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Cloud Datawarehouse Market Size, Share & Industry Trends Analysis Report By Type, By Application, By Deployment Model, By Organization Size, By Vertical, By Regional Outlook and Forecast, 2022-2028

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    Report

  • 365 Pages
  • April 2022
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5600968
The Global Cloud Datawarehouse Market size is expected to reach $17.8 billion by 2028, rising at a market growth of 21.5% CAGR during the forecast period.

The cloud data warehouse is a database that is maintained as a managed service on the public cloud and is designed for scalable business intelligence and analytics. For many years, data warehouses have been a mainstay of corporate analytics and reporting.

Companies now can flexibly build or shrink data warehouses to comply with changing company budgets and objectives due to cloud data warehousing. A cloud data warehouse is a typical data warehouse that saves data from a range of sources, including finance systems, IoT, CRM, and many others. The data saved in a cloud-based data warehouse is highly organized and standardized, making it suitable to support a wide range of particular business intelligence and analytics use cases.

Cloud-based data warehouses enable business intelligence teams to provide faster and better insights due to enhanced access, scalability, and speed, allowing them to focus on running their business instead of managing a room full of servers.

Through Data Access, an enterprise can store data on the cloud, it provides real-time data from a variety of sources to their analysts, allowing them to perform better analyses more quickly. The Scalability is growing a cloud data warehouse, which is faster and less expensive than scaling an on-premise system because it eliminates the requirement of purchasing new hardware, and scaling can be done automatically as needed. Performance allows queries addressed faster and at a lesser cost in a cloud data warehouse than they can in a typical on-premises data warehouse.

Cloud Data Warehouses offer enhanced performance, service resilience, and other benefits to clients, boosting overall industry demand for Cloud Data Warehouse. With the increased adoption of IoT technologies and the rising usage of cloud Data warehouses for processing in different businesses for various purposes, the Cloud Data Warehouse Market is expected to grow.

IoT data is complicated, with several clients and many queries, storage built in both SQL and NoSQL and transactions that must be managed by IoT apps. The data is secure and reliable due to the Cloud Data Warehouse. Additionally, Cloud Data Warehouse provides clients with information storage, automatic data backups, and replication, accelerating the usage of Data Warehouse as a Service.

The rising significance of data analytics and business intelligence in enterprise management, along with the growing reliance on data-driven decision to boost business performance and the need for regulatory oversight and security, are likely to propel the market forward.



COVID-19 Impact Analysis

COVID-19 has wreaked havoc on the world's economic sectors and industries. The disruptions are largely due to lockdown measures created and implemented by countries across the world as a health strategy to minimize the impact of the pandemic's spread on the worldwide population. The pandemic has boosted the market for Cloud Datawarehouses. Organizations are experiencing new challenges as a result of the COVID-19 pandemic and the rise of remote work environments. The recent economic downfall in response to the worldwide diffusion of COVID-19 highlights the necessity for alternative business methods.

Market Growth Factors


Deployment of Large-scale cloud data warehouses

With the current IT infrastructure's pace along with the fast volume of data and complexity levels, companies are focusing on strategies to emphasize business operations rather than IT infrastructure. Advances in cloud-based architecture are pushing businesses to move their mission-critical operations to the cloud, including the use of cloud-based data stores and data warehouses. The increasing adoption of IoT-enabled devices is one of the primary drivers leading development in the cloud data warehouse industry. The increased use of IoT-connected devices across the world has resulted in massive amounts of data being generated.

Low cost and more secure cloud data warehouse

Cloud data warehouses are becoming increasingly popular due to their low cost. On-premises data warehouses necessitate high-cost technology, lengthy upgrades, maintenance costs, and outage management. Growing a business intelligence programme increases expenses considerably because on-premises computation and storage cannot be acquired separately. Organizations with on-premises data warehouses, for example, invest a large amount of money to accommodate data influxes in advance of major events such as a new release or the upcoming years. Data warehouse teams can buy as little or as much computing power and storage as they need using cloud data warehouses. Furthermore, cloud data warehouses do not necessitate server rooms, networking, or any additional infrastructure.

Marketing Restraining Factor:


Access control and experience of the cloud data warehouse are insufficient

While working with data warehouses, it's critical to define the framework of access control. In most circumstances, companies are unable to determine which departments and users require data warehouse access. When users are not balanced and permissions are not granted, the system becomes overburdened, resulting in delays that cannot be avoided. A major lack of appropriate access control and sensitive information might be obtained by unauthorized people, resulting in a significant loss of corporate growth. As a result, the installation of data warehouses requires a well-defined access control mechanism.



Type Outlook

Based on Type, the market is segmented into Enterprise DWaaS and Operational Data Storage. The operational data storage segment registered a significant revenue share in the Cloud Datawarehouse Market in 2021. The level of real data tracking and data is primarily responsible for the increase. ODS supports an organization's existing data architecture while also supporting the organization's current and future demands. Moreover, the increasing usage of artificial intelligence (AI) in data stores is expected to generate future growth potentials for the ODS industry. Companies in the Cloud Datawarehouse market offer cutting-edge solutions to keep up with the rapid development of data quantities while also adhering to regulatory compliance requirements.

Application Outlook

Based on Application, the market is segmented into Customer Analytics, Business Intelligence, Predictive Analytics, Data Modernization, and Others. The Customer Analytics segment acquired the highest revenue share in the Cloud Datawarehouse Market in 2021. Companies establish a cleaner, more accurate image of what actions need to be made inside their business by storing all data within a CDW and attaching analytics and BI tools directly to it. A CDW removes the need for product and development marketing teams to explore different data repositories in order to uncover useful information. This centralized source ensures data integrity and provides a more actionable picture of all client data coming in from diverse sources. Organizations is expected to need to acquire data in a variety of methods to gain the most comprehensive picture of each consumer contact. The CDW is becoming the gateway, a single point of truth where structured data is expected to be accessed. When the similar data is stored in several places, it opens up the possibility of mistakes in the data that various teams use to make choices.

Deployment Model Outlook

Based on Deployment Model, the market is segmented into Public and Private. The private segment recorded a substantial revenue share in the Cloud Datawarehouse Market in 2021. The Cloud data Warehouse Private Cloud solution allows teams of industry experts to self-serve the building of autonomous data warehouses marts without the expense of bare-metal installations. All data is kept in Hadoop Distributed File System in the Cloud data Warehouse Private Cloud service's base cluster which boost the growth of the Cloud datawarehouse market in the private sector.

Organization Size Outlook

Based on Organization Size, the market is segmented into Large Enterprises and Small & Medium Enterprises. The Large enterprise segment garnered the largest revenue share in the Cloud Datawarehouse Market in 2021. Large organizations are increasingly adopting personal cloud Data Warehouses built on No SQL-enabled storage, which provides security as well as other benefits like decreased infrastructure deployment and administrative overheads. Enterprises can develop cloud-based apps and solutions using cloud virtualization technologies, tools, and data warehouses.

Vertical Outlook

Based on Vertical, the market is segmented into BFSI, IT & Telecom, Retail & E-commerce, Government, Healthcare & Life Sciences, Manufacturing, Media & Entertainment, Energy & Utilities, and Others. Healthcare and life sciences registered the substantial revenue share in the Cloud Datawarehouse Market in 2021. Healthcare and life sciences are one of the quickest verticals, due to the industry's rapid development and technological breakthroughs, which are strengthening the whole industry vertical. The importance of information quality and the need for high-grade medical administrations has grown in recent years. The usage of Cloud Datawarehouse solutions in the healthcare sector was initially gradual due to data complexity and a variety of medical and clinical data.However, the increased use of Cloud Datawarehouse solutions in recent years has proven to be beneficial in administrative and clinical settings. The massive volumes of data acquired throughout the years have been put to several uses, ranging from improving patient health to testing medications.

Regional Outlook

Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa. North America registered the highest revenue share in the Cloud Datawarehouse Market in 2021. A significant number of people have shifted to remote employment. In addition, Canada's industries have been majorly benefitted from digitalization. While the evidence does not prove a causal link, it does show that digitalization is linked to increased labor productivity growth.

Cloud Datawarehouse Market Competition Analysis



The major strategies followed by the market participants are Partnerships. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Cloud Datawarehouse Market. Companies such as Amazon Web Services, Inc., Oracle Corporation, and IBM Corporation are some of the key innovators in the Market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services, Inc., IBM Corporation, Microsoft Corporation, Google LLC, Oracle Corporation, SAP SE, Micro Focus International PLC, Teradata Corporation, Cloudera, Inc., and Snowflake, Inc.

Recent Strategies Deployed in Cloud Datawarehouse Market


Partnerships, Collaborations and Agreements:

  • Mar-2022: Google Cloud joined hands with Mahindra Group, an Indian multinational conglomerate. Through this collaboration, Mahindra Digital Engine is expected to use Google Cloud's protected and dependable architecture and advanced data analytics technology.
  • Feb-2022: Microsoft Azure extended its partnership with Teradata, an American software company. Through this expansion, Azure aimed to combine Azure Synapse Analytics along with 60 other Azure data services within Teradatas" Vantage to co-op with challengers.
  • Nov-2021: Amazon Web Services joined hands with Goldman Sachs, an American multinational investment bank and financial services company. Together, the companies aimed to launch Goldman Sachs Financial Cloud for Data to minimize the desire for investment enterprises to design and preserve foundational data-combination technology and lower the blockade to entry for ascertaining advanced observational analytics around international markets.
  • Nov-2021: Oracle extended its partnership with Bharti Airtel, India's premier communications solutions provider. Through this partnership, the companies aimed to support the advancement of India's digital economy by providing a variety of organization-leading cloud solutions to more than 1 million organization consumers. Additionally, the companies is expected to jointly market Oracle Cloud solutions to organizational consumers in the public and private sectors.
  • Nov-2021: Vertica came into a partnership with NetApp StorageGRID, software-defined object storage. This partnership aimed to provide enterprises the independence to adopt cloud innovation for analytics wherever data consist, without presuming the price, threats, and complication of cloud migration.
  • Jul-2021: Cloudera signed an agreement with Alibaba Cloud, the digital technology and intellectual backbone of Alibaba Group. Through this agreement, Cloudera aimed at the general accessibility of Cloudera Data Platform on Alibaba Cloud in the Greater China Region to allow consumers to gain the full advantages of the cloud and fulfill enterprise demand.
  • Jul-2021: IBM joined hands with SAP SE, a German multinational software corporation. Through this collaboration, SAP aimed to launch SAP's finance and data management solutions within IBM Cloud for Financial Services to help propel IBM cloud fostering within the financial services organization. Additionally, collaboration is expected to be developed to assist the enterprise address the organization's security, strict conformity, and flexibility conditions, while supporting business up-gradation and innovation for the financial services academy.
  • May-2021: Google Cloud signed a six-year strategic partnership with Vodafone, a British multinational telecommunications company. Through this partnership, the companies aimed to expand their current efforts to develop an appropriated, big data platform to support the telco giant's ongoing digital up-gradation attempt. This partnership is expected to witness the pair work to bring additional functionality to the platform, called Nucleus, and is expected to result in Vodafone migrating its SAP surroundings and other assorted business intelligence workloads to the Google Cloud.
  • Apr-2021: Cloudera joined hands with NVIDIA, an American multinational technology company. Through this acquisition, the companies aimed to combine RAPIDS Accelerator for Apache Spark 3.0. to provide the organization the capabilities to rapidly answer to growing and ongoing enterprise tasks and provide insightful analytics. Additionally, this combination is expected to entitle the use of data-driven intuition to power mission-critical use cases such as scam disclosure.  
  • Oct-2020: IBM joined hands with Vodafone Idea, an Indian telecom operator. Under this collaboration, IBM is expected to leverage VIL to convert the way data is enhanced and delivered to employees, partners, and interior systems. Additionally, depository and fragmented data can now be assigned for seamless data accessibility.
  • Aug-2020: Google Cloud extended its partnership with Informatica, the enterprise cloud data management leader. Under this expansion, the companies is expected to introduce a new joint go-to-market initiative to boost analytics with BigQuery and SAP on Google Cloud. This latest CDC support for BigQuery is expected to also further allow companies utilizing Google Cloud to easily improve their data warehouses with BigQuery including Informatica's industry-leading tools.
  • Mar-2020: Microsoft came into a partnership with Cisco, an American multinational technology conglomerate corporation. Through this partnership, the companies aimed to allow real-time action of data from the IoT edge and give consumers the chance to unlock enterprise worth from data.      

Product Expansions and Product Launches:

  • Aug-2021: Cloudera introduced Cloudera DataFlow for the Public Cloud, a cloud-native service for data flows to process hybrid streaming workloads. Through this launch, consumers can automatize complicated data flow workload to propel the running ability of streaming data flows with auto-scaling abilities, and reduce cloud price by deleting architecture sizing work.
  • Apr-2021: IBM unveiled IBM Spectrum Fusion, storage portfolio. The solution is developed to combine IBM's general parallel file system technology and its data protection software to give enterprises and applications easy and less complicated access to ascertain data seamlessly within the data center, at the edge, and around the hybrid cloud ecosystem.
  • Mar-2021: Oracle introduced a set of innovative improvements to Oracle Autonomous Data Warehouse. The improved solution offers a single data platform built for enterprises to transform, ingest, store, and govern all data to run various analytical workloads from any source enterprise adding data warehouses, departmental systems, and data lakes.
  • Oct-2020: Micro Focus unveiled ITOM “Collect Once Store Once” Data Lake. COSO provides extraordinary storage and collection abilities built on Vertica's powerful, rapid data analytics platform. Additionally, COSO employs a data platform to propel full-stack AIOps around the wide set of Micro Focus automation and observance solutions.
  • Sep-2020: Cloudera introduced analytic experiences. These services provide data specialists like analysts, data engineers, and scientists. Additionally, the Enterprise data cloud services combine CDP Operational Database, CDP Data Engineering, and CDP Data Visualization.
  • Aug-2020: Cloudera unveiled Cloudera Data Platform Private Cloud. The solution offers authoritative container-based administration tools that minimize the time to supply analytics and machine learning within weeks to minutes. Additionally, CDP Private Cloud also changes data center economics with container-based machine and analytics learning to help minimize data center prices.
  • Mar-2020: Micro Focus introduced Vertica 10 Analytics Platform. The solution provides a profound combination of TensorFlow and Python for unconquered learning and PMML standard model format for multiplatform adaptability. Moreover, through this combination, scientists can use larger numbers of data and complement performance benefits to enhance replicability and precision.

Acquisitions and Mergers:

  • Jun-2021: Cloudera took over Datacoral along with Cazena. This acquisition aimed to embrace a new generation of no-code, low-code self-service by automatic complicated operations, allowing consumers to aim at achieving value from data rather than operating configuring, and controlling the underlying architecture. Additionally, the acquisition is expected to allow the consumer to enjoy a reduced complication and quick worth for data actions, quick innovation, stronger engagements, and enhanced insights. 
  • Dec-2020: Google's Google Cloud took over Dataform, a startup in the U.K. Dataform uses BigQuery's innovative infrastructure enabling for approximately unlimited scale, to allow analysts and engineers to control all their data procedures within BigQuery.
  • Jun-2020: Microsoft Corporation took over ADRM Software, a leading provider of large-scale industry data models. Through this acquisition, the company aimed to integrate ADRM with endless computing and storage from Azure enable for the formation of the intelligent data lake where data from various lines of enterprise can cooperate more rapidly.
  • Feb-2020: AWS took over DataRow, a unique player in the data exploration realm. Through this acquisition, AWS is expected to allow companies to provide consumers with better AWS decisions and inquiry decisions. Additionally, AWS consumers is expected to take benefit from quick to load data, author issues, perform visual analysis, collaborate with others to share SQL code, analysis, and results, and Build an easy-to-use interface to develop tables from DataRow.
  • Feb-2020: Google Cloud completed its acquisition with Looker, an American computer software company. This acquisition aimed to reinforce Google Cloud's analytics and data warehouse abilities including BigQuery, allowing consumers to address their hardest enterprise challenges, faster while enduring entire control of data.

Scope of the Study


Market Segments Covered in the Report:


By Type
  • Enterprise DWaaS
  • Operational Data Storage
By Application
  • Customer Analytics
  • Business Intelligence
  • Predictive Analytics
  • Data Modernization
  • Others
By Deployment Model
  • Public
  • Private
By Organization Size
  • Large Enterprises
  • Small & Medium Enterprises
By Vertical
  • BFSI
  • IT & Telecom
  • Retail & E-commerce
  • Government
  • Healthcare & Life Sciences
  • Manufacturing
  • Media & Entertainment
  • Energy & Utilities
  • Others

By Geography

  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players


List of Companies Profiled in the Report:

  • Amazon Web Services, Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • Oracle Corporation
  • SAP SE
  • Micro Focus International PLC
  • Teradata Corporation
  • Cloudera, Inc.
  • Snowflake, Inc.

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Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Cloud Datawarehouse Market, by Type
1.4.2 Global Cloud Datawarehouse Market, by Application
1.4.3 Global Cloud Datawarehouse Market, by Deployment Model
1.4.4 Global Cloud Datawarehouse Market, by Organization Size
1.4.5 Global Cloud Datawarehouse Market, by Vertical
1.4.6 Global Cloud Datawarehouse Market, by Geography
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Market Share Analysis, 2020
3.4 Top Winning Strategies
3.4.1 Key Leading Strategies: Percentage Distribution (2018-2022)
3.4.2 Key Strategic Move: (Partnerships, Collaborations, and Agreements: 2019, Jun - 2022, Mar) Leading Players
Chapter 4. Global Cloud Datawarehouse Market by Type
4.1 Global Enterprise DWaaS Market by Region
4.2 Global Operational Data Storage Market by Region
Chapter 5. Global Cloud Datawarehouse Market by Application
5.1 Global Customer Analytics Market by Region
5.2 Global Business Intelligence Market by Region
5.3 Global Predictive Analytics Market by Region
5.4 Global Data Modernization Market by Region
5.5 Global Others Market by Region
Chapter 6. Global Cloud Datawarehouse Market by Deployment Model
6.1 Global Public Market by Region
6.2 Global Private Market by Region
Chapter 7. Global Cloud Datawarehouse Market by Organization Size
7.1 Global Large Enterprises Market by Region
7.2 Global Small & Medium Enterprises Market by Region
Chapter 8. Global Cloud Datawarehouse Market by Vertical
8.1 Global BFSI Market by Region
8.2 Global IT & Telecom Market by Region
8.3 Global Retail & E-commerce Market by Region
8.4 Global Government Market by Region
8.5 Global Healthcare & Life Sciences Market by Region
8.6 Global Manufacturing Market by Region
8.7 Global Media & Entertainment Market by Region
8.8 Global Energy & Utilities Market by Region
8.9 Global Others Market by Region
Chapter 9. Global Cloud Datawarehouse Market by Region
9.1 North America Cloud Datawarehouse Market
9.1.1 North America Cloud Datawarehouse Market by Type
9.1.1.1 North America Enterprise DWaaS Market by Country
9.1.1.2 North America Operational Data Storage Market by Country
9.1.2 North America Cloud Datawarehouse Market by Application
9.1.2.1 North America Customer Analytics Market by Country
9.1.2.2 North America Business Intelligence Market by Country
9.1.2.3 North America Predictive Analytics Market by Country
9.1.2.4 North America Data Modernization Market by Country
9.1.2.5 North America Others Market by Country
9.1.3 North America Cloud Datawarehouse Market by Deployment Model
9.1.3.1 North America Public Market by Country
9.1.3.2 North America Private Market by Country
9.1.4 North America Cloud Datawarehouse Market by Organization Size
9.1.4.1 North America Large Enterprises Market by Country
9.1.4.2 North America Small & Medium Enterprises Market by Country
9.1.5 North America Cloud Datawarehouse Market by Vertical
9.1.5.1 North America BFSI Market by Country
9.1.5.2 North America IT & Telecom Market by Country
9.1.5.3 North America Retail & E-commerce Market by Country
9.1.5.4 North America Government Market by Country
9.1.5.5 North America Healthcare & Life Sciences Market by Country
9.1.5.6 North America Manufacturing Market by Country
9.1.5.7 North America Media & Entertainment Market by Country
9.1.5.8 North America Energy & Utilities Market by Country
9.1.5.9 North America Others Market by Country
9.1.6 North America Cloud Datawarehouse Market by Country
9.1.6.1 US Cloud Datawarehouse Market
9.1.6.1.1 US Cloud Datawarehouse Market by Type
9.1.6.1.2 US Cloud Datawarehouse Market by Application
9.1.6.1.3 US Cloud Datawarehouse Market by Deployment Model
9.1.6.1.4 US Cloud Datawarehouse Market by Organization Size
9.1.6.1.5 US Cloud Datawarehouse Market by Vertical
9.1.6.2 Canada Cloud Datawarehouse Market
9.1.6.2.1 Canada Cloud Datawarehouse Market by Type
9.1.6.2.2 Canada Cloud Datawarehouse Market by Application
9.1.6.2.3 Canada Cloud Datawarehouse Market by Deployment Model
9.1.6.2.4 Canada Cloud Datawarehouse Market by Organization Size
9.1.6.2.5 Canada Cloud Datawarehouse Market by Vertical
9.1.6.3 Mexico Cloud Datawarehouse Market
9.1.6.3.1 Mexico Cloud Datawarehouse Market by Type
9.1.6.3.2 Mexico Cloud Datawarehouse Market by Application
9.1.6.3.3 Mexico Cloud Datawarehouse Market by Deployment Model
9.1.6.3.4 Mexico Cloud Datawarehouse Market by Organization Size
9.1.6.3.5 Mexico Cloud Datawarehouse Market by Vertical
9.1.6.4 Rest of North America Cloud Datawarehouse Market
9.1.6.4.1 Rest of North America Cloud Datawarehouse Market by Type
9.1.6.4.2 Rest of North America Cloud Datawarehouse Market by Application
9.1.6.4.3 Rest of North America Cloud Datawarehouse Market by Deployment Model
9.1.6.4.4 Rest of North America Cloud Datawarehouse Market by Organization Size
9.1.6.4.5 Rest of North America Cloud Datawarehouse Market by Vertical
9.2 Europe Cloud Datawarehouse Market
9.2.1 Europe Cloud Datawarehouse Market by Type
9.2.1.1 Europe Enterprise DWaaS Market by Country
9.2.1.2 Europe Operational Data Storage Market by Country
9.2.2 Europe Cloud Datawarehouse Market by Application
9.2.2.1 Europe Customer Analytics Market by Country
9.2.2.2 Europe Business Intelligence Market by Country
9.2.2.3 Europe Predictive Analytics Market by Country
9.2.2.4 Europe Data Modernization Market by Country
9.2.2.5 Europe Others Market by Country
9.2.3 Europe Cloud Datawarehouse Market by Deployment Model
9.2.3.1 Europe Public Market by Country
9.2.3.2 Europe Private Market by Country
9.2.4 Europe Cloud Datawarehouse Market by Organization Size
9.2.4.1 Europe Large Enterprises Market by Country
9.2.4.2 Europe Small & Medium Enterprises Market by Country
9.2.5 Europe Cloud Datawarehouse Market by Vertical
9.2.5.1 Europe BFSI Market by Country
9.2.5.2 Europe IT & Telecom Market by Country
9.2.5.3 Europe Retail & E-commerce Market by Country
9.2.5.4 Europe Government Market by Country
9.2.5.5 Europe Healthcare & Life Sciences Market by Country
9.2.5.6 Europe Manufacturing Market by Country
9.2.5.7 Europe Media & Entertainment Market by Country
9.2.5.8 Europe Energy & Utilities Market by Country
9.2.5.9 Europe Others Market by Country
9.2.6 Europe Cloud Datawarehouse Market by Country
9.2.6.1 Germany Cloud Datawarehouse Market
9.2.6.1.1 Germany Cloud Datawarehouse Market by Type
9.2.6.1.2 Germany Cloud Datawarehouse Market by Application
9.2.6.1.3 Germany Cloud Datawarehouse Market by Deployment Model
9.2.6.1.4 Germany Cloud Datawarehouse Market by Organization Size
9.2.6.1.5 Germany Cloud Datawarehouse Market by Vertical
9.2.6.2 UK Cloud Datawarehouse Market
9.2.6.2.1 UK Cloud Datawarehouse Market by Type
9.2.6.2.2 UK Cloud Datawarehouse Market by Application
9.2.6.2.3 UK Cloud Datawarehouse Market by Deployment Model
9.2.6.2.4 UK Cloud Datawarehouse Market by Organization Size
9.2.6.2.5 UK Cloud Datawarehouse Market by Vertical
9.2.6.3 France Cloud Datawarehouse Market
9.2.6.3.1 France Cloud Datawarehouse Market by Type
9.2.6.3.2 France Cloud Datawarehouse Market by Application
9.2.6.3.3 France Cloud Datawarehouse Market by Deployment Model
9.2.6.3.4 France Cloud Datawarehouse Market by Organization Size
9.2.6.3.5 France Cloud Datawarehouse Market by Vertical
9.2.6.4 Russia Cloud Datawarehouse Market
9.2.6.4.1 Russia Cloud Datawarehouse Market by Type
9.2.6.4.2 Russia Cloud Datawarehouse Market by Application
9.2.6.4.3 Russia Cloud Datawarehouse Market by Deployment Model
9.2.6.4.4 Russia Cloud Datawarehouse Market by Organization Size
9.2.6.4.5 Russia Cloud Datawarehouse Market by Vertical
9.2.6.5 Spain Cloud Datawarehouse Market
9.2.6.5.1 Spain Cloud Datawarehouse Market by Type
9.2.6.5.2 Spain Cloud Datawarehouse Market by Application
9.2.6.5.3 Spain Cloud Datawarehouse Market by Deployment Model
9.2.6.5.4 Spain Cloud Datawarehouse Market by Organization Size
9.2.6.5.5 Spain Cloud Datawarehouse Market by Vertical
9.2.6.6 Italy Cloud Datawarehouse Market
9.2.6.6.1 Italy Cloud Datawarehouse Market by Type
9.2.6.6.2 Italy Cloud Datawarehouse Market by Application
9.2.6.6.3 Italy Cloud Datawarehouse Market by Deployment Model
9.2.6.6.4 Italy Cloud Datawarehouse Market by Organization Size
9.2.6.6.5 Italy Cloud Datawarehouse Market by Vertical
9.2.6.7 Rest of Europe Cloud Datawarehouse Market
9.2.6.7.1 Rest of Europe Cloud Datawarehouse Market by Type
9.2.6.7.2 Rest of Europe Cloud Datawarehouse Market by Application
9.2.6.7.3 Rest of Europe Cloud Datawarehouse Market by Deployment Model
9.2.6.7.4 Rest of Europe Cloud Datawarehouse Market by Organization Size
9.2.6.7.5 Rest of Europe Cloud Datawarehouse Market by Vertical
9.3 Asia Pacific Cloud Datawarehouse Market
9.3.1 Asia Pacific Cloud Datawarehouse Market by Type
9.3.1.1 Asia Pacific Enterprise DWaaS Market by Country
9.3.1.2 Asia Pacific Operational Data Storage Market by Country
9.3.2 Asia Pacific Cloud Datawarehouse Market by Application
9.3.2.1 Asia Pacific Customer Analytics Market by Country
9.3.2.2 Asia Pacific Business Intelligence Market by Country
9.3.2.3 Asia Pacific Predictive Analytics Market by Country
9.3.2.4 Asia Pacific Data Modernization Market by Country
9.3.2.5 Asia Pacific Others Market by Country
9.3.3 Asia Pacific Cloud Datawarehouse Market by Deployment Model
9.3.3.1 Asia Pacific Public Market by Country
9.3.3.2 Asia Pacific Private Market by Country
9.3.4 Asia Pacific Cloud Datawarehouse Market by Organization Size
9.3.4.1 Asia Pacific Large Enterprises Market by Country
9.3.4.2 Asia Pacific Small & Medium Enterprises Market by Country
9.3.5 Asia Pacific Cloud Datawarehouse Market by Vertical
9.3.5.1 Asia Pacific BFSI Market by Country
9.3.5.2 Asia Pacific IT & Telecom Market by Country
9.3.5.3 Asia Pacific Retail & E-commerce Market by Country
9.3.5.4 Asia Pacific Government Market by Country
9.3.5.5 Asia Pacific Healthcare & Life Sciences Market by Country
9.3.5.6 Asia Pacific Manufacturing Market by Country
9.3.5.7 Asia Pacific Media & Entertainment Market by Country
9.3.5.8 Asia Pacific Energy & Utilities Market by Country
9.3.5.9 Asia Pacific Others Market by Country
9.3.6 Asia Pacific Cloud Datawarehouse Market by Country
9.3.6.1 China Cloud Datawarehouse Market
9.3.6.1.1 China Cloud Datawarehouse Market by Type
9.3.6.1.2 China Cloud Datawarehouse Market by Application
9.3.6.1.3 China Cloud Datawarehouse Market by Deployment Model
9.3.6.1.4 China Cloud Datawarehouse Market by Organization Size
9.3.6.1.5 China Cloud Datawarehouse Market by Vertical
9.3.6.2 Japan Cloud Datawarehouse Market
9.3.6.2.1 Japan Cloud Datawarehouse Market by Type
9.3.6.2.2 Japan Cloud Datawarehouse Market by Application
9.3.6.2.3 Japan Cloud Datawarehouse Market by Deployment Model
9.3.6.2.4 Japan Cloud Datawarehouse Market by Organization Size
9.3.6.2.5 Japan Cloud Datawarehouse Market by Vertical
9.3.6.3 India Cloud Datawarehouse Market
9.3.6.3.1 India Cloud Datawarehouse Market by Type
9.3.6.3.2 India Cloud Datawarehouse Market by Application
9.3.6.3.3 India Cloud Datawarehouse Market by Deployment Model
9.3.6.3.4 India Cloud Datawarehouse Market by Organization Size
9.3.6.3.5 India Cloud Datawarehouse Market by Vertical
9.3.6.4 South Korea Cloud Datawarehouse Market
9.3.6.4.1 South Korea Cloud Datawarehouse Market by Type
9.3.6.4.2 South Korea Cloud Datawarehouse Market by Application
9.3.6.4.3 South Korea Cloud Datawarehouse Market by Deployment Model
9.3.6.4.4 South Korea Cloud Datawarehouse Market by Organization Size
9.3.6.4.5 South Korea Cloud Datawarehouse Market by Vertical
9.3.6.5 Singapore Cloud Datawarehouse Market
9.3.6.5.1 Singapore Cloud Datawarehouse Market by Type
9.3.6.5.2 Singapore Cloud Datawarehouse Market by Application
9.3.6.5.3 Singapore Cloud Datawarehouse Market by Deployment Model
9.3.6.5.4 Singapore Cloud Datawarehouse Market by Organization Size
9.3.6.5.5 Singapore Cloud Datawarehouse Market by Vertical
9.3.6.6 Malaysia Cloud Datawarehouse Market
9.3.6.6.1 Malaysia Cloud Datawarehouse Market by Type
9.3.6.6.2 Malaysia Cloud Datawarehouse Market by Application
9.3.6.6.3 Malaysia Cloud Datawarehouse Market by Deployment Model
9.3.6.6.4 Malaysia Cloud Datawarehouse Market by Organization Size
9.3.6.6.5 Malaysia Cloud Datawarehouse Market by Vertical
9.3.6.7 Rest of Asia Pacific Cloud Datawarehouse Market
9.3.6.7.1 Rest of Asia Pacific Cloud Datawarehouse Market by Type
9.3.6.7.2 Rest of Asia Pacific Cloud Datawarehouse Market by Application
9.3.6.7.3 Rest of Asia Pacific Cloud Datawarehouse Market by Deployment Model
9.3.6.7.4 Rest of Asia Pacific Cloud Datawarehouse Market by Organization Size
9.3.6.7.5 Rest of Asia Pacific Cloud Datawarehouse Market by Vertical
9.4 LAMEA Cloud Datawarehouse Market
9.4.1 LAMEA Cloud Datawarehouse Market by Type
9.4.1.1 LAMEA Enterprise DWaaS Market by Country
9.4.1.2 LAMEA Operational Data Storage Market by Country
9.4.2 LAMEA Cloud Datawarehouse Market by Application
9.4.2.1 LAMEA Customer Analytics Market by Country
9.4.2.2 LAMEA Business Intelligence Market by Country
9.4.2.3 LAMEA Predictive Analytics Market by Country
9.4.2.4 LAMEA Data Modernization Market by Country
9.4.2.5 LAMEA Others Market by Country
9.4.3 LAMEA Cloud Datawarehouse Market by Deployment Model
9.4.3.1 LAMEA Public Market by Country
9.4.3.2 LAMEA Private Market by Country
9.4.4 LAMEA Cloud Datawarehouse Market by Organization Size
9.4.4.1 LAMEA Large Enterprises Market by Country
9.4.4.2 LAMEA Small & Medium Enterprises Market by Country
9.4.5 LAMEA Cloud Datawarehouse Market by Vertical
9.4.5.1 LAMEA BFSI Market by Country
9.4.5.2 LAMEA IT & Telecom Market by Country
9.4.5.3 LAMEA Retail & E-commerce Market by Country
9.4.5.4 LAMEA Government Market by Country
9.4.5.5 LAMEA Healthcare & Life Sciences Market by Country
9.4.5.6 LAMEA Manufacturing Market by Country
9.4.5.7 LAMEA Media & Entertainment Market by Country
9.4.5.8 LAMEA Energy & Utilities Market by Country
9.4.5.9 LAMEA Others Market by Country
9.4.6 LAMEA Cloud Datawarehouse Market by Country
9.4.6.1 Brazil Cloud Datawarehouse Market
9.4.6.1.1 Brazil Cloud Datawarehouse Market by Type
9.4.6.1.2 Brazil Cloud Datawarehouse Market by Application
9.4.6.1.3 Brazil Cloud Datawarehouse Market by Deployment Model
9.4.6.1.4 Brazil Cloud Datawarehouse Market by Organization Size
9.4.6.1.5 Brazil Cloud Datawarehouse Market by Vertical
9.4.6.2 Argentina Cloud Datawarehouse Market
9.4.6.2.1 Argentina Cloud Datawarehouse Market by Type
9.4.6.2.2 Argentina Cloud Datawarehouse Market by Application
9.4.6.2.3 Argentina Cloud Datawarehouse Market by Deployment Model
9.4.6.2.4 Argentina Cloud Datawarehouse Market by Organization Size
9.4.6.2.5 Argentina Cloud Datawarehouse Market by Vertical
9.4.6.3 UAE Cloud Datawarehouse Market
9.4.6.3.1 UAE Cloud Datawarehouse Market by Type
9.4.6.3.2 UAE Cloud Datawarehouse Market by Application
9.4.6.3.3 UAE Cloud Datawarehouse Market by Deployment Model
9.4.6.3.4 UAE Cloud Datawarehouse Market by Organization Size
9.4.6.3.5 UAE Cloud Datawarehouse Market by Vertical
9.4.6.4 Saudi Arabia Cloud Datawarehouse Market
9.4.6.4.1 Saudi Arabia Cloud Datawarehouse Market by Type
9.4.6.4.2 Saudi Arabia Cloud Datawarehouse Market by Application
9.4.6.4.3 Saudi Arabia Cloud Datawarehouse Market by Deployment Model
9.4.6.4.4 Saudi Arabia Cloud Datawarehouse Market by Organization Size
9.4.6.4.5 Saudi Arabia Cloud Datawarehouse Market by Vertical
9.4.6.5 South Africa Cloud Datawarehouse Market
9.4.6.5.1 South Africa Cloud Datawarehouse Market by Type
9.4.6.5.2 South Africa Cloud Datawarehouse Market by Application
9.4.6.5.3 South Africa Cloud Datawarehouse Market by Deployment Model
9.4.6.5.4 South Africa Cloud Datawarehouse Market by Organization Size
9.4.6.5.5 South Africa Cloud Datawarehouse Market by Vertical
9.4.6.6 Nigeria Cloud Datawarehouse Market
9.4.6.6.1 Nigeria Cloud Datawarehouse Market by Type
9.4.6.6.2 Nigeria Cloud Datawarehouse Market by Application
9.4.6.6.3 Nigeria Cloud Datawarehouse Market by Deployment Model
9.4.6.6.4 Nigeria Cloud Datawarehouse Market by Organization Size
9.4.6.6.5 Nigeria Cloud Datawarehouse Market by Vertical
9.4.6.7 Rest of LAMEA Cloud Datawarehouse Market
9.4.6.7.1 Rest of LAMEA Cloud Datawarehouse Market by Type
9.4.6.7.2 Rest of LAMEA Cloud Datawarehouse Market by Application
9.4.6.7.3 Rest of LAMEA Cloud Datawarehouse Market by Deployment Model
9.4.6.7.4 Rest of LAMEA Cloud Datawarehouse Market by Organization Size
9.4.6.7.5 Rest of LAMEA Cloud Datawarehouse Market by Vertical
Chapter 10. Company Profiles
10.1 IBM Corporation
10.1.1 Company Overview
10.1.2 Financial Analysis
10.1.3 Regional & Segmental Analysis
10.1.4 Research & Development Expenses
10.1.5 Recent strategies and developments:
10.1.5.1 Partnerships, Collaborations, and Agreements:
10.1.5.2 Product Launches and Product Expansions:
10.1.6 SWOT Analysis
10.2 Micro Focus International PLC
10.2.1 Company Overview
10.2.2 Financial Analysis
10.2.3 Regional Analysis
10.2.4 Research & Development Expenses
10.2.5 Recent strategies and developments:
10.2.5.1 Partnerships, Collaborations, and Agreements:
10.2.5.2 Product Launches and Product Expansions:
10.3 Amazon Web Services, Inc.
10.3.1 Company Overview
10.3.2 Financial Analysis
10.3.3 Segmental and Regional Analysis
10.3.4 Recent strategies and developments:
10.3.4.1 Partnerships, Collaborations, and Agreements:
10.3.4.2 Product Launches and Product Expansions:
10.4 Microsoft Corporation
10.4.1 Company Overview
10.4.2 Financial Analysis
10.4.3 Segmental and Regional Analysis
10.4.4 Research & Development Expenses
10.4.5 Recent strategies and developments:
10.4.5.1 Partnerships, Collaborations, and Agreements:
10.4.5.2 Product Launches and Product Expansions:
10.4.5.3 Acquisition and Mergers:
10.5 Google LLC
10.5.1 Company Overview
10.5.2 Financial Analysis
10.5.3 Segmental and Regional Analysis
10.5.4 Research & Development Expense
10.5.5 Recent strategies and developments:
10.5.5.1 Partnerships, Collaborations, and Agreements:
10.5.5.2 Acquisition and Mergers:
10.5.6 SWOT Analysis
10.6 Oracle Corporation
10.6.1 Company Overview
10.6.2 Financial Analysis
10.6.3 Segmental and Regional Analysis
10.6.4 Research & Development Expense
10.6.5 Recent strategies and developments:
10.6.5.1 Partnerships, Collaborations, and Agreements:
10.6.5.2 Product Launches and Product Expansions:
10.6.6 SWOT Analysis
10.7 Cloudera, Inc.
10.7.1 Company Overview
10.7.2 Financial Analysis
10.7.3 Segmental Analysis
10.7.4 Research & Development Expense
10.7.5 Recent strategies and developments:
10.7.5.1 Partnerships, Collaborations, and Agreements:
10.7.5.2 Product Launches and Product Expansions:
10.7.5.3 Acquisition and Mergers:
10.8 SAP SE
10.8.1 Company Overview
10.8.2 Financial Analysis
10.8.3 Segmental and Regional Analysis
10.8.4 Research & Development Expense
10.8.5 SWOT Analysis
10.9 Teradata Corporation
10.9.1 Company Overview
10.9.2 Financial Analysis
10.9.3 Regional Analysis
10.9.4 Research & Development Expense
10.9.5 SWOT Analysis
10.10. Snowflake, Inc.
10.10.1 Company Overview
10.10.2 Financial Analysis
10.10.3 Regional Analysis
10.10.4 Research & Development Expenses

Companies Mentioned

  • Amazon Web Services, Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • Oracle Corporation
  • SAP SE
  • Micro Focus International PLC
  • Teradata Corporation
  • Cloudera, Inc.
  • Snowflake, Inc.

Methodology

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