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Global Data Lake Market to reach USD XX billion by the end of 2029

Global Data Lake Market Size study & Forecast, by Type (Solution, Services) by Deployment (On-premise, Cloud), by Vertical (IT, BFSI, Retail, Healthcare, Media and Entertainment, Manufacturing, Others (government, hospitality, education, others) ) and Regional Analysis, 2022-2029

Product Code: ICTBC-11140156
Publish Date: 5-01-2023
Page: 200

Global Data Lake Market is valued at approximately USD XX billion in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2029. Systems called data lakes are used to store information in its unprocessed state. It serves as a central hub for enormous amounts of conveniently accessible data. Unstructured data used by data analysts and data scientists can be stored in a data lake, while structured data is frequently used by the aviation and automobile industries. The major driving factors for the market are the rising usage of IoT devices and the rise in the number of digital payments. Along with this, the deployment of smart cities is creating a lucrative growth opportunity for the market over the forecast period.

According to Statista, Short range technologies such as WiFi and Bluetooth enable 5.7 billion Internet of Things (IoT) connected devices worldwide in 2019. In 2019, 1.2 billion IoT connections were made on public networks such as cellular networks. By 2030, there are expected to be 24.1 billion linked IoT devices, up from 7.6 billion in 2019. However, the high cost of Data Lake stifles market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Data Lake Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. Over the course of the forecast, North America is anticipated to hold the biggest market share. The share can be ascribed to increased information quantities across industries, rising data lake investments, and expanding use of big data technology. A COVID-19 data lake was created by C3 ai, Inc., a U.S.-based AI startup, in March 2020. A uniform and open dataset will be stored in this one location and made available to researchers worldwide starting in mid-April 2020. The forecast period is expected to have the highest CAGR in the Asia Pacific. The expansion is attributable to rising investments from significant technological firms in China, Australia, India, and Japan. Additionally, a number of additional elements, such as advancing big data analytics technologies and growing digitization, are projected to propel the market in the area.

Major market player included in this report are:
Amazon Web Services, Inc
Cloudera, Inc.
Dremio Corporation
Informatica Corporation
Microsoft Corporation
Oracle Corporation
SAS Institute Inc.
Snowflake Inc.
Teradata Corporation
Zaloni, Inc.

Recent Developments in the Market:
 The U.S.-based company Zaloni, Inc. announced in January 2020 that the Zaloni Data Platform was now available in the Microsoft Azure Marketplace. Through this partnership, Zaloni, Inc.’s clients will have access to the Azure cloud computing platform.
Global Data Lake 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 Type, Deployment, Vertical, 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 Type:
Solution
Services

By Deployment:
On-premise
Cloud

By Vertical:
IT
BFSI
Retail
Healthcare
Media and Entertainment
Manufacturing
Others (government, hospitality, education, others)

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
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 Lake Market, by Region, 2019-2029 (USD Billion)
1.2.2. Data Lake Market, by Type, 2019-2029 (USD Billion)
1.2.3. Data Lake Market, by Deployment, 2019-2029 (USD Billion)
1.2.4. Data Lake Market, by Vertical, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Data Lake 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 Lake Market Dynamics
3.1. Data Lake Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing IoT devices
3.1.1.2. Rise in the number of digital payments
3.1.2. Market Challenges
3.1.2.1. High Cost of Data Lake
3.1.3. Market Opportunities
3.1.3.1. Deployment of smart cities
Chapter 4. Global Data Lake 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. Investment Adoption Model
4.5. Analyst Recommendation & Conclusion
4.6. Top investment opportunity
4.7. Top winning strategies
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 Lake Market, by Type
6.1. Market Snapshot
6.2. Global Data Lake Market by Type, Performance – Potential Analysis
6.3. Global Data Lake Market Estimates & Forecasts by Type 2019-2029 (USD Billion)
6.4. Data Lake Market, Sub Segment Analysis
6.4.1. Solution
6.4.2. Services
Chapter 7. Global Data Lake Market, by Deployment
7.1. Market Snapshot
7.2. Global Data Lake Market by Deployment, Performance – Potential Analysis
7.3. Global Data Lake Market Estimates & Forecasts by Deployment 2019-2029 (USD Billion)
7.4. Data Lake Market, Sub Segment Analysis
7.4.1. On-premises
7.4.2. Cloud
Chapter 8. Global Data Lake Market, by Vertical
8.1. Market Snapshot
8.2. Global Data Lake Market by Vertical, Performance – Potential Analysis
8.3. Global Data Lake Market Estimates & Forecasts by Vertical 2019-2029 (USD Billion)
8.4. Data Lake Market, Sub Segment Analysis
8.4.1. IT
8.4.2. BFSI
8.4.3. Retail
8.4.4. Healthcare
8.4.5. Media and Entertainment
8.4.6. Manufacturing
8.4.7. Others (government, hospitality, education, others)
Chapter 9. Global Data Lake Market, Regional Analysis
9.1. Data Lake Market, Regional Market Snapshot
9.2. North America Data Lake Market
9.2.1. U.S. Data Lake Market
9.2.1.1. Type breakdown estimates & forecasts, 2019-2029
9.2.1.2. Deployment breakdown estimates & forecasts, 2019-2029
9.2.1.3. Vertical breakdown estimates & forecasts, 2019-2029
9.2.2. Canada Data Lake Market
9.3. Europe Data Lake Market Snapshot
9.3.1. U.K. Data Lake Market
9.3.2. Germany Data Lake Market
9.3.3. France Data Lake Market
9.3.4. Spain Data Lake Market
9.3.5. Italy Data Lake Market
9.3.6. Rest of Europe Data Lake Market
9.4. Asia-Pacific Data Lake Market Snapshot
9.4.1. China Data Lake Market
9.4.2. India Data Lake Market
9.4.3. Japan Data Lake Market
9.4.4. Australia Data Lake Market
9.4.5. South Korea Data Lake Market
9.4.6. Rest of Asia Pacific Data Lake Market
9.5. Latin America Data Lake Market Snapshot
9.5.1. Brazil Data Lake Market
9.5.2. Mexico Data Lake Market
9.6. Rest of The World Data Lake Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Amazon Web Services, Inc.
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. Cloudera, Inc.
10.2.3. Dermio Corporation
10.2.4. Information Corporation
10.2.5. Microsoft Corporation
10.2.6. Oracle Corporation
10.2.7. SAS Institute, Inc.
10.2.8. Snowflake, Inc.
10.2.9. Teradata Corporation
10.2.10. Zaloni, Inc.
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. 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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