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Global Data Lake Market Size, Share & Industry Trends Analysis Report By Component (Solution, and Services), By Enterprise Size, By Deployment Type (On-premise, and Cloud), By Vertical, By Regional Outlook and Forecast, 2023 - 2030

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    Report

  • 297 Pages
  • September 2023
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5903600
The Global Data Lake Market size is expected to reach $51.3 billion by 2030, rising at a market growth of 19.8% CAGR during the forecast period.

Cloud-based data lakes integrate seamlessly with various data sources and cloud services, facilitating data ingestion, transformation, and integration. Consequently, the Cloud segment would capture around 45% share of the market by 2030. Cloud data lakes offer robust security features, encryption, access control, and compliance with industry-specific regulations, easing organizations' data governance and compliance efforts. Cloud-based data lakes are well-suited for running advanced analytics workloads, including machine learning and AI. Organizations can leverage cloud-based analytics services and tools to gain deeper insights from their data.



The major strategies followed by the market participants are Product Launches as the key developmental strategy to keep pace with the changing demands of end users. For instance, In July, 2023, Oracle Corporation unveiled MySQL HeatWave Lakehouse, allowing customers to query object storage data as quickly as database data. Additionally, In September, 2023, Dremio Corporation announced the next-generation Reflections for sub-second analytics, spanning the entire data ecosystem, regardless of data location. The new product redefines data access, enabling swift insights at 1/3 the cost of a cloud data warehouse.

Cardinal Matrix - Market Competition Analysis

Based on the Analysis presented in the Cardinal Matrix; Microsoft Corporation is the forerunners in the Market. In May, 2023, Microsoft Corporation unveiled Microsoft Fabric, a comprehensive unified analytics platform that consolidates essential data and analytics tools. The platform combines Azure Data Factory, to unleash the power of their data and prepare for the AI era. Companies such as Oracle Corporation, Amazon Web Services, Inc., Snowflake, Inc. are some of the key innovators in the Market.



Market Growth Factors

Increasing need to extract insights from vast volumes of data

Organizations are generating more data than ever, owing to digital transformation, IoT devices, social media, and other data sources. This explosion of data has created a demand for storage solutions that can endure massive amounts of structured and unstructured data. Data lakes can store various data types, including text, images, videos, log files, and sensor data. The growing need to extract insights from large volumes of data has driven organizations to invest in data lakes as a foundational data management and analytics solution. These platforms provide the agility, scalability, and flexibility needed to unlock the full potential of data and stay competitive in today's data-driven world. Hence, these factors will aid in the expansion of the market.

Rapid growth of advanced analytics technologies

The rapid growth of advanced analytics technologies has been a significant driver of the development of the market. Advanced analytics encompasses a range of sophisticated techniques and tools, including machine learning, artificial intelligence, predictive analytics, and data mining, which require extensive and diverse datasets for meaningful insights. Advanced analytics requires access to large volumes of historical and real-time data. Data lakes provide a cost-effective and scalable solution for storing massive datasets, making them readily available for analysis. Data lakes facilitate data preparation by providing a central location for raw data, enabling data engineers and scientists to access and shape data as needed. As organizations increasingly acknowledge the value of data-driven insights, data lakes play a vital role in enabling advanced analytics capabilities and driving innovation across various industries. Thus, the rapid growth of technologies will augment the expansion of the market.

Market Restraining Factors

Regulatory compliance-related data usage complexities

Regulatory bodies, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States and the General Data Protection Regulation (GDPR) in Europe, impose stringent data security and privacy requirements. Organizations using data lakes must implement strong safety measures to protect sensitive data and secure compliance with these regulations. Many regulations mandate specific data retention and deletion policies. Organizations must configure data lakes to adhere to these requirements, which can be complex when dealing with vast datasets. Beyond regulatory compliance, organizations must also consider legal and ethical aspects when managing data within data lakes. This includes addressing potential legal liabilities and ethical concerns associated with data use. The regulatory compliance challenges can pose obstacles for the market.

Component Outlook

On the basis of component, the market is segmented into solution and services. The services segment acquired a substantial revenue share in the market in 2022. Service providers offer ongoing support and maintenance to ensure the continued dependability and availability of the data lake environment. This includes monitoring, troubleshooting, and applying updates and patches. These services assist in ingesting data from various sources into the data lake. Service providers can help with data extraction, transformation, and loading (ETL) processes, ensuring that data is appropriately formatted and cleansed before storage.

Enterprise Size Outlook

By enterprise size, the market is bifurcated into large enterprises and small & medium enterprises. The large enterprises segment acquired the highest revenue share in the market in 2022. Data lakes are highly scalable, allowing organizations to store and manage petabytes of data or more as their data volume grows. This scalability accommodates the increasing data needs of large enterprises. Data lakes often use cost-effective storage solutions, such as cloud storage or Hadoop Distributed File System (HDFS), which can significantly reduce storage costs compared to traditional data warehousing.

Deployment Type Outlook

Based on deployment type, the market is fragmented into on-premise and cloud. The cloud segment garnered a significant revenue share in the market in 2022. Significant data lake parasol vendors provide cloud-based solutions that automate equipment maintenance processes and increase profits. In addition, the adoption of cloud data lakes is anticipated to increase due to their adaptability, scalability, flexibility, and cost-effectiveness. Companies favor cloud-based solutions, which facilitate cross-regional, cross-regional, and cross-national information storage and recovery strategies.

Vertical Outlook

By vertical, the market is classified into IT, BFSI, retail & Ecommerce, healthcare, media & entertainment, manufacturing, and others. The retail and Ecommerce segment recorded a remarkable revenue share in the market in 2022. Data lakes could play a crucial role in retail marketing, as they would facilitate rapid classification of potential customers. Data lakes would provide an in-depth understanding of buyers, their purchasing motivations, and their requirements by analyzing information gathered from various sources, such as call logs, surveys, and social media platforms. Retailers can analyze customer purchase patterns and discover associations between products frequently purchased together.

Regional Outlook

Region-wise, the market is analysed across North America, Europe, Asia Pacific, and LAMEA. In 2022, the North America region witnessed the largest revenue share in the market. The rapid pace of growth in North America can be attributed to the increasing use of big data technology, the rising volume of data across industry verticals, and the rising investment in data lake solutions by businesses. In the United States, associations have begun utilizing data lake solutions to generate actionable insights from structured and unstructured data to remain competitive. Growing the generation of data, such as clickstream data, server logs, customer data, customer relationship management (CRM), and Enterprise Resource Planning (ERP), causes vendors to launch multiple data lake services and products to cater to various demands of the organizations and their customers.

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., Cloudera, Inc., Dremio Corporation, Informatica Inc., Microsoft Corporation, Oracle Corporation, SAS Institute Inc., Snowflake Inc., Teradata Corporation and Zaloni, Inc.

Strategies deployed in the Market


» Partnerships, Collaborations, and Agreements:

  • Sep-2023: Cloudera, Inc. collaborated with Amazon Web Services, Inc., a subsidiary of Amazon that provides on-demand cloud computing platforms. This collaboration reinforces Cloudera's bond with AWS, pledging to advance cloud-native data management and analytics. It utilizes AWS services to provide ongoing innovation and cost savings for customers, supporting Cloudera's open data lakehouse on AWS for reliable enterprise generative AI.
  • Sep-2022: Snowflake Inc. strengthened its partnership with Endava, one of the world’s leading providers of digital transformation consulting and agile software development services, to assist joint customers in their digital transformation. This collaboration aimed to enable data-driven strategies, enhance data governance and security, centralize cloud-based data, and democratize analytics across various business domains.
  • May-2022: Informatica Inc. partnered with Oracle, an American multinational computer technology company, to integrate Informatica's data integration and governance products, specifically the Intelligent Data Management Cloud (IDMC), with Oracle Cloud Infrastructure (OCI), including Oracle Exadata Database Service, Oracle Autonomous Database, Oracle Object Storage, and Oracle Exadata Cloud@Customer.
  • Apr-2022: Informatica inc. expanded its partnership with Snowflake, the Data Cloud Company. This partnership aimed to enhance integration between the Data Cloud and Informatica's Intelligent Data Management Cloud (IDMC), facilitating an expedited transition to the cloud for customers by offering extended data management and governance capabilities.
  • Oct-2021: Dremio Corporation partnered with InterWork, a global IT consulting & services company offering innovative and cutting-edge solutions. Under this partnership, InterWorks leveraged Dremio's capabilities for optimizing data lake investments, enhancing BI dashboards, and enabling interactive analytics, particularly with Tableau Software integration.

» Product Launches and Product Expansions:

  • Sep-2023: Dremio Corporation announced the next-generation Reflections for sub-second analytics, spanning the entire data ecosystem, regardless of data location. The new product redefines data access, enabling swift insights at 1/3 the cost of a cloud data warehouse.
  • Jul-2023: Oracle Corporation unveiled MySQL HeatWave Lakehouse, allowing customers to query object storage data as quickly as database data. The lakehouse supports various object store file formats (CSV, Parquet, etc.) and can seamlessly merge object storage and MySQL database data in a single query.
  • Jul-2023: Teradata Corporation launched VantageCloud Lake analytics platform to Microsoft Azure, a cloud computing platform run by Microsoft. This version includes ClearScape Analytics, offering advanced analytics features, and utilizes Azure Data Lake Storage, a specialized Azure Blob Storage for enhanced capabilities.
  • Jun-2023: Snowflake, Inc. introduced a government and education data cloud, catering to public-sector agencies and educational institutions. This fully managed package simplifies data integration and application development, allowing organizations to harness their data for vertical-specific needs, from predictive capabilities to historical trend analysis.
  • May-2023: Amazon Web Services, Inc. launched Amazon Security Lake, a service that centralizes security data from various sources into a dedicated data lake. Amazon Security Lake standardizes incoming security data to the Open Cybersecurity Schema Framework (OCSF), streamlining its automatic collection, integration, and analysis from over 80 sources, encompassing AWS, security partners, and analytics providers.
  • May-2023: Informatica Inc. enhanced Intelligent Data Management Cloud (IDMC) with expanded data engineering services, including replication, ingestion, ELT, and data quality observability. These improvements offering advanced intelligence, automation, and a wider range of cloud data management services.
  • May-2023: Microsoft Corporation unveiled Microsoft Fabric, a comprehensive unified analytics platform that consolidates essential data and analytics tools. The platform combines Azure Data Factory, Azure Synapse Analytics, and Power BI into a single product, enabling data and business professionals to unleash the power of their data and prepare for the AI era.
  • May-2023: Oracle Corporation unveiled new innovations to its Autonomous Data Warehouse, the first autonomous database for analytics workloads. These innovations promote multicloud compatibility, open standard-based data sharing, and simplified data integration and analysis through a low-code tool, departing from the closed nature of traditional data warehouses and lakes.
  • Mar-2023: Amazon Web Services, Inc. added new features to Amazon S3, a service offered by Amazon Web Services that provides object storage through a web service interface. The new features allow third-party data sales without duplicating data to another S3 bucket and introduce Mountpoint for Amazon S3, an open-source file client. This accelerates and reduces the cost of building data lakes for customers.
  • Aug-2022: Cloudera, Inc. introduced CDP One, a single software-as-a-service (SaaS) solution for data lakehouses, facilitating self-service analytics and data science on diverse data types. CDP One boasted built-in enterprise security and machine learning, reducing costs and risk without needing extra staff. It enhanced productivity for data experts and developers, enabling quicker business insights and fostering innovation.
  • Aug-2022: Teradata Corporation unveiled VantageCloud Lake, a cloud-native product built on a new architecture. It combines Teradata Vantage's capabilities with cloud elasticity, cost-efficiency, and scalability, named VantageCloud Enterprise, designed for ease of use and flexibility.
  • Mar-2022: Snowflake, Inc. introduced the Data Cloud for Retail, following the recent launch of the Healthcare and Life Sciences Data Cloud. The cloud provides a dedicated platform to tackle data challenges in the retail industry for stakeholders like retailers, manufacturers, distributors, and CPG vendors.
  • Jul-2021: Dremio Corporation unveiled Dremio Cloud, a cloud service that streamlines data lake creation and management, allowing for in-memory SQL queries on object-based storage, eliminating the necessity for internal IT teams to handle these tasks.
  • Dec-2020: Amazon Web Services Inc. introduced Amazon HealthLake, a HIPAA-eligible healthcare data lake service that centralizes and normalizes data from various sources using machine learning, tagging critical information and creating a standardized timeline.

» Acquisitions and Mergers:

  • Jun-2020: Microsoft Corporation acquired ADRM Software, a supplier of extensive industry data models. With combined ADRM and Azure's expansive storage and computing capabilities, customers and channel partners can now establish intelligent data lakes in the cloud.

Scope of the Study

Market Segments Covered in the Report:

By Component
  • Solution
  • Services
By Enterprise Size
  • Large Enterprises
  • Small & Medium Enterprises
By Deployment Type
  • On-premise
  • Cloud
By Vertical
  • IT
  • Media & Entertainment
  • Healthcare
  • BFSI
  • Manufacturing
  • Retail & Ecommerce
  • 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
  • Cloudera, Inc.
  • Dremio Corporation
  • Informatica Inc.
  • Microsoft Corporation
  • Oracle Corporation
  • SAS Institute Inc.
  • Snowflake Inc.
  • Teradata Corporation
  • Zaloni, 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 Data Lake Market, by Component
1.4.2 Global Data Lake Market, by Enterprise Size
1.4.3 Global Data Lake Market, by Deployment Type
1.4.4 Global Data Lake Market, by Vertical
1.4.5 Global Data Lake Market, by Geography
1.5 Methodology for the research
Chapter 2. Market at a Glance
2.1 Key Highlights
Chapter 3. Market Overview
3.1 Introduction
3.1.1 Overview
3.1.1.1 Market Composition and Scenario
3.2 Key Factors Impacting the Market
3.2.1 Market Drivers
3.2.2 Market Restraints
Chapter 4. Competition Analysis - Global
4.1 Cardinal Matrix
4.2 Recent Industry Wide Strategic Developments
4.2.1 Partnerships, Collaborations and Agreements
4.2.2 Product Launches and Product Expansions
4.2.3 Acquisition and Mergers
4.3 Top Winning Strategies
4.3.1 Key Leading Strategies: Percentage Distribution (2019-2023)
4.3.2 Key Strategic Move: (Product Launches and Product Expansions : 2021, Oct - 2023, Sep) Leading Players
4.4 Porter Five Forces Analysis
Chapter 5. Global Data Lake Market, By Component
5.1 Global Solution Market, By Region
5.2 Global Services Market, By Region
Chapter 6. Global Data Lake Market, By Enterprise Size
6.1 Global Large Enterprises Market, By Region
6.2 Global Small & Medium Enterprises Market, By Region
Chapter 7. Global Data Lake Market, By Deployment Type
7.1 Global On-premise Market, By Region
7.2 Global Cloud Market, By Region
Chapter 8. Global Data Lake Market, By Vertical
8.1 Global IT Market, By Region
8.2 Global Media & Entertainment Market, By Region
8.3 Global Healthcare Market, By Region
8.4 Global BFSI Market, By Region
8.5 Global Manufacturing Market, By Region
8.6 Global Retail & Ecommerce Market, By Region
8.7 Global Others Market, By Region
Chapter 9. Global Data Lake Market, By Region
9.1 North America Data Lake Market
9.1.1 North America Data Lake Market, By Component
9.1.1.1 North America Solution Market, By Country
9.1.1.2 North America Services Market, By Country
9.1.2 North America Data Lake Market, By Enterprise Size
9.1.2.1 North America Large Enterprises Market, By Country
9.1.2.2 North America Small & Medium Enterprises Market, By Country
9.1.3 North America Data Lake Market, By Deployment Type
9.1.3.1 North America On-premise Market, By Country
9.1.3.2 North America Cloud Market, By Country
9.1.4 North America Data Lake Market, By Vertical
9.1.4.1 North America IT Market, By Country
9.1.4.2 North America Media & Entertainment Market, By Country
9.1.4.3 North America Healthcare Market, By Country
9.1.4.4 North America BFSI Market, By Country
9.1.4.5 North America Manufacturing Market, By Country
9.1.4.6 North America Retail & Ecommerce Market, By Country
9.1.4.7 North America Others Market, By Country
9.1.5 North America Data Lake Market, By Country
9.1.5.1 US Data Lake Market
9.1.5.1.1 US Data Lake Market, By Component
9.1.5.1.2 US Data Lake Market, By Enterprise Size
9.1.5.1.3 US Data Lake Market, By Deployment Type
9.1.5.1.4 US Data Lake Market, By Vertical
9.1.5.2 Canada Data Lake Market
9.1.5.2.1 Canada Data Lake Market, By Component
9.1.5.2.2 Canada Data Lake Market, By Enterprise Size
9.1.5.2.3 Canada Data Lake Market, By Deployment Type
9.1.5.2.4 Canada Data Lake Market, By Vertical
9.1.5.3 Mexico Data Lake Market
9.1.5.3.1 Mexico Data Lake Market, By Component
9.1.5.3.2 Mexico Data Lake Market, By Enterprise Size
9.1.5.3.3 Mexico Data Lake Market, By Deployment Type
9.1.5.3.4 Mexico Data Lake Market, By Vertical
9.1.5.4 Rest of North America Data Lake Market
9.1.5.4.1 Rest of North America Data Lake Market, By Component
9.1.5.4.2 Rest of North America Data Lake Market, By Enterprise Size
9.1.5.4.3 Rest of North America Data Lake Market, By Deployment Type
9.1.5.4.4 Rest of North America Data Lake Market, By Vertical
9.2 Europe Data Lake Market
9.2.1 Europe Data Lake Market, By Component
9.2.1.1 Europe Solution Market, By Country
9.2.1.2 Europe Services Market, By Country
9.2.2 Europe Data Lake Market, By Enterprise Size
9.2.2.1 Europe Large Enterprises Market, By Country
9.2.2.2 Europe Small & Medium Enterprises Market, By Country
9.2.3 Europe Data Lake Market, By Deployment Type
9.2.3.1 Europe On-premise Market, By Country
9.2.3.2 Europe Cloud Market, By Country
9.2.4 Europe Data Lake Market, By Vertical
9.2.4.1 Europe IT Market, By Country
9.2.4.2 Europe Media & Entertainment Market, By Country
9.2.4.3 Europe Healthcare Market, By Country
9.2.4.4 Europe BFSI Market, By Country
9.2.4.5 Europe Manufacturing Market, By Country
9.2.4.6 Europe Retail & Ecommerce Market, By Country
9.2.4.7 Europe Others Market, By Country
9.2.5 Europe Data Lake Market, By Country
9.2.5.1 Germany Data Lake Market
9.2.5.1.1 Germany Data Lake Market, By Component
9.2.5.1.2 Germany Data Lake Market, By Enterprise Size
9.2.5.1.3 Germany Data Lake Market, By Deployment Type
9.2.5.1.4 Germany Data Lake Market, By Vertical
9.2.5.2 UK Data Lake Market
9.2.5.2.1 UK Data Lake Market, By Component
9.2.5.2.2 UK Data Lake Market, By Enterprise Size
9.2.5.2.3 UK Data Lake Market, By Deployment Type
9.2.5.2.4 UK Data Lake Market, By Vertical
9.2.5.3 France Data Lake Market
9.2.5.3.1 France Data Lake Market, By Component
9.2.5.3.2 France Data Lake Market, By Enterprise Size
9.2.5.3.3 France Data Lake Market, By Deployment Type
9.2.5.3.4 France Data Lake Market, By Vertical
9.2.5.4 Russia Data Lake Market
9.2.5.4.1 Russia Data Lake Market, By Component
9.2.5.4.2 Russia Data Lake Market, By Enterprise Size
9.2.5.4.3 Russia Data Lake Market, By Deployment Type
9.2.5.4.4 Russia Data Lake Market, By Vertical
9.2.5.5 Spain Data Lake Market
9.2.5.5.1 Spain Data Lake Market, By Component
9.2.5.5.2 Spain Data Lake Market, By Enterprise Size
9.2.5.5.3 Spain Data Lake Market, By Deployment Type
9.2.5.5.4 Spain Data Lake Market, By Vertical
9.2.5.6 Italy Data Lake Market
9.2.5.6.1 Italy Data Lake Market, By Component
9.2.5.6.2 Italy Data Lake Market, By Enterprise Size
9.2.5.6.3 Italy Data Lake Market, By Deployment Type
9.2.5.6.4 Italy Data Lake Market, By Vertical
9.2.5.7 Rest of Europe Data Lake Market
9.2.5.7.1 Rest of Europe Data Lake Market, By Component
9.2.5.7.2 Rest of Europe Data Lake Market, By Enterprise Size
9.2.5.7.3 Rest of Europe Data Lake Market, By Deployment Type
9.2.5.7.4 Rest of Europe Data Lake Market, By Vertical
9.3 Asia Pacific Data Lake Market
9.3.1 Asia Pacific Data Lake Market, By Component
9.3.1.1 Asia Pacific Solution Market, By Country
9.3.1.2 Asia Pacific Services Market, By Country
9.3.2 Asia Pacific Data Lake Market, By Enterprise Size
9.3.2.1 Asia Pacific Large Enterprises Market, By Country
9.3.2.2 Asia Pacific Small & Medium Enterprises Market, By Country
9.3.3 Asia Pacific Data Lake Market, By Deployment Type
9.3.3.1 Asia Pacific On-premise Market, By Country
9.3.3.2 Asia Pacific Cloud Market, By Country
9.3.4 Asia Pacific Data Lake Market, By Vertical
9.3.4.1 Asia Pacific IT Market, By Country
9.3.4.2 Asia Pacific Media & Entertainment Market, By Country
9.3.4.3 Asia Pacific Healthcare Market, By Country
9.3.4.4 Asia Pacific BFSI Market, By Country
9.3.4.5 Asia Pacific Manufacturing Market, By Country
9.3.4.6 Asia Pacific Retail & Ecommerce Market, By Country
9.3.4.7 Asia Pacific Others Market, By Country
9.3.5 Asia Pacific Data Lake Market, By Country
9.3.5.1 China Data Lake Market
9.3.5.1.1 China Data Lake Market, By Component
9.3.5.1.2 China Data Lake Market, By Enterprise Size
9.3.5.1.3 China Data Lake Market, By Deployment Type
9.3.5.1.4 China Data Lake Market, By Vertical
9.3.5.2 Japan Data Lake Market
9.3.5.2.1 Japan Data Lake Market, By Component
9.3.5.2.2 Japan Data Lake Market, By Enterprise Size
9.3.5.2.3 Japan Data Lake Market, By Deployment Type
9.3.5.2.4 Japan Data Lake Market, By Vertical
9.3.5.3 India Data Lake Market
9.3.5.3.1 India Data Lake Market, By Component
9.3.5.3.2 India Data Lake Market, By Enterprise Size
9.3.5.3.3 India Data Lake Market, By Deployment Type
9.3.5.3.4 India Data Lake Market, By Vertical
9.3.5.4 South Korea Data Lake Market
9.3.5.4.1 South Korea Data Lake Market, By Component
9.3.5.4.2 South Korea Data Lake Market, By Enterprise Size
9.3.5.4.3 South Korea Data Lake Market, By Deployment Type
9.3.5.4.4 South Korea Data Lake Market, By Vertical
9.3.5.5 Singapore Data Lake Market
9.3.5.5.1 Singapore Data Lake Market, By Component
9.3.5.5.2 Singapore Data Lake Market, By Enterprise Size
9.3.5.5.3 Singapore Data Lake Market, By Deployment Type
9.3.5.5.4 Singapore Data Lake Market, By Vertical
9.3.5.6 Malaysia Data Lake Market
9.3.5.6.1 Malaysia Data Lake Market, By Component
9.3.5.6.2 Malaysia Data Lake Market, By Enterprise Size
9.3.5.6.3 Malaysia Data Lake Market, By Deployment Type
9.3.5.6.4 Malaysia Data Lake Market, By Vertical
9.3.5.7 Rest of Asia Pacific Data Lake Market
9.3.5.7.1 Rest of Asia Pacific Data Lake Market, By Component
9.3.5.7.2 Rest of Asia Pacific Data Lake Market, By Enterprise Size
9.3.5.7.3 Rest of Asia Pacific Data Lake Market, By Deployment Type
9.3.5.7.4 Rest of Asia Pacific Data Lake Market, By Vertical
9.4 LAMEA Data Lake Market
9.4.1 LAMEA Data Lake Market, By Component
9.4.1.1 LAMEA Solution Market, By Country
9.4.1.2 LAMEA Services Market, By Country
9.4.2 LAMEA Data Lake Market, By Enterprise Size
9.4.2.1 LAMEA Large Enterprises Market, By Country
9.4.2.2 LAMEA Small & Medium Enterprises Market, By Country
9.4.3 LAMEA Data Lake Market, By Deployment Type
9.4.3.1 LAMEA On-premise Market, By Country
9.4.3.2 LAMEA Cloud Market, By Country
9.4.4 LAMEA Data Lake Market, By Vertical
9.4.4.1 LAMEA IT Market, By Country
9.4.4.2 LAMEA Media & Entertainment Market, By Country
9.4.4.3 LAMEA Healthcare Market, By Country
9.4.4.4 LAMEA BFSI Market, By Country
9.4.4.5 LAMEA Manufacturing Market, By Country
9.4.4.6 LAMEA Retail & Ecommerce Market, By Country
9.4.4.7 LAMEA Others Market, By Country
9.4.5 LAMEA Data Lake Market, By Country
9.4.5.1 Brazil Data Lake Market
9.4.5.1.1 Brazil Data Lake Market, By Component
9.4.5.1.2 Brazil Data Lake Market, By Enterprise Size
9.4.5.1.3 Brazil Data Lake Market, By Deployment Type
9.4.5.1.4 Brazil Data Lake Market, By Vertical
9.4.5.2 Argentina Data Lake Market
9.4.5.2.1 Argentina Data Lake Market, By Component
9.4.5.2.2 Argentina Data Lake Market, By Enterprise Size
9.4.5.2.3 Argentina Data Lake Market, By Deployment Type
9.4.5.2.4 Argentina Data Lake Market, By Vertical
9.4.5.3 UAE Data Lake Market
9.4.5.3.1 UAE Data Lake Market, By Component
9.4.5.3.2 UAE Data Lake Market, By Enterprise Size
9.4.5.3.3 UAE Data Lake Market, By Deployment Type
9.4.5.3.4 UAE Data Lake Market, By Vertical
9.4.5.4 Saudi Arabia Data Lake Market
9.4.5.4.1 Saudi Arabia Data Lake Market, By Component
9.4.5.4.2 Saudi Arabia Data Lake Market, By Enterprise Size
9.4.5.4.3 Saudi Arabia Data Lake Market, By Deployment Type
9.4.5.4.4 Saudi Arabia Data Lake Market, By Vertical
9.4.5.5 South Africa Data Lake Market
9.4.5.5.1 South Africa Data Lake Market, By Component
9.4.5.5.2 South Africa Data Lake Market, By Enterprise Size
9.4.5.5.3 South Africa Data Lake Market, By Deployment Type
9.4.5.5.4 South Africa Data Lake Market, By Vertical
9.4.5.6 Nigeria Data Lake Market
9.4.5.6.1 Nigeria Data Lake Market, By Component
9.4.5.6.2 Nigeria Data Lake Market, By Enterprise Size
9.4.5.6.3 Nigeria Data Lake Market, By Deployment Type
9.4.5.6.4 Nigeria Data Lake Market, By Vertical
9.4.5.7 Rest of LAMEA Data Lake Market
9.4.5.7.1 Rest of LAMEA Data Lake Market, By Component
9.4.5.7.2 Rest of LAMEA Data Lake Market, By Enterprise Size
9.4.5.7.3 Rest of LAMEA Data Lake Market, By Deployment Type
9.4.5.7.4 Rest of LAMEA Data Lake Market, By Vertical
Chapter 10. Company Profiles
10.1 Amazon Web Services, Inc. (Amazon.com, Inc.)
10.1.1 Company Overview
10.1.2 Financial Analysis
10.1.3 Segmental Analysis
10.1.4 Recent strategies and developments:
10.1.4.1 Product Launches and Product Expansions:
10.1.5 SWOT Analysis
10.2 Dremio Corporation
10.2.1 Company Overview
10.2.2 Recent strategies and developments:
10.2.2.1 Partnerships, Collaborations, and Agreements:
10.2.2.2 Product Launches and Product Expansions:
10.2.3 SWOT Analysis
10.3 Cloudera, Inc.
10.3.1 Company Overview
10.3.2 Recent strategies and developments:
10.3.2.1 Partnerships, Collaborations, and Agreements:
10.3.2.2 Product Launches and Product Expansions:
10.3.3 SWOT Analysis
10.4 Informatica Inc.
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:
10.4.6 SWOT Analysis
10.5 Microsoft Corporation
10.5.1 Company Overview
10.5.2 Financial Analysis
10.5.3 Segmental and Regional Analysis
10.5.4 Research & Development Expenses
10.5.5 Recent strategies and developments:
10.5.5.1 Product Launches and Product Expansions:
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 Product Launches and Product Expansions:
10.6.6 SWOT Analysis
10.7 SAS Institute, Inc.
10.7.1 Company Overview
10.7.2 SWOT Analysis
10.8 Snowflake, Inc.
10.8.1 Company Overview
10.8.2 Financial Analysis
10.8.3 Regional Analysis
10.8.4 Research & Development Expenses
10.8.5 Recent strategies and developments:
10.8.5.1 Partnerships, Collaborations, and Agreements:
10.8.5.2 Product Launches and Product Expansions:
10.8.6 SWOT Analysis
10.9 Teradata Corporation
10.9.1 Company Overview
10.9.2 Financial Analysis
10.9.3 Segmental & Regional Analysis
10.9.4 Research & Development Expense
10.9.5 Recent strategies and developments:
10.9.5.1 Product Launches and Product Expansions:
10.9.6 SWOT Analysis
10.10. Zaloni, Inc (Truist Financial Corporation)
10.10.1 Company Overview
10.10.2 Financial Analysis
10.10.3 Segmental and Regional Analysis
10.10.4 SWOT Analysis
Chapter 11. Winning Imperatives of Data Lake Market

Companies Mentioned

  • Amazon Web Services, Inc
  • Cloudera, Inc.
  • Dremio Corporation
  • Informatica Inc.
  • Microsoft Corporation
  • Oracle Corporation
  • SAS Institute Inc.
  • Snowflake Inc.
  • Teradata Corporation
  • Zaloni, Inc.

Methodology

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