Data Warehousing Market Size By Data Type (Structured, Unstructured), By Deployment Model (On Premise, Cloud, Hybrid), By Organization Type (SMEs, Large Enterprises), By Offering (Statistical Analysis, Data Mining Tools, ETL Solutions), By Application (Retail, Telecom & IT, BFSI, Manufacturing, Healthcare, Government), Industry Analysis Report, Regional Outlook, Growth Potential, Competitive Marke

Published Date: July - 2024 | Publisher: MRA | No of Pages: 240 | Industry: Media and IT | Format: Report available in PDF / Excel Format

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Data Warehousing Market Size By Data Type (Structured, Unstructured), By Deployment Model (On Premise, Cloud, Hybrid), By Organization Type (SMEs, Large Enterprises), By Offering (Statistical Analysis, Data Mining Tools, ETL Solutions), By Application (Retail, Telecom & IT, BFSI, Manufacturing, Healthcare, Government), Industry Analysis Report, Regional Outlook, Growth Potential, Competitive Marke

Data Warehousing Market Size

Data Warehousing Market size exceeded USD 13 billion, globally in 2018 and is estimated to grow at over 12% CAGR between 2019 and 2025.

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Data warehousing refers to the amalgamation of data from several disparate sources, including social media, mobile data, and business applications. This data is used for delivering valuable business insights and analytical reports. Heterogeneous data obtained from various sources is first cleansed and then organized into a consolidated format in the data warehouse. Enterprises use data warehousing tools and Database Management System (DBMS) to access the data stored on warehouse servers to support their operational decisions.


The data warehousing market growth is attributed to factors such as the increasing amount of data generated by enterprises and growing need for Business Intelligence (BI) to gain competitive advantage. The vast volumes of data produced by various business verticals are exerting tremendous pressure on existing enterprise resources, forcing them to adopt data warehousing solutions for efficient, flexible, and scalable storage. This data can be leveraged using advanced data mining and BI tools, providing valuable business insights to users for increased operational efficiency, better decision making, strengthening customer retention, and increasing revenue streams.
 

Data Warehousing Market Report Attributes
Report Attribute Details
Base Year 2018
Data Warehousing Market Size in 2018 13 Billion (USD)
Forecast Period 2019 to 2025
Forecast Period 2019 to 2025 CAGR 12%
2025 Value Projection 30 Billion (USD)
Historical Data for 2014 to 2018
No. of Pages 265
Tables, Charts & Figures 429
Segments covered Data Type, Deployment Model, Organization Type, Offering, Application and Region
Growth Drivers
  • Rising need of data warehouses for disparate data storage
  • Growing demand of data mining for BI and data analytics
  • Increasing use of historical data for enhancing customer experience
  • Proliferation of cloud technology in data warehousing
Pitfalls & Challenges
  • Data rigidity and inefficient architecture
  • High deployment costs and IT complexity
  • Threat of data breaches and cyber attacks

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Another factor leading to market growth is the rising trend of cloud computing. The growing adoption of cloud-based services will facilitate the demand for cloud data warehousing. Enterprises and government agencies are realizing the economic benefits of cloud data warehouse, such as on-demand computing, unlimited storage, integrated BI tools, and affordable pricing options. The proliferation of Data Warehouse as-a-Service (DWaaS) and the increasing popularity of unstructured data for data analytics are further expected to fuel market growth.

Data Warehousing Market Analysis

Unstructured data warehousing market, which includes data not associated with a recognizable model, is expected to grow at over 10% CAGR from 2019 to 2025 as enterprises leverage unstructured data for advanced analytics. The data is not pre-organized in any format and usually contains text-rich information such as names and addresses. The major driving force leading to the increased popularity of unstructured data warehousing is the presence of crucial underlying information.

The rapidly increasing volumes of Big Data and usage of new business analytics tools for handling it, such as MapReduce and Hadoop, have highlighted the need for unstructured data in warehousing solutions. With the rapid adoption of flexible cloud data warehouses with unstructured data ingestion, the unstructured data segment is expected to witness high growth over the forecast period.

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Data mining tools aid in the automated processing and analysis of large volumes of data to discover patterns, trends, or correlations that hold important business value. Enterprises leverage such tools to predict future results, helping them to find new opportunities such as product development and revenue expansion.

Data mining has witnessed a substantial increase in its adoption for fraud detection, consumer profiling, website optimization, and determining potential market segments. A wide variety of data warehousing tools, including Azure ML Studio, RStudio, Python, and SAS are available at affordable prices, enabling enterprises to capitalize on enhanced data insights and increase business productivity. They are forecast to account over 25% of the data warehousing market share by 2025.

Storing data on-premise can become very expensive if computing power and storage have different scalability. Cloud warehouses can instantly scale themselves to deliver as high or as low computing needs as required, making them highly cost-effective.

Cloud data warehousing is gaining significant traction among enterprises as it provides numerous benefits including multiple data type support, on-demand computing, unlimited storage, and flexible pricing models. SMEs are rapidly adopting the cloud deployment model due to affordable costs and low infrastructure requirements. Favorable government initiatives to promote cloud computing and big data analytics are also a chief growth driver for the market.

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Data has become a goldmine for the banking, financial services, and insurance (BFSI) industry. With data mining and big data analytics, BFSI companies can gather and make sense of vast amounts of data. This has led to a surge in data warehousing solutions because companies need a place to store and manage all this data. Why? Because it's helping them tackle big problems like fraud and cyberattacks. Financial institutions are using big data analytics to spot fake insurance claims, predict fraud, assess credit risk, and make sure they're meeting all the rules and regulations. With the rise of the Internet of Things (IoT), BFSI companies are also dealing with even more data from connected devices like ATMs, mobile banking apps, and smart credit cards. This is driving the demand for big data analytics and data warehousing even further.

Large enterprises are early adopters of data warehousing solutions. In-house data centers, dedicated IT staff, and availability of financial resources for infrastructure development have fueled the market growth among large enterprises. They deploy advanced enterprise solutions, such as Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP), generating a vast amount of valuable data, which is leveraged for competitive advantage. With the development of hybrid warehousing models, large enterprises can harness the flexibility and scalability of cloud warehouse using on-premise data warehousing.

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Enterprises in Asia Pacific are establishing various data centers for providing big data solutions and cloud data warehousing systems. For instance, in 2019, the Chinese e-commerce firm, Alibaba launched two cloud-based data centers in China, targeted at providing cloud data warehousing solutions to Chinese enterprises in the Hohhot and Chengdu industrial areas. The services are also proving economical for SMEs due to no upfront infrastructure investments and affordable pricing.

The Asia Pacific data warehousing market is expected to witness growth at over 15% CAGR from 2019 to 2025 due to the rapid growth of IT infrastructure, increasing number of data centers, and the wide-scale adoption of cloud technologies.

Data Warehousing Market Share

Enterprises operating in the market are adopting strategies such as collaborations, new data center launches, and product developments, to enhance their existing offerings and expand their portfolio for targeting a wider customer base. For instance, in May 2019, Oracle partnered with SUSE, a German company developing Linux software, for integrating its Oracle Database 19c data warehouse software into its SUSE platform. The collaboration brings new developments in data warehousing software such as hybrid memory partitioning and advanced diagnostics.

Some of the major companies operating in the data warehousing market are

  • AWS
  • 1010DATA
  • Accur8Software
  • Actian Corp
  • AtScale, Inc.
  • Attunity
  • Cloudera, Inc.
  • Dell
  • Google
  • IBM Corporation
  • Informatica
  • Microfocus
  • Microsoft Corporation
  • MarkLogic Corporation
  • Netavis Software Gmbh
  • Oracle Corporation
  • Panoply Ltd.
  • Pivotal Software, Inc.
  • SAP SE
  • Sigma Computing
  • Snowflake, Inc.
  • Teradata
  • Talend
  • SAS Institute, Inc.

Industry Background

Imagine your business as a massive puzzle, with each piece of data representing a tiny fragment of the whole picture. In the past, companies had to assemble this puzzle using two smaller boxesdatabases and data marts. This was like cutting up the puzzle and storing it in different places, making it difficult to see the big picture. But technology has given us a new tooldata warehousing. It's like a giant storage chest that can hold all the pieces of the puzzle in one place. With data warehousing, companies can analyze vast amounts of data together, like combining all the puzzle pieces to reveal the full image. Before, we relied on older systems that couldn't keep up with the growing size and speed of data. But now, we have super-powerful data warehouses that can handle even the most massive puzzles. And with cloud computing, we can access these warehouses from anywhere with an internet connection. As a result, businesses can now use data analytics to make smarter decisions, find new opportunities, and stay ahead of the competition. It's like having a crystal ball that shows you the path to success. And as data becomes even bigger and more important, the demand for data warehousing and big data solutions will only grow.

The data warehousing market research report includes in-depth coverage of the industry, with estimates & forecast in terms of revenue in USD from 2014 to 2025, for the following segments

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By Data Type

  • Structured
  • Unstructured

By Deployment Model

  • On-premise
  • Cloud
  • Hybrid

By Organization Type

  • Large enterprises
  • SMEs

By Offering

  • Statistical analysis
  • Data mining tools
  • Extract, Transform & Load (ETL) Solutions
  • Others

By Application

  • Retail
  • IT & Telecom
  • BFSI
  • Manufacturing
  • Healthcare
  • Government
  • Others

The above information has been provided for the following regions and countries

  • North America
    • U.S.
    • Canada
  • Europe
    • UK
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
  • APAC
    • China
    • India
    • Japan
    • South Korea
    • ANZ
    • Southeast Asia
  • LAMEA
    • Brazil
    • Mexico
    • Colombia
    • Chile
  • MEA
    • Saudi Arabia
    • South Africa
    • Qatar
    • UAE

 

 

Table of Content

Report Content

Chapter 1.   Methodology & Scope

1.1.  Methodology

1.1.1. Initial data exploration

1.1.2. Statistical model and forecast

1.1.3. Industry insights and validation

1.1.4. Scope

1.1.5. Definitions

1.1.6. Methodology & forecast parameters

1.2.  Data Sources

1.2.1. Secondary

1.2.2. Primary

Chapter 2.   Executive Summary

2.1.  Data warehousing  industry 360º synopsis, 2014 – 2025

2.2.  Business trends

2.3.  Regional trends

2.4.  Data type trends

2.5.  Deployment model trends

2.6.  Organization type trends

2.7.  Offering trends

2.8.  Application trends

Chapter 3.   Data Warehousing Industry Insights

3.1.  Introduction

3.2.  Industry segmentation

3.3.  Industry landscape, 2014 – 2025

3.4.  Data warehousing evolution

3.5.  Data warehousing architecture analysis

3.6.  Data warehousing industry ecosystem analysis

3.7.  Technology & innovation landscape

3.7.1. Integration of Machine Learning (ML) with data warehousing

3.7.2. Technological advancements in Internet-of-Things (IoT)

3.7.3. Proliferation of cloud technology in data warehousing

3.8.  Regulatory landscape

3.8.1. Information Security Technology- Personal Information Security Specification GB/T 35273-2017

3.8.2. General Data Protection Regulation (GDPR), EU

3.8.3. The NIST Special Publication 800-144 - Guidelines on Security and Privacy in Public Cloud Computing, U.S.

3.8.4. The Health Insurance Portability and Accountability Act (HIPAA) of 1996

3.8.5. Secure India National Digital Communications Policy 2018 - Draft

3.8.6. Payment Card Industry Data Security Standard (PCI DSS)- version 3.2.1

3.9.  Industry impact forces

3.9.1. Growth drivers

3.9.1.1.    Rising need of data warehouses for disparate data storage

3.9.1.2.    Growing demand of data mining for BI and data analytics

3.9.1.3.    Increasing use of historical data for enhancing customer experience

3.9.1.4.    Proliferation of cloud technology in data warehousing

3.9.2. Industry pitfalls & challenges

3.9.2.1.    Data rigidity and inefficient architecture

3.9.2.2.    High deployment costs and IT complexity

3.9.2.3.    Threat of data breaches and cyber attacks

3.10.   Porter’s analysis

3.11.   PESTEL analysis

3.12.   Growth potential analysis

Chapter 4.   Competitive Landscape

4.1.  Introduction

4.2.  Company market share analysis, 2018

4.3.  Competive analysis of major data warehousing solution providers, 2018

4.3.1. Amazon Web Services (AWS)

4.3.2. IBM Corporation

4.3.3. Microsoft Corporation

4.3.4. Oracle Corporation

4.3.5. SAP SE

4.3.6. Teradata Corporation

4.4.  Competive analysis of other prominent players, 2018

4.4.1. Cloudera, Inc.

4.4.2. MarkLogic Corporation

4.4.3. Snowflake Inc.

Chapter 5.   Data Warehousing Market, By Data Type

5.1.  Key trends, by data type

5.2.  Structured

5.2.1. Market estimates and forecast, 2014 – 2025

5.3.  Unstructured

5.3.1. Market estimates and forecast, 2014 – 2025

Chapter 6.   Data Warehousing Market, By Deployment Model

6.1.  Key trends, by deployment model

6.2.  On-premise

6.2.1. Market estimates and forecast, 2014 - 2025

6.3.  Cloud

6.3.1. Market estimates and forecast, 2014 - 2025

6.4.  Hybrid

6.4.1. Market estimates and forecast, 2014 - 2025

Chapter 7.   Data Warehousing Market, By Organization Type

7.1.  Key trends, by organization type

7.2.  Large enterprises

7.2.1. Market estimates and forecast, 2014 - 2025

7.3.  SMEs

7.3.1. Market estimates and forecast, 2014 – 2025

Chapter 8.   Data Warehousing Market, By Offering

8.1.  Key trends, by offering

8.2.  Statistical analysis

8.2.1. Market estimates and forecast, 2014 - 2025

8.3.  Data mining tools

8.3.1. Market estimates and forecast, 2014 – 2025

8.4.  ETL solutions

8.4.1. Market estimates and forecast, 2014 - 2025

8.5.  Others

8.5.1. Market estimates and forecast, 2014 - 2025

Chapter 9.   Data Warehousing Market, By Application

9.1.  Key trends, by application

9.2.  Retail

9.2.1. Market estimates and forecast, 2014 - 2025

9.3.  Telecom & IT

9.3.1. Market estimates and forecast, 2014 – 2025

9.4.  BFSI

9.4.1. Market estimates and forecast, 2014 – 2025

9.5.  Manufacturing

9.5.1. Market estimates and forecast, 2014 - 2025

9.6.  Healthcare

9.6.1. Market estimates and forecast, 2014 – 2025

9.7.  Government

9.7.1. Market estimates and forecast, 2014 – 2025

9.8.  Others

9.8.1. Market estimates and forecast, 2014 – 2025

Chapter 10. Data Warehousing Market, By Region

10.1. Key trends, by region

10.2. North America

10.2.1. Market estimates and forecast, 2014 - 2025

10.2.2.  Market estimates and forecast, by data type, 2014 – 2025

10.2.3.  Market estimates and forecast, by deployment model, 2014 – 2025

10.2.4.  Market estimates and forecast, by organization type, 2014 – 2025

10.2.5.  Market estimates and forecast, by offering, 2014 – 2025

10.2.6.  Market estimates and forecast, by application, 2014 – 2025

10.2.7.  U.S.

10.2.7.1.     Market estimates and forecast, 2014 - 2025

10.2.7.2.     Market estimates and forecast, by data type, 2014 – 2025

10.2.7.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.2.7.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.2.7.5.     Market estimates and forecast, by offering, 2014 – 2025

10.2.7.6.     Market estimates and forecast, by application, 2014 – 2025

10.2.8. Canada

10.2.8.1.     Market estimates and forecast, 2014 - 2025

10.2.8.2.     Market estimates and forecast, by data type, 2014 – 2025

10.2.8.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.2.8.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.2.8.5.     Market estimates and forecast, by offering, 2014 – 2025

10.2.8.6.     Market estimates and forecast, by application, 2014 – 2025

10.3. Europe

10.3.1. Market estimates and forecast, 2014 - 2025

10.3.2.  Market estimates and forecast, by data type, 2014 – 2025

10.3.3.  Market estimates and forecast, by deployment model, 2014 – 2025

10.3.4.  Market estimates and forecast, by organization type, 2014 – 2025

10.3.5.  Market estimates and forecast, by offering, 2014 – 2025

10.3.6.  Market estimates and forecast, by application, 2014 – 2025

10.3.7.  U.K.

10.3.7.1.     Market estimates and forecast, 2014 - 2025

10.3.7.2.     Market estimates and forecast, by data type, 2014 – 2025

10.3.7.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.3.7.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.3.7.5.     Market estimates and forecast, by offering, 2014 – 2025

10.3.7.6.     Market estimates and forecast, by application, 2014 – 2025

10.3.8. Germany

10.3.8.1.     Market estimates and forecast, 2014 - 2025

10.3.8.2.     Market estimates and forecast, by data type, 2014 – 2025

10.3.8.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.3.8.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.3.8.5.     Market estimates and forecast, by offering, 2014 – 2025

10.3.8.6.     Market estimates and forecast, by application, 2014 – 2025

10.3.9. France

10.3.9.1.     Market estimates and forecast, 2014 - 2025

10.3.9.2.     Market estimates and forecast, by data type, 2014 – 2025

10.3.9.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.3.9.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.3.9.5.     Market estimates and forecast, by offering, 2014 – 2025

10.3.9.6.     Market estimates and forecast, by application, 2014 – 2025

10.3.10.  Italy

10.3.10.1.    Market estimates and forecast, 2014 - 2025

10.3.10.2.    Market estimates and forecast, by data type, 2014 – 2025

10.3.10.3.    Market estimates and forecast, by deployment model, 2014 – 2025

10.3.10.4.    Market estimates and forecast, by organization type, 2014 – 2025

10.3.10.5.    Market estimates and forecast, by offering, 2014 – 2025

10.3.10.6.    Market estimates and forecast, by application, 2014 – 2025

10.3.11.  Spain

10.3.11.1.    Market estimates and forecast, 2014 - 2025

10.3.11.2.    Market estimates and forecast, by data type, 2014 – 2025

10.3.11.3.    Market estimates and forecast, by deployment model, 2014 – 2025

10.3.11.4.    Market estimates and forecast, by organization type, 2014 – 2025

10.3.11.5.    Market estimates and forecast, by offering, 2014 – 2025

10.3.11.6.    Market estimates and forecast, by application, 2014 – 2025

10.3.12.  Netherlands

10.3.12.1.    Market estimates and forecast, 2014 - 2025

10.3.12.2.    Market estimates and forecast, by data type, 2014 – 2025

10.3.12.3.    Market estimates and forecast, by deployment model, 2014 – 2025

10.3.12.4.    Market estimates and forecast, by organization type, 2014 – 2025

10.3.12.5.    Market estimates and forecast, by offering, 2014 – 2025

10.3.12.6.    Market estimates and forecast, by application, 2014 – 2025

10.4.  Asia Pacific

10.4.1. Market estimates and forecast, 2014 - 2025

10.4.2.  Market estimates and forecast, by data type, 2014 – 2025

10.4.3.  Market estimates and forecast, by deployment model, 2014 – 2025

10.4.4.  Market estimates and forecast, by organization type, 2014 – 2025

10.4.5.  Market estimates and forecast, by offering, 2014 – 2025

10.4.6.  Market estimates and forecast, by application, 2014 – 2025

10.4.7.  China

10.4.7.1.     Market estimates and forecast, 2014 - 2025

10.4.7.2.     Market estimates and forecast, by data type, 2014 – 2025

10.4.7.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.4.7.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.4.7.5.     Market estimates and forecast, by offering, 2014 – 2025

10.4.7.6.     Market estimates and forecast, by application, 2014 – 2025

10.4.8. India

10.4.8.1.     Market estimates and forecast, 2014 - 2025

10.4.8.2.     Market estimates and forecast, by data type, 2014 – 2025

10.4.8.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.4.8.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.4.8.5.     Market estimates and forecast, by offering, 2014 – 2025

10.4.8.6.     Market estimates and forecast, by application, 2014 – 2025

10.4.9.  Japan

10.4.9.1.     Market estimates and forecast, 2014 - 2025

10.4.9.2.     Market estimates and forecast, by data type, 2014 – 2025

10.4.9.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.4.9.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.4.9.5.     Market estimates and forecast, by offering, 2014 – 2025

10.4.9.6.     Market estimates and forecast, by application, 2014 – 2025

10.4.10.  ANZ

10.4.10.1.    Market estimates and forecast, 2014 - 2025

10.4.10.2.    Market estimates and forecast, by data type, 2014 – 2025

10.4.10.3.    Market estimates and forecast, by deployment model, 2014 – 2025

10.4.10.4.    Market estimates and forecast, by organization type, 2014 – 2025

10.4.10.5.    Market estimates and forecast, by offering, 2014 – 2025

10.4.10.6.    Market estimates and forecast, by application, 2014 – 2025

10.4.11.  South Korea

10.4.11.1.    Market estimates and forecast, 2014 - 2025

10.4.11.2.    Market estimates and forecast, by data type, 2014 – 2025

10.4.11.3.    Market estimates and forecast, by deployment model, 2014 – 2025

10.4.11.4.    Market estimates and forecast, by organization type, 2014 – 2025

10.4.11.5.    Market estimates and forecast, by offering, 2014 – 2025

10.4.11.6.    Market estimates and forecast, by application, 2014 – 2025

10.4.12.  Southeast Asia

10.4.12.1.    Market estimates and forecast, 2014 - 2025

10.4.12.2.    Market estimates and forecast, by data type, 2014 – 2025

10.4.12.3.    Market estimates and forecast, by deployment model, 2014 – 2025

10.4.12.4.    Market estimates and forecast, by organization type, 2014 – 2025

10.4.12.5.    Market estimates and forecast, by offering, 2014 – 2025

10.4.12.6.    Market estimates and forecast, by application, 2014 – 2025

10.5. Latin America

10.5.1. Market estimates and forecast, 2014 - 2025

10.5.2.  Market estimates and forecast, by data type type, 2014 – 2025

10.5.3.  Market estimates and forecast, by deployment model, 2014 – 2025

10.5.4.  Market estimates and forecast, by organization type, 2014 – 2025

10.5.5.  Market estimates and forecast, by offering, 2014 – 2025

10.5.6.  Market estimates and forecast, by application, 2014 – 2025

10.5.7.  Brazil

10.5.7.1.     Market estimates and forecast, 2014 - 2025

10.5.7.2.     Market estimates and forecast, by data type, 2014 – 2025

10.5.7.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.5.7.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.5.7.5.     Market estimates and forecast, by offering, 2014 – 2025

10.5.7.6.     Market estimates and forecast, by application, 2014 – 2025

10.5.8. Mexico

10.5.8.1.     Market estimates and forecast, 2014 - 2025

10.5.8.2.     Market estimates and forecast, by data type, 2014 – 2025

10.5.8.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.5.8.4.     Market estimates and forecast, by organization type, 2014 – 2025

10.5.8.5.     Market estimates and forecast, by offering, 2014 – 2025

10.5.8.6.     Market estimates and forecast, by application, 2014 – 2025

10.5.9.  Argentina

10.5.9.1.     Market estimates and forecast, 2014 - 2025

10.5.9.2.     Market estimates and forecast, by data type, 2014 – 2025

10.5.9.3.     Market estimates and forecast, by deployment model, 2014 – 2025

10.5.9.4. &

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