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Global Data Pipeline Tools Market to reach USD 32.92 billion by the end of 2029

Global Data Pipeline Tools Market Size study & Forecast, By Component (Tools, Services), by Type ( ELT Data Pipeline, Real-Time Data Pipeline, Batch Data Pipeline), by deployment (On-Premise, Cloud), by Enterprise Size (Large Enterprises and Small and Medium Enterprise), by Application ( Real Time Analytics, Predictive Maintenance, Sales and Marketing Data, Customer Relationship Management, Data Traffic Management, Others), by End-Use (BFSI, Retail and E-commerce, IT and Telecom, Healthcare, Transportation and Logistics and Others) and Regional Analysis, 2022-2029

Product Code: ICTICTS-79189300
Publish Date: 10-04-2023
Page: 200

Global Data Pipeline Tools Market is valued at approximately USD 7.1 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 24.5% over the forecast period 2022-2029. Data extraction from a data source, data transformations, and data movement into one or more data storage sites are all made easier with the aid of data pipeline technologies. Each step in the data pipeline process can be completed using a variety of tools, which cover every part of it. The market is being driven by factors including the expansion of AI and ML implementation and adoption, as well as the expansion of IoT use.

According to the data published by, the State of IoT Spring 2022, with more than 12.2 billion active endpoints, the IoT connections have grown by 8.0% across the world as compared to the year 2021. Furthermore, as per Statista, the number of IoT connected devices would reach 29.42 million by year 2030. Thus, the rising adoption of IoT connected devices is catering to the market growth. Implementing 5G, lowering data latency, increasing demand for tools transporting data from disparate sources to the cloud or warehouse, and the growth of cloud computing are other significant factors causing space to expand. However, over the projected period of 2022-2029, data downtime and a lack of experience among workforces may restrain market expansion.

The key regions considered for the Global Data Pipeline Tools Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the market in terms of revenue, owing to high investments in AI technology and other advanced technologies. Whereas Asia Pacific is expected to grow with the highest CAGR during the forecast period, owing to factors such as rise in number of initiatives taken by various end-use industries for reducing the latency in this region.

Major market players included in this report are:
Hevo Data Inc.
SnapLogic Inc.
Amazon Web Services, Inc.
Actian Corporation
Software AG

Recent Developments in the Market:
 In June 2022, Snap Logic introduced Snap Logic Accelerator for Amazon Health Lake. It will make it possible for healthcare organisations to learn new information about healthcare. Additionally, it is anticipated to assist healthcare institutions in automating procedures and enhance the general patient experience.
 In May 2022, SoftServe entered into a partnership with Google Cloud to build the services, Manufacturing Data Engine, which is a comprehensive solution that analyses, contextualises, and manages industrial data on the premier data platform in the market, Google Cloud. A platform called Manufacturing Connect was developed at the factory edge in association with Litmus Automation. It quickly attaches to any industrial or manufacturing equipment and sends data from there to Google Cloud.

Global Data Pipeline Tools Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Component, Type, Deployment, Enterprise Size, Application, End-use, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Type offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:

By Type:
ELT Data Pipeline
Real-Time Data Pipeline
Batch Data Pipeline By Deployment: On-premise Cloud

By Enterprise Size:
Large Enterprises
Small and Medium Enterprise

By Application:
Real Time Analytics
Predictive Maintenance
Sales and Marketing Data
Customer Relationship Management
Data Traffic Management

By End-Use:
Retail and E-commerce
IT and Telecom
Transportation and Logistics

By Region:
North America
Asia Pacific
South Korea
Latin America
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Data Pipeline Tools Market, by Region, 2019-2029 (USD Billion)
1.2.2. Data Pipeline Tools Market, by Component, 2019-2029 (USD Billion)
1.2.3. Data Pipeline Tools Market, by Type, 2019-2029 (USD Billion)
1.2.4. Data Pipeline Tools Market, by Deployment, 2019-2029 (USD Billion)
1.2.5. Data Pipeline Tools Market, by Enterprise Size, 2019-2029 (USD Billion)
1.2.6. Data Pipeline Tools Market, by Application, 2019-2029 (USD Billion)
1.2.7. Data Pipeline Tools Market, by End-Use, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Data Pipeline Tools Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Data Pipeline Tools Market Dynamics
3.1. Data Pipeline Tools Market Impact Analysis (2019-2029)
3.1.1. Market Drivers Growth in the implementation and adoption of AI and ML Growth in adoption of Internet of things
3.1.2. Market Challenges Lack of expertise workforce Data downtime
3.1.3. Market Opportunities Implementation of 5G and reducing data latency
Chapter 4. Global Data Pipeline Tools Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Data Pipeline Tools Market, by Component
6.1. Market Snapshot
6.2. Global Data Pipeline Tools Market by Component, Performance – Potential Analysis
6.3. Global Data Pipeline Tools Market Estimates & Forecasts by Component 2019-2029 (USD Billion)
6.4. Data Pipeline Tools Market, Sub Segment Analysis
6.4.1. Tools
6.4.2. Services
Chapter 7. Global Data Pipeline Tools Market, by Type
7.1. Market Snapshot
7.2. Global Data Pipeline Tools Market by Type, Performance – Potential Analysis
7.3. Global Data Pipeline Tools Market Estimates & Forecasts by Type 2019-2029 (USD Billion)
7.4. Data Pipeline Tools Market, Sub Segment Analysis
7.4.1. ELT Data Pipeline
7.4.2. Real-Time Data Pipeline
7.4.3. Batch Data Pipeline
Chapter 8. Global Data Pipeline Tools Market, by Deployment
8.1. Market Snapshot
8.2. Global Data Pipeline Tools Market by Deployment, Performance – Potential Analysis
8.3. Global Data Pipeline Tools Market Estimates & Forecasts by Deployment 2019-2029 (USD Billion)
8.4. Data Pipeline Tools Market, Sub Segment Analysis
8.4.1. On-Premise
8.4.2. Cloud
Chapter 9. Global Data Pipeline Tools Market, by Enterprise Size
9.1. Market Snapshot
9.2. Global Data Pipeline Tools Market by Enterprise Size, Performance – Potential Analysis
9.3. Global Data Pipeline Tools Market Estimates & Forecasts by Enterprise Size 2019-2029 (USD Billion)
9.4. Data Pipeline Tools Market, Sub Segment Analysis
9.4.1. Large Enterprise
9.4.2. Small and Medium Enterprise
Chapter 10. Global Data Pipeline Tools Market, by Application
10.1. Market Snapshot
10.2. Global Data Pipeline Tools Market by Application, Performance – Potential Analysis
10.3. Global Data Pipeline Tools Market Estimates & Forecasts by Application 2019-2029 (USD Billion)
10.4. Data Pipeline Tools Market, Sub Segment Analysis
10.4.1. Real Time Analytics
10.4.2. Predictive Maintenance
10.4.3. Sales and Marketing Data
10.4.4. Customer Relationship Management
10.4.5. Data Traffic Management
10.4.6. Others
Chapter 11. Global Data Pipeline Tools Market, by End-Use
11.1. Market Snapshot
11.2. Global Data Pipeline Tools Market by End-Use, Performance – Potential Analysis
11.3. Global Data Pipeline Tools Market Estimates & Forecasts by End-Use 2019-2029 (USD Billion)
11.4. Data Pipeline Tools Market, Sub Segment Analysis
11.4.1. BFSI
11.4.2. Retail and E-commerce
11.4.3. IT and Telecom
11.4.4. Healthcare
11.4.5. Transportation and Logistics
11.4.6. Others
Chapter 12. Global Data Pipeline Tools Market, Regional Analysis
12.1. Data Pipeline Tools Market, Regional Market Snapshot
12.2. North America Data Pipeline Tools Market
12.2.1. U.S. Data Pipeline Tools Market Component breakdown estimates & forecasts, 2019-2029 Type breakdown estimates & forecasts, 2019-2029 Deployment breakdown estimates & forecasts, 2019-2029 Enterprise breakdown estimates & forecasts, 2019-2029 Application breakdown estimates & forecasts, 2019-2029 End-Use breakdown estimates & forecasts, 2019-2029
12.2.2. Canada Data Pipeline Tools Market
12.3. Europe Data Pipeline Tools Market Snapshot
12.3.1. U.K. Data Pipeline Tools Market
12.3.2. Germany Data Pipeline Tools Market
12.3.3. France Data Pipeline Tools Market
12.3.4. Spain Data Pipeline Tools Market
12.3.5. Italy Data Pipeline Tools Market
12.3.6. Rest of Europe Data Pipeline Tools Market
12.4. Asia-Pacific Data Pipeline Tools Market Snapshot
12.4.1. China Data Pipeline Tools Market
12.4.2. India Data Pipeline Tools Market
12.4.3. Japan Data Pipeline Tools Market
12.4.4. Australia Data Pipeline Tools Market
12.4.5. South Korea Data Pipeline Tools Market
12.4.6. Rest of Asia Pacific Data Pipeline Tools Market
12.5. Latin America Data Pipeline Tools Market Snapshot
12.5.1. Brazil Data Pipeline Tools Market
12.5.2. Mexico Data Pipeline Tools Market
12.5.3. Rest of Latin America Data Pipeline Tools Market
12.6. Rest of The World Data Pipeline Tools Market

Chapter 13. Competitive Intelligence
13.1. Top Market Strategies
13.2. Company Profiles
13.2.1. IBM Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
13.2.2. Hevo Data Inc.
13.2.3. SnapLogic Inc.
13.2.4. K2VIEW
13.2.5. Amazon Web Services, Inc.
13.2.6. Actian Corporation
13.2.7. Google
13.2.8. Software AG
13.2.9. Microsoft
13.2.10. Oracle
Chapter 14. Research Process
14.1. Research Process
14.1.1. Data Mining
14.1.2. Analysis
14.1.3. Market Estimation
14.1.4. Validation
14.1.5. Publishing
14.2. Research Attributes
14.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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