufacturing
  • 10.5.1 Market Trends
  • 10.5.2 Market Forecast
• 10.6 Energy and Utilities
  • 10.6.1 Market Trends
  • 10.6.2 Market Forecast
• 10.7 Media and Entertainment
  • 10.7.1 Market Trends
  • 10.7.2 Market Forecast
• 10.8 Government
  • 10.8.1 Market Trends
  • 10.8.2 Market Forecast
• 10.9 Others
  • 10.9.1 Market Trends
  • 10.9.2 Market Forecast

11 Market Breakup by Region

• 11.1 North America
  • 11.1.1 United States
    • 11.1.1.1 Market Trends
    • 11.1.1.2 Market Forecast
  • 11.1.2 Canada
    • 11.1.2.1 Market Trends
    • 11.1.2.2 Market Forecast
• 11.2 Asia-Pacific
  • 11.2.1 China
    • 11.2.1.1 Market Trends
    • 11.2.1.2 Market Forecast
  • 11.2.2 Japan
    • 11.2.2.1 Market Trends
    • 11.2.2.2 Market Forecast
  • 11.2.3 India
    • 11.2.3.1 Market Trends
    • 11.2.3.2 Market Forecast
  • 11.2.4 South Korea
    • 11.2.4.1 Market Trends
    • 11.2.4.2 Market Forecast
  • 11.2.5 Australia
    • 11.2.5.1 Market Trends
    • 11.2.5.2 Market Forecast
  • 11.2.6 Indonesia
    • 11.2.6.1 Market Trends
    • 11.2.6.2 Market Forecast
  • 11.2.7 Others
    • 11.2.7.1 Market Trends
    • 11.2.7.2 Market Forecast
• 11.3 Europe
  • 11.3.1 Germany
    • 11.3.1.1 Market Trends
    • 11.3.1.2 Market Forecast
  • 11.3.2 France
    • 11.3.2.1 Market Trends
    • 11.3.2.2 Market Forecast
  • 11.3.3 United Kingdom
    • 11.3.3.1 Market Trends
    • 11.3.3.2 Market Forecast
  • 11.3.4 Italy
    • 11.3.4.1 Market Trends
    • 11.3.4.2 Market Forecast
  • 11.3.5 Spain
    • 11.3.5.1 Market Trends
    • 11.3.5.2 Market Forecast
  • 11.3.6 Russia
    • 11.3.6.1 Market Trends
    • 11.3.6.2 Market Forecast
  • 11.3.7 Others
    • 11.3.7.1 Market Trends
    • 11.3.7.2 Market Forecast
• 11.4 Latin America
  • 11.4.1 Brazil
    • 11.4.1.1 Market Trends
    • 11.4.1.2 Market Forecast
  • 11.4.2 Mexico
    • 11.4.2.1 Market Trends
    • 11.4.2.2 Market Forecast
  • 11.4.3 Others
    • 11.4.3.1 Market Trends
    • 11.4.3.2 Market Forecast
• 11.5 Middle East and Africa
  • 11.5.1 Market Trends
  • 11.5.2 Market Breakup by Country
  • 11.5.3 Market Forecast

12 SWOT Analysis

• 12.1 Overview
• 12.2 Strengths
• 12.3 Weaknesses
• 12.4 Opportunities
• 12.5 Threats

13 Value Chain Analysis

14 Porters Five Forces Analysis

• 14.1 Overview
• 14.2 Bargaining Power of Buyers
• 14.3 Bargaining Power of Suppliers
• 14.4 Degree of Competition
• 14.5 Threat of New Entrants
• 14.6 Threat of Substitutes

15 Price Analysis

16 Competitive Landscape

• 16.1 Market Structure
• 16.2 Key Players
• 16.3 Profiles of Key Players
  • 16.3.1 Amazon Web Services Inc. (Amazon.com Inc)
    • 16.3.1.1 Company Overview
    • 16.3.1.2 Product Portfolio
    • 16.3.1.3 SWOT Analysis
  • 16.3.2 Atos SE
    • 16.3.2.1 Company Overview
    • 16.3.2.2 Product Portfolio
    • 16.3.2.3 Financials
    • 16.3.2.4 SWOT Analysis
  • 16.3.3 Capgemini
    • 16.3.3.1 Company Overview
    • 16.3.3.2 Product Portfolio
    • 16.3.3.3 Financials
    • 16.3.3.4 SWOT Analysis
  • 16.3.4 Cloudera Inc.
    • 16.3.4.1 Company Overview
    • 16.3.4.2 Product Portfolio
    • 16.3.4.3 Financials
  • 16.3.5 Dell Technologies Inc.
    • 16.3.5.1 Company Overview
    • 16.3.5.2 Product Portfolio
    • 16.3.5.3 Financials
    • 16.3.5.4 SWOT Analysis
  • 16.3.6 Google LLC (Alphabet Inc.)
    • 16.3.6.1 Company Overview
    • 16.3.6.2 Product Portfolio
    • 16.3.6.3 SWOT Analysis
  • 16.3.7 Hewlett Packard Enterprise Development LP
    • 16.3.7.1 Company Overview
    • 16.3.7.2 Product Portfolio
    • 16.3.7.3 Financials
    • 16.3.7.4 SWOT Analysis
  • 16.3.8 International Business Machines Corporation
    • 16.3.8.1 Company Overview
    • 16.3.8.2 Product Portfolio
    • 16.3.8.3 Financials
    • 16.3.8.4 SWOT Analysis
  • 16.3.9 Microsoft Corporation
    • 16.3.9.1 Company Overview
    • 16.3.9.2 Product Portfolio
    • 16.3.9.3 Financials
    • 16.3.9.4 SWOT Analysis
  • 16.3.10 Oracle Corporation
    • 16.3.10.1 Company Overview
    • 16.3.10.2 Product Portfolio
    • 16.3.10.3 Financials
    • 16.3.10.4 SWOT Analysis
  • 16.3.11 SAP SE
    • 16.3.11.1 Company Overview
    • 16.3.11.2 Product Portfolio
    • 16.3.11.3 Financials
    • 16.3.11.4 SWOT Analysis
  • 16.3.12 SAS Institute Inc.
    • 16.3.12.1 Company Overview
    • 16.3.12.2 Product Portfolio
    • 16.3.12.3 SWOT Analysis
  • 16.3.13 Snowflake Inc.
    • 16.3.13.1 Company Overview
    • 16.3.13.2 Product Portfolio
    • 16.3.13.3 Financials
  • 16.3.14 Tata Consultancy Services Limited
    • 16.3.14.1 Company Overview
    • 16.3.14.2 Product Portfolio
    • 16.3.14.3 Financials
    • 16.3.14.4 SWOT Analysis
  • 16.3.15 Teradata Corporation
    • 16.3.15.1 Company Overview
    • 16.3.15.2 Product Portfolio
    • 16.3.15.3 Financials
    • 16.3.15.4 SWOT Analysis