데이터 웨어하우징 시장 분석 : 제공 내용별, 데이터 유형별, 전개 모델별, 기업 규모별, 최종사용자별, 지역별(2025-2033년)

The global data warehousing market size reached USD 34.5 Billion in 2024. The market is projected to reach USD 75.0 Billion by 2033, exhibiting a growth rate (CAGR) of 8.54% during 2025-2033. North America currently dominates the market on account of the increasing amount of data generated by organizations across the globe. In addition, the rising demand for next-generation BI solutions is catalyzing the overall demand

Global Data Warehousing Market Trends:

Growing Utilization of Artificial Intelligence (AI) and Machine Learning (ML)

Rising employment of ML and AI technologies is propelling the market growth. As per industry reports, the global AI market size was valued at USD 638.23 Billion in 2024. AI and ML technologies enhance data warehousing by enabling smart and automated data optimization, which improves data quality, speeds up processing, and reduces manual efforts. These technologies assist in recognizing patterns and trends in extensive datasets, allowing predictive analysis that supports faster and more accurate business decisions. ML models continuously learn from incoming data, improving performance and offering real-time insights. AI also facilitates knowledge discovery by automatically detecting correlations and anomalies that traditional methods may miss. As organizations continue to rely on data-oriented strategies, the integration of AI and ML into data warehousing is boosting operational efficiency and decision-making capabilities. This shift is leading to higher adoption across industries, such as retail, healthcare, and finance. Consequently, businesses are investing more in modern solutions, contributing to the expansion of the data warehousing market size 2025.

Rising Penetration of Smartphones

The increasing number of people with smartphones and internet connections is primarily driving the data warehousing market growth. According to the GSMA, there are more than 6.2 Billion active iOS and android smartphones worldwide as of 2023, and it is expected to reach 7.4 Billion by 2025. Additionally, the usage of mobile technology is increasing across a range of computer systems, including Data Warehouse (DW), Business Intelligence (BI) systems, and Data Analytic systems. Moreover, according to the Ministry of Information and Broadcasting, in November 2022, India had more than 1.2 Billion mobile phone subscribers, including 600 million smartphone users. Furthermore, it was mentioned that in addition to having relatively cheap data rates, the widespread usage of smartphones has resulted in individuals consuming a lot of information and entertainment on their mobile devices. Besides this, mobile phones act as a database, where a considerable amount of user data is stored, which can be subjected to analysis as per the T&C approval by the user. The data can be utilized by active data warehouses to collect multiple traits of the user. Smartphone users need a vast cloud database for data access, thereby needing data warehousing solutions, driving market growth.

Emergence of Cloud Data Warehouses

The rising importance of business intelligence and analytics across different business verticals is emerging as one of the new trends in data warehousing. Moreover, cloud data warehouses act as a backbone in analytics and business intelligence processes for storing large amounts of data. In line with this, the escalating adoption of cloud services is further augmenting the adoption of business intelligence and analytic practices as they aid organizations in deriving actionable insights. The shift towards the implementation of Artificial Intelligence (AI) and Machine Learning (ML) across different industries is further expected to bolster the market for data warehousing solutions. Moreover, various key market players are AI-integrated cloud data warehousing solutions. For instance, in October 2023, mParticle, Inc. announced the launch of ComposeID, an identity resolution service compatible with cloud data warehousing environments. ComposeID is based on IDSync. IDSync is intended to assist teams in supporting any identity strategy on any data architecture. Similarly, in July 2023, International Business Machines Corp. (IBM) announced new updates in the IBM Db2 Warehouse. The next generation of the warehouse can add cloud object storage with the support of advanced caching, delivering four times faster query response while cutting storage costs by 34%.

Increasing Adoption of Hybrid Work Models

The surge in remote work arrangements is gaining significance among the current key trends in data warehousing. The emerging trend of work-from-home has generated new complicated challenges for organizations to overcome. As a result, businesses are increasingly embracing cloud computing and migrating to cloud data warehouses. In line with this, various tech giants are partnering with each other to develop high-performing cloud data warehouses. For instance, in June 2022, HCL Technologies partnered with Amazon Web Services. AWS allows HCL to offer scalable, cost-effective, secure, and high-performing enterprise data warehouse solutions. Amazon Redshift provides data-driven business insights enabled by modern AI/ML capabilities to improve operational efficiency, decision-making, and faster time to market to HCL Technologies. Besides this, the rising need for low latency and high-speed analytics, combined with the growing role of business intelligence in enterprise management, is expected to drive the data warehousing market demand significantly.

Global Data Warehousing Industry Segmentation:

Breakup by Offering:

• ETL Solutions
• Statistical Analysis
• Data Mining
• Others

ETL solutions hold the majority of the total market share

Based on the offering, the global data warehousing market can be segmented into ETL solutions, statistical analysis, data mining, and others. According to the report, ETL solutions hold the majority of the total market share.

Extract, transform, and load (ETL) refers to a process through which data is extracted from a source and then moved to a central host. The process is high in demand as it runs in parallel to save time. For instance, during data extraction, transformation can begin processing the received data simultaneously to prepare it for loading. This allows the loading process to work on the prepared data without waiting for the entire extraction process to finish.

Breakup by Data Type:

• Unstructured Data
• Semi-Structured and Structured Data

Semi-structured and structured data currently accounts for the largest market share

Based on the data type, the global data warehousing market has been divided into unstructured data and semi-structured and structured data. According to the report, semi-structured and structured data currently accounts for the largest market share.

Structured data is information that has been formatted and transformed into a well-defined data model. The raw data is mapped into predesigned fields that can then be extracted and read through SQL easily. Due to the organization of structured data, it is easier to analyze and drive insights from it. While on the other hand semi-structured data or partially structured data is another category between structured and unstructured data. Semi-structured data is a type of data that has some consistent and definite characteristics. Businesses generally use organizational properties like metadata or semantics tags with semi-structured data to make it more manageable.

Breakup by Deployment Model:

• On-premises
• Cloud-based
• Hybrid

On-premises exhibit a clear dominance in the market

Based on the deployment model, the global data warehousing market can be categorized into on-premises, cloud-based, and hybrid. According to the report, on-premises exhibit a clear dominance in the market.

In an on-premises deployment model, the service is purchased and installed on the user server. This service is maintained by the IT specialists in the end-user organization. The growing demand for the on-premises model can be attributed to factors such as the high cost involved with the implementation and up-gradation and fewer options for scalability. These solutions offer features such as workflow streamlining, control, speed, security, governance, and reporting.

Breakup by Enterprise Size:

• Large Enterprises
• Small and Medium-sized Enterprises

Large enterprises currently hold the majority of the global market share

Based on the enterprise size, the global data warehousing market has been segregated into large enterprises and small and medium-sized enterprises, where large enterprises currently hold the majority of the global market share.

Large enterprises generally have more complex data management requirements on account of their scale and diverse operations, which may require a combination of on-premises solutions, cloud-based services, and hybrid deployments to meet their complex business needs. Large enterprises also need more customization, integration with existing systems, and advanced features such as data governance, analytics, and security.

Breakup by End User:

• BFSI
• IT and Telecom
• Government
• Manufacturing
• Retail
• Healthcare
• Media and Entertainment
• Others

The BFSI sector exhibits a clear dominance in the market

Based on the end user, the global data warehousing market can be bifurcated into BFSI, IT and telecom, government, manufacturing, retail, healthcare, media and entertainment, and others. According to the report, the BFSI sector exhibits a clear dominance in the market.

The banking, financial services, and insurance (BFSI) sector is highly lucrative for growth in the Data Warehouse-as-a-Service market as it deals with massive customer data generated regularly. Due to the large amount of data generated across the BFSI sector, enterprises need data warehousing solutions to automatically track the performance and behavior of the information stored in their systems. Numerous banks, including BNY Mellon, Morgan Stanley, Bank of America, Credit Suisse, and PNC are already working on strategies around Big Data in Banking, and other banks are rapidly catching up.

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

North America currently dominates the global market

On a regional level, the market has been classified into North America, Asia-Pacific, Europe, Latin America, and Middle East and Africa, where North America currently dominates the global market.

North America is anticipated to have a significant market share owing to the availability of technologically advanced data warehouse infrastructure. U.S. organizations are rapidly adopting analytics solutions across several verticals. They are considered the leading country in the market due to the significant demand for managing operational data and the increased emergence of cloud solution providers. Moreover, various enterprises in the region are extensively investing in the deployment of robust data warehousing solutions to manage and utilize data effectively. For instance, in January 2023, Eucloid, a Data & Growth Intelligence company, announced a partnership with Databricks to make the Lakehouse Platform available to its Fortune 500 clients. The company's Lakehouse platform provides a single solution for all significant data tasks, which integrates several data warehouse and data lake features.

Competitive Landscape:

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

• Actian Corporation (HCL Technologies Limited)
• Amazon Web Services Inc. (Amazon.com Inc)
• Cloudera Inc.
• Dell Technologies Inc.
• Google LLC (Alphabet Inc.)
• Hewlett Packard Enterprise Development LP
• International Business Machines Corporation
• Microsoft Corporation
• Oracle Corporation
• SAP SE
• Snowflake Inc
• Teradata Corporation

Key Questions Answered in This Report

• 1.How big is the data warehousing market?
• 2.What is the expected growth rate of the global data warehousing market during 2025-2033?
• 3.What has been the impact of COVID-19 on the global data warehousing market?
• 4.What are the key factors driving the global data warehousing market?
• 5.What is the breakup of the global data warehousing market based on the offering?
• 6.What is the breakup of the global data warehousing market based on the data type?
• 7.What is the breakup of the global data warehousing market based on deployment model?
• 8.What is the breakup of the global data warehousing market based on the enterprise size?
• 9.What is the breakup of the global data warehousing market based on the end user?
• 10.What are the key regions in the global data warehousing market?
• 11.Who are the key players/companies in the global data warehousing market?

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 Warehousing Market

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

6 Market Breakup by Offering

• 6.1 ETL Solutions
  • 6.1.1 Market Trends
  • 6.1.2 Market Forecast
• 6.2 Statistical Analysis
  • 6.2.1 Market Trends
  • 6.2.2 Market Forecast
• 6.3 Data Mining
  • 6.3.1 Market Trends
  • 6.3.2 Market Forecast
• 6.4 Others
  • 6.4.1 Market Trends
  • 6.4.2 Market Forecast

7 Market Breakup by Data Type

• 7.1 Unstructured Data
  • 7.1.1 Market Trends
  • 7.1.2 Market Forecast
• 7.2 Semi-Structured and Structured Data
  • 7.2.1 Market Trends
  • 7.2.2 Market Forecast

8 Market Breakup by Deployment Model

• 8.1 On-premises
  • 8.1.1 Market Trends
  • 8.1.2 Market Forecast
• 8.2 Cloud-based
  • 8.2.1 Market Trends
  • 8.2.2 Market Forecast
• 8.3 Hybrid
  • 8.3.1 Market Trends
  • 8.3.2 Market Forecast

9 Market Breakup by Enterprise Size

• 9.1 Large Enterprises
  • 9.1.1 Market Trends
  • 9.1.2 Market Forecast
• 9.2 Small and Medium-sized Enterprises
  • 9.2.1 Market Trends
  • 9.2.2 Market Forecast

10 Market Breakup by End User

• 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 Government
  • 10.3.1 Market Trends
  • 10.3.2 Market Forecast
• 10.4 Manufacturing
  • 10.4.1 Market Trends
  • 10.4.2 Market Forecast
• 10.5 Retail
  • 10.5.1 Market Trends
  • 10.5.2 Market Forecast
• 10.6 Healthcare
  • 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 Others
  • 10.8.1 Market Trends
  • 10.8.2 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 Actian Corporation (HCL Technologies Limited)
    • 16.3.1.1 Company Overview
    • 16.3.1.2 Product Portfolio
  • 16.3.2 Amazon Web Services Inc. (Amazon.com Inc)
    • 16.3.2.1 Company Overview
    • 16.3.2.2 Product Portfolio
    • 16.3.2.3 SWOT Analysis
  • 16.3.3 Cloudera Inc.
    • 16.3.3.1 Company Overview
    • 16.3.3.2 Product Portfolio
    • 16.3.3.3 Financials
  • 16.3.4 Dell Technologies Inc.
    • 16.3.4.1 Company Overview
    • 16.3.4.2 Product Portfolio
    • 16.3.4.3 Financials
    • 16.3.4.4 SWOT Analysis
  • 16.3.5 Google LLC (Alphabet Inc.)
    • 16.3.5.1 Company Overview
    • 16.3.5.2 Product Portfolio
    • 16.3.5.3 SWOT Analysis
  • 16.3.6 Hewlett Packard Enterprise Development LP
    • 16.3.6.1 Company Overview
    • 16.3.6.2 Product Portfolio
    • 16.3.6.3 Financials
    • 16.3.6.4 SWOT Analysis
  • 16.3.7 International Business Machines Corporation
    • 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 Microsoft 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 Oracle 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 SAP SE
    • 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 Snowflake Inc
    • 16.3.11.1 Company Overview
    • 16.3.11.2 Product Portfolio
    • 16.3.11.3 Financials
  • 16.3.12 Teradata Corporation
    • 16.3.12.1 Company Overview
    • 16.3.12.2 Product Portfolio
    • 16.3.12.3 Financials
    • 16.3.12.4 SWOT Analysis