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Cloud Data Warehouse Market Report Scope & Overview:

Cloud Data Warehouse Market Revenue Analysis

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The Cloud Data Warehouse Market size was valued at USD 6.96 billion in 2023 and will reach USD 47.79 billion by 2032 and grow at a CAGR of 23.87% by 2024-2032

A database that is maintained and configured for scalable BI (business intelligence) and analytics is referred to as a cloud data warehouse. A business cloud data warehouse is another name for it. A cloud data warehouse compiles and organizes data from various sources. A relational database utilized for analysis and query processing is called a cloud data warehouse. Customers are given access to data storage, replication, and automatic data backups through a cloud data warehouse; going forward, these elements will fuel market expansion. The information is useful for both large businesses, including e-commerce solution providers, and small and medium-sized businesses in particular for the expansion of their operations.

It provides the customer with data storage, automatic data backups, and replication and also Cloud Data Warehouse makes the data secure and reliable.

Market Dynamics:

Drivers:

  • Consistently expanding the role of business intelligence and data analytics in enterprise management.

  • Continuously increasing the use of IoT-connected devices.

  • Dependence on data-driven decision-making is Growing for improving business performance.

It is impossible to perform analytics and business intelligence without a data warehouse solution. Business intelligence is the capacity to provide comprehensive answers, and these understandings can be applied to make well-informed decisions. As the foundation for storage in business intelligence, a data warehouse is used. Data collection, data analysis, and data storage are all part of business intelligence. The adoption of BI has grown as a result of the introduction of cloud services. Dashboard, data visualization, BI/OLAP tools, and analytics are some of a BI solution's key features. To generate meaningful insights from the exponential rise of data, one needs effective data analytics. BI technologies are often used to provide firms with better data classifications and reporting. Thus, the need for data warehouses is being driven by the growing use of BI tools.

Restrains:

  • Increasing cybersecurity threats and the unavailability of professionals are reducing market growth.

Opportunities:

  • Large-scale cloud data warehouse having rapid deployment.

  • The adoption of virtual data warehousing is increasing to speed up the data access process.

Challenges:

While working with data warehouses, it is crucial to define the access control framework. Businesses frequently struggle to decide which users and departments need access to the data warehouse. Without balancing users and issuing rights, the system is put under heavy demand that inevitably leads to restriction. Without adequate access control, sensitive data may become accessible to unauthorized people, severely hampering the expansion of the business. Consequently, the deployment of data warehouses requires a clearly defined access control mechanism.

Impact Of covid-19:

The report provides the COVID-19 pandemic's effects on the market in detail. The pandemic has positive effect on the market for cloud data warehouses. It has become more challenging for businesses to run as a result of the COVID-19 pandemic and the rise of remote work environments. The impact of COVID-19 on the most recent economic downturn emphasizes the need for alternate business strategies. Now more than ever, business owners must adopt cloud computing and migrate their data warehouses there. In the short term, this will help businesses maintain a stable business climate while pursuing long-term growth and expansion. Data warehouse services are being used by businesses in a variety of industries due to their improved availability, reduced latency, scalability, and enterprise-grade security, among other benefits.

Key Market Segmentation:

By application:

  • Business Intelligence

  • Customer Analytics

  • Data Modernization

  • Operational Analytics

  • Predictive Analytics

By type:

  • Enterprise DWaaS

  • Operational data storage

By deployment model:

  • Public cloud

  • Private Cloud

By organization size:

  • Large Enterprises

  • SMEs

By Vertical:

  • BFSI

  • Energy and utilities

  • Government and public sector

  • Healthcare and life sciences

  • IT and ITeS

  • Manufacturing

  • Media and Entertainment

  • Retail and consumer goods

  • Telecommunications

  • Others

Regional Analysis:

In the APAC area, there is an increasing need for cloud-driven and cloud-supported Cloud Data Warehouses, which has sparked investment and led to technological advancements in a variety of industries.  Manufacturing is the biggest industry vertical in the APAC region, followed by retail, e-commerce, and BFSI. As a result of international competition, lower operational costs, and improved productivity have become major difficulties for local firms; these problems must be quickly overcome to retain market competitiveness. Businesses in this area continue to focus on improving customer service in order to stand out from the competition and improve their income. The need for hosted and cloud alternatives to on-premises Cloud Data Warehouse solutions is forcing enterprises to do so. The top three nations are China, Japan, and Australia, and New Zealand (ANZ).

In the regional analysis study of the regions of North America, Europe, Asia Pacific middle east, and Africa.

Cloud-Data-Warehouse-Market-Regional-Analysis--2023

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REGIONAL COVERAGE:

North America

  • USA

  • Canada

  • Mexico

Europe

  • Germany

  • UK

  • France

  • Italy

  • Spain

  • The Netherlands

  • Rest of Europe

Asia-Pacific

  • Japan

  • South Korea

  • China

  • India

  • Australia

  • Rest of Asia-Pacific

The Middle East & Africa

  • Israel

  • UAE

  • South Africa

  • Rest of the Middle East & Africa

Latin America

  • Brazil

  • Argentina

  • Rest of Latin America

Key Players:

The major players of the market are Marklogic (US), IBM (US), Pivotal (US), Microsoft (US), Google (US), SAP(Germany), Snowflake (US), Micro Focus(UK), Teradata(US), 1010Data(US), Oracle (US),  Cloudera(US), Yellowbrick(US), Veeva Systems(US), AWS(US), Actian(US), Netavis Software(Austria), Solver(US), Accur8 Software(US), AtScale(US), Panoply(US), SingleStore(US), and Transwarp(China), and others in the final report

Recent Developments:

The Amazon Redshift query editor was made available by AWS, and it supports clusters with improved VPC routing. The query editor supports all node types and the query time-out limit increased from 10 minutes to 24 hours for queries with longer run times.

With the introduction of cloud studio, WPP and Microsoft announced a partnership to creatively alter content production.

Cloud Data Warehouse Market Report Scope:
Report Attributes Details
Market Size in 2023  USD 6.96 Bn
Market Size by 2032  USD 47.79 Bn
CAGR   CAGR of 23.87% From 2024 to 2032
Base Year  2023
Forecast Period  2024-2032
Historical Data  2020-2022
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • By application (Business Intelligence, Customer Analytics, Data Modernization, Operational Analytics, Predictive Analytics)
• By type (Enterprise DWaaS, Operational data storage)
• By deployment model (Public cloud, Private cloud)
• By organization size (Large Enterprises, SMEs)
• By Vertical (BFSI, Energy and utilities, Government and public sector, Healthcare and life sciences, IT and ITeS, Manufacturing, Media, and Entertainment, Retail and consumer goods, Telecommunications, Others)
Regional Analysis/Coverage North America (USA, Canada, Mexico), Europe
(Germany, UK, France, Italy, Spain, Netherlands,
Rest of Europe), Asia-Pacific (Japan, South Korea,
China, India, Australia, Rest of Asia-Pacific), The
Middle East & Africa (Israel, UAE, South Africa,
Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America)
Company Profiles Marklogic(US), IBM(US), Pivotal(US), Microsoft (US), Google (US), SAP(Germany), Snowflake (US), Micro Focus(UK), Teradata(US), 1010Data(US), Oracle (US),  Cloudera(US), Yellowbrick(US), Veeva Systems(US), AWS(US), Actian(US), Netavis Software(Austria), Solver(US), Accur8 Software(US), AtScale(US), Panoply(US), SingleStore(US), and Transwarp(China)
Key Drivers • Consistently expanding the role of business intelligence and data analytics in enterprise management.
• Continuously increasing the use of IoT-connected devices.
Market Opportunities • Large-scale cloud data warehouse having rapid deployment.
• Adoption of virtual data warehousing is increasing to speed up the data access process.

 

Frequently Asked Questions

Ans: The Cloud Data Warehouse Market size was valued at US$ 6.96 billion in 2023.

The major worldwide key players in the Cloud Data Warehouse Market are AWS, IBM, Microsoft, Google, Oracle, SAP, Snowflake, Micro Focus, Teradata, 1010Data, Cloudera, Pivotal, Yellowbrick, Veeva Systems and other.

  • In enterprise management increasing the role of data analytics and business intelligence consistently.
  • Continuously increasing the use of IoT-connected devices.

The market is expected to grow to USD 47.79 billion by the forecast period of 2032.

Table of Contents

1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions

2. Research Methodology

3. Market Dynamics
3.1 Drivers
3.2 Restraints
3.3 Opportunities
3.4 Challenges

4. Impact Analysis
4.1 COVID-19 Impact Analysis
4.3 Impact of Ongoing Recession
4.3.1 Introduction
4.3.2 Impact on major economies
4.3.2.1 US
4.3.2.2 Canada
4.3.2.3 Germany
4.3.2.4 France
4.3.2.5 United Kingdom
4.3.2.6 China
4.3.2.7 japan
4.3.2.8 South Korea
4.3.2.9 Rest of the World

5. Value Chain Analysis

6. Porter’s 5 forces model

7. PEST Analysis

8. Cloud Data Warehouse Market Segmentation, by application
8.1 Business Intelligence
8.2 Customer Analytics
8.3 Data Modernization
8.4 Operational Analytics
8.5 Predictive Analytics

9. Cloud Data Warehouse Market Segmentation, by type
9.1 Enterprise DWaaS
9.2 Operational data storage

10. Cloud Data Warehouse Market Segmentation, by deployment model
10.1 Public cloud
10.2 Private cloud

11. Cloud Data Warehouse Market Segmentation, by organization size
11.1 Large Enterprises
11.2 SMEs

12. Cloud Data Warehouse Market Segmentation, by vertical
12.1 BFSI
12.2 Energy and utilities
12.3 Government and public sector
12.4 Healthcare and life sciences
12.5 IT and ITeS
12.6 Manufacturing
12.7 Media and Entertainment
12.8 Retail and consumer goods
12.9 Telecommunications
12.10 Others

13. Regional Analysis
13.1 Introduction
13.2 North America
13.2.1 North America Cloud Data Warehouse Market by country
13.2.2North America Cloud Data Warehouse Market by application
13.2.3 North America Cloud Data Warehouse Market by type
13.2.4 North America Cloud Data Warehouse Market by deployment model
13.2.5 North America Cloud Data Warehouse Market by organization size
13.2.6 North America Cloud Data Warehouse Market by vertical
13.2.7 USA
13.2.7.1 USA Cloud Data Warehouse Market by application
13.2.7.2 USA Cloud Data Warehouse Market by type
13.2.7.3 USA Cloud Data Warehouse Market by deployment model
13.2.7.4 USA Cloud Data Warehouse Market by organization size
13.2.7.5 USA Cloud Data Warehouse Market by vertical
13.2.8 Canada
13.2.8.1 Canada Cloud Data Warehouse Market by application
13.2.8.2 Canada Cloud Data Warehouse Market by type
13.2.8.3 Canada Cloud Data Warehouse Market by deployment model
13.2.8.4 Canada Cloud Data Warehouse Market by organization size
13.2.8.5 Canada Cloud Data Warehouse Market by vertical
13.2.9 Mexico
13.2.9.1 Mexico Cloud Data Warehouse Market by application
13.2.9.2 Mexico Cloud Data Warehouse Market by type
13.2.9.3 Mexico Cloud Data Warehouse Market by deployment model
13.2.9.4 Mexico Cloud Data Warehouse Market by organization size
13.2.9.5 Mexico Cloud Data Warehouse Market by vertical
13.3 Europe
13.3.1 Europe Cloud Data Warehouse Market by country
1.3.3.2 Europe Cloud Data Warehouse Market by application
13.3.3 Europe Cloud Data Warehouse Market by type
13.3.4 Europe Cloud Data Warehouse Market by deployment model
13.3.5 Europe Cloud Data Warehouse Market by organization size
13.3.6 Europe Cloud Data Warehouse Market by vertical
13.3.7 Germany
13.3.8.1 Germany Cloud Data Warehouse Market by application
13.3.8.2 Germany Cloud Data Warehouse Market by type
13.3.8.3 Germany Cloud Data Warehouse Market by deployment model
13.3.8.4 Germany Cloud Data Warehouse Market by organization size
13.3.8.5 Germany Cloud Data Warehouse Market by vertical
13.3.8 UK
13.3.8.1 UK Cloud Data Warehouse Market by application
13.3.8.2 UK Cloud Data Warehouse Market by type
13.3.8.3 UK Cloud Data Warehouse Market by deployment model
13.3.8.4 UK Cloud Data Warehouse Market by organization size
13.3.8.5 UK Cloud Data Warehouse Market by vertical
13.3.9 France
13.3.9.1 France Cloud Data Warehouse Market by application
13.3.9.2 France Cloud Data Warehouse Market by type
13.3.9.3 France Cloud Data Warehouse Market by deployment model
13.3.9.4 France Cloud Data Warehouse Market by organization size
13.3.9.5 France Cloud Data Warehouse Market by vertical
13.3.10 Italy
13.3.10.1 Italy Cloud Data Warehouse Market by application
13.3.10.2 Italy Cloud Data Warehouse Market by type
13.3.10.3 Italy Cloud Data Warehouse Market by deployment model
13.3.10.4 Italy Cloud Data Warehouse Market by organization size
13.3.10.5 Italy Cloud Data Warehouse Market by vertical
13.3.11 Spain
13.3.11.1 Spain Cloud Data Warehouse Market by application
13.3.11.2 Spain Cloud Data Warehouse Market by type
13.3.11.3 Spain Cloud Data Warehouse Market by deployment model
13.3.11.4 Spain Cloud Data Warehouse Market by organization size
13.3.11.5 Spain Cloud Data Warehouse Market by vertical
13.3.12 The Netherlands
13.3.12.1 Netherlands Cloud Data Warehouse Market by application
13.3.12.2 Netherlands Cloud Data Warehouse Market by type
13.3.12.3 Netherlands Cloud Data Warehouse Market by deployment model
13.3.12.4 Netherlands Cloud Data Warehouse Market by organization size
13.3.12.5 Netherlands Cloud Data Warehouse Market by vertical
13.3.13 Rest of Europe
13.3.13.1 Rest of Europe Cloud Data Warehouse Market by application
13.3.13.2 Rest of Europe Cloud Data Warehouse Market by type
13.3.13.3 Rest of Europe Cloud Data Warehouse Market by deployment model
13.3.13.4 Rest of Europe Cloud Data Warehouse Market by organization size
13.3.13.5 Rest of Europe Cloud Data Warehouse Market by vertical
13.4 Asia-Pacific
13.4.1 Asia Pacific Cloud Data Warehouse Market by country
13.4.2 Asia Pacific Cloud Data Warehouse Market by application
13.4.3 Asia Pacific Cloud Data Warehouse Market by type
13.4.4Asia Pacific Cloud Data Warehouse Market by deployment model
13.4.5Asia Pacific Cloud Data Warehouse Market by organization size
13.4.6 Asia Pacific Cloud Data Warehouse Market by vertical
13.4.7 Japan
13.4.7.1 Japan Cloud Data Warehouse Market by application
13.4.7.2 Japan Cloud Data Warehouse Market by type
13.4.7.3 Japan Cloud Data Warehouse Market by deployment model
13.4.7.4 Japan Cloud Data Warehouse Market by organization size
13.4.7. 5Japan Cloud Data Warehouse Market by vertical
13.4.8South Korea
13.4.8.1 South Korea Cloud Data Warehouse Market by application
13.4.8.2 South Korea Cloud Data Warehouse Market by type
13.4.8.3 South Korea Cloud Data Warehouse Market by deployment model
13.4.8.4 South Korea Cloud Data Warehouse Market by organization size
13.4.8.5 South Korea Cloud Data Warehouse Market by vertical
13.4.9 China
13.4.9.1 China Cloud Data Warehouse Market by application
13.4.9.2 China Cloud Data Warehouse Market by type
13.4.9.3 China Cloud Data Warehouse Market by deployment model
13.4.9.4 China Cloud Data Warehouse Market by organization size
13.4.9.5 China Cloud Data Warehouse Market by application
13.4.10 India
13.4.10.1 India Cloud Data Warehouse Market by application
13.4.10.2 India Cloud Data Warehouse Market by type
13.4.10.3 India Cloud Data Warehouse Market by deployment model
13.4.10.4 India Cloud Data Warehouse Market by organization size
13.4.10.5 India Cloud Data Warehouse Market by vertical
13.4.11 Australia
13.4.11.1 Australia Cloud Data Warehouse Market by application
13.4.11.2 Australia Cloud Data Warehouse Market by type
13.4.11.3 Australia Cloud Data Warehouse Market by deployment model
13.4.11.4 Australia Cloud Data Warehouse Market by organization size
13.4.11.5 Australia Cloud Data Warehouse Market by vertical
13.4.12 Rest of Asia-Pacific
13.4.12.1 APAC Cloud Data Warehouse Market by application
13.4.12.2 APAC Cloud Data Warehouse Market by type
13.4.12.3 APAC Cloud Data Warehouse Market by deployment model
13.4.12.4 APAC Cloud Data Warehouse Market by organization size
13.4.12.5 APAC Cloud Data Warehouse Market by vertical
13.5 The Middle East & Africa
13.5.1 The Middle East & Africa Cloud Data Warehouse Market by country
13.5.2 The Middle East & Africa Cloud Data Warehouse Market by application
13.5.3 The Middle East & Africa Cloud Data Warehouse Market by type
13.5.4The Middle East & Africa Cloud Data Warehouse Market by deployment model
13.5.5 The Middle East & Africa Cloud Data Warehouse Market by organization size
13.5.6The Middle East & Africa Cloud Data Warehouse Market by vertical
13.5.7 Israel
13.5.7.1 Israel Cloud Data Warehouse Market by application
13.5.7.2 Israel Cloud Data Warehouse Market by type
13.5.7.3 Israel Cloud Data Warehouse Market by deployment model
13.5.7.4 Israel Cloud Data Warehouse Market by organization size
13.5.7.5 Israel Cloud Data Warehouse Market by vertical
13.5.8 UAE
13.5.8.1 UAE Cloud Data Warehouse Market by application
13.5.8.2 UAE Cloud Data Warehouse Market by type
13.5.8.3 UAE Cloud Data Warehouse Market by deployment model
13.5.8.4 UAE Cloud Data Warehouse Market by organization size
13.5.8.5 UAE Cloud Data Warehouse Market by vertical
13.5.9South Africa
13.5.9.1 South Africa Cloud Data Warehouse Market by application
13.5.9.2 South Africa Cloud Data Warehouse Market by type
13.5.9.3 South Africa Cloud Data Warehouse Market by deployment model
13.5.9.4 South Africa Cloud Data Warehouse Market by organization size
13.5.9.5 South Africa Cloud Data Warehouse Market by vertical
13.5.10 Rest of Middle East & Africa
13.5.10.1 Rest of Middle East & Asia Cloud Data Warehouse Market by application
13.5.10.2 Rest of Middle East & Asia Cloud Data Warehouse Market by type
13.5.10.3 Rest of Middle East & Asia Cloud Data Warehouse Market by deployment model
13.5.10.4 Rest of Middle East & Asia Cloud Data Warehouse Market by organization size
13.5.10.5 Rest of Middle East & Asia Cloud Data Warehouse Market by vertical
13.6 Latin America
13.6.1 Latin America Cloud Data Warehouse Market by country
13.6.2 Latin America Cloud Data Warehouse Market by application
13.6.3 Latin America Cloud Data Warehouse Market by type
13.6.4 Latin America Cloud Data Warehouse Market by deployment model
13.6.5 Latin America Cloud Data Warehouse Market by organization size
13.6.6 Latin America Cloud Data Warehouse Market by vertical
13.6.7 Brazil
13.6.7.1 Brazil Cloud Data Warehouse Market by application
13.6.7.2 Brazil Africa Cloud Data Warehouse Market by type
13.6.7.3 Brazil Cloud Data Warehouse Market by deployment model
13.6.7.4 Brazil Cloud Data Warehouse Market by organization size
13.6.7.5 Brazil Cloud Data Warehouse Market by vertical
13.6.8 Argentina
13.6.8.1 Argentina Cloud Data Warehouse Market by application
13.6.8.2 Argentina Cloud Data Warehouse Market by type
13.6.8.3 Argentina Cloud Data Warehouse Market by deployment model
13.6.8.4 Argentina Cloud Data Warehouse Market by organization size
13.6.8.5 Argentina Cloud Data Warehouse Market by vertical
13.6.9 Rest of Latin America
13.6.9.1 Rest of Latin America Cloud Data Warehouse Market by application
13.6.9.2 Rest of Latin America Cloud Data Warehouse Market by type
13.6.9.3 Rest of Latin America Cloud Data Warehouse Market by deployment model
13.6.9.4 Rest of Latin America Cloud Data Warehouse Market by organization size
13.6.9.5 Rest of Latin America Cloud Data Warehouse Market by vertical

14. Company Profile
14.1 AWS
14.1.1 Market Overview
14.1.2 Financials
14.1.3 Product/Services/Offerings
14.1.4 SWOT Analysis
14.1.5 The SNS View
14.2 IBM.
14.2.1 Market Overview
14.2.2 Financials
14.2.3 Product/Services/Offerings
14.2.4 SWOT Analysis
14.2.5 The SNS View
14.3 Microsoft.
14.3.1 Market Overview
14.3.2 Financials
14.3.3 Product/Services/Offerings
14.3.4 SWOT Analysis
14.3.5 The SNS View
14.4 Google.
14.4.1 Market Overview
14.4.2 Financials
14.4.3 Product/Services/Offerings
14.4.4 SWOT Analysis
14.4.5 The SNS View
14.5 Oracle
14.5.1 Market Overview
14.5.2 Financials
14.5.3 Product/Services/Offerings
14.5.4 SWOT Analysis
14.5.5 The SNS View
14.6 SAP.
14.6.1 Market Overview
14.6.2 Financials
14.6.3 Product/Services/Offerings
14.6.4 SWOT Analysis
14.6.5 The SNS View
14.7 Micro Focus
14.7.1 Market Overview
14.7.2 Financials
14.7.3 Product/Services/Offerings
14.7.4 SWOT Analysis
14.7.5 The SNS View
14.8 Cloudera
14.8.1 Market Overview
14.8.2 Financials
14.8.3 Product/Services/Offerings
14.8.4 SWOT Analysis
14.8.5 The SNS View
14.9 Netavis Software
14.9.1 Market Overview
14.9.2 Financials
14.9.3 Product/Services/Offerings
14.9.4 SWOT Analysis
14.9.5 The SNS View
14.10 Panoply
14.10.1 Market Overview
14.10.2 Financials
14.10.3 Product/Services/Offerings
14.10.4 SWOT Analysis
14.10.5 The SNS View

15. Competitive Landscape
15.1 Competitive Benchmarking
15.2 Market Share Analysis
15.3 Recent Developments

16. USE Cases and Best Practices

17. Conclusion
 

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.

 

The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data.  This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.

We at SNS Insider have divided Primary Research into 2 parts.

Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.

This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Primary Research

Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.

Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.

Step 3: Data Bank Validation

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Data Bank Validation

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