
Big Data Technology Market Report and Forecast 2025-2034
Description
The global big data technology market is expected to grow at a CAGR of 17.10% during the period 2025-2034. The market is expected to be driven by organizations’ need to gather and analyse huge amounts of data to gain insights and make intelligent decisions. North America, Europe and Asia are expected to be key markets.
Global Market Likely to be Driven by Companies Adopting Big Data Processing Technologies to Analyse Massive Amounts of Real-time Data and Make Predictions to Reduce Risk of Failure
Big data describes the vast collection of data that is great in size and exponentially increasing with time. It denotes the massive amount of data difficult to stock, investigate, and transform with conventional tools of management. Big data technologies refer to the utilized software that incorporates data mining, data storage, data sharing, and data visualization; the inclusive term embraces data, data framework including tools and techniques used to examine and transform data. In greater terms of range in technology, it is widely linked with other technologies such as Machine Learning, Deep Learning, Artificial Intelligence , and IoT that are amplified on a larger scale. Big data technologies can be split into two categories – operational and analytical.
Operational big data technologies indicate the generated quantity of data on a daily basis through online transactions, social media, or any kind of data from a particular firm used for analysis through big data technologies-based software; it acts as raw data to feed analytical big data technologies. Some examples outlining operational big data technologies include executives’ details in an MNC, online trading and purchasing from platforms like Amazon, Flipkart, Walmart, etc, online ticket booking for flights, movies, railways, etc.
Analytical big data technologies refer to advanced adaptation of big data technologies; these are relatively complex than operational big data. These involve the investigation of the massive amounts of data crucial for business decisions. Examples include stock marketing, weather forecasting, time series analysis, medical-health records, etc.
Modern Big Data Technologies Offered by Leading Companies Likely to Boost Market Growth
The global big data technology market is likely to be driven by leading big data technologies including Apache Hadoop, Apache Spark, MongoDB, Apache Cassandra, Apache Kafka, QlikView, Qlik Sense, Tableau, Apache Storm, Apache Hive, Apache Pig, Presto, Apache Flink, Apache Sqoop, Rapidminer, KNIME (Konstanz Information Miner), and Elasticsearch.
Applications of Big Data Technologies Likely to Drive Global Market
Big data technologies are widely used in product development, predictive maintenance, to enhance customer experience and operational efficiency, fraud and compliance, machine learning, and to drive innovation.
Companies such as Netflix and Procter & Gamble employ big data to predict customer demand. The companies construct predictive models for novel products and services by categorizing main characteristics of past and current products or services and modelling the association between those features and the commercial success of the offerings. P&G also utilizes data and analytics from focus groups, social media, test markets, and early store rollouts to plan, produce, and launch new products. Such applications are expected to drive the global big data technology market. Factors capable of predicting mechanical failures may be rooted in structured as well as unstructured data. By analysing such data for indications of possible issues before problems occur, organizations can deploy maintenance more efficiently and maximize parts and equipment uptime.
Big data enables a clearer view of customer experience through collection of information from social media, web visits, call logs, and other sources; such information helps enhance interaction experience and maximize value delivered, and enables companies to deliver tailored offers, decrease customer churn, and manage issues proactively. Big data helps identify patterns in data that signify fraud and aggregate large volumes of information to quicken regulatory reporting.
Innovation Enabled by Big Data Technologies and Increasing Use of Such Technologies by Organizations Expected to Stimulate Market Growth
Big data helps analyse and evaluate production, customer feedback and returns, and other aspects to decrease outages and predict future demands. Big data may also be used to enhance decision-making in line with current market demand.
The global big data technology market is expected to be driven by big data technologies that can drive innovation by enabling the study of interdependencies among humans, institutions, entities, and process, and identification of new ways to use those understandings.
Organizations are increasingly leveraging big data to extract value and insights from data. With the exponential increase of data, distributed storage and compute solutions such as Hadoop offer the framework for storing, processing, and analysing big data.
Microsoft Azure offers several options to run big data workloads in the cloud.
Big Data Technology Market Segmentation
By offering, the market is segmented into Big Data Analytics
Data Discovery
Data Visualisation
Data Management Managed Services
Professional Services
By deployment, the market is divided into
The report presents a detailed analysis of the following key players in the global big data technology market, looking into their capacity, and latest developments like capacity expansions, plant turnarounds, and mergers and acquisitions:
Global Market Likely to be Driven by Companies Adopting Big Data Processing Technologies to Analyse Massive Amounts of Real-time Data and Make Predictions to Reduce Risk of Failure
Big data describes the vast collection of data that is great in size and exponentially increasing with time. It denotes the massive amount of data difficult to stock, investigate, and transform with conventional tools of management. Big data technologies refer to the utilized software that incorporates data mining, data storage, data sharing, and data visualization; the inclusive term embraces data, data framework including tools and techniques used to examine and transform data. In greater terms of range in technology, it is widely linked with other technologies such as Machine Learning, Deep Learning, Artificial Intelligence , and IoT that are amplified on a larger scale. Big data technologies can be split into two categories – operational and analytical.
Operational big data technologies indicate the generated quantity of data on a daily basis through online transactions, social media, or any kind of data from a particular firm used for analysis through big data technologies-based software; it acts as raw data to feed analytical big data technologies. Some examples outlining operational big data technologies include executives’ details in an MNC, online trading and purchasing from platforms like Amazon, Flipkart, Walmart, etc, online ticket booking for flights, movies, railways, etc.
Analytical big data technologies refer to advanced adaptation of big data technologies; these are relatively complex than operational big data. These involve the investigation of the massive amounts of data crucial for business decisions. Examples include stock marketing, weather forecasting, time series analysis, medical-health records, etc.
Modern Big Data Technologies Offered by Leading Companies Likely to Boost Market Growth
The global big data technology market is likely to be driven by leading big data technologies including Apache Hadoop, Apache Spark, MongoDB, Apache Cassandra, Apache Kafka, QlikView, Qlik Sense, Tableau, Apache Storm, Apache Hive, Apache Pig, Presto, Apache Flink, Apache Sqoop, Rapidminer, KNIME (Konstanz Information Miner), and Elasticsearch.
Applications of Big Data Technologies Likely to Drive Global Market
Big data technologies are widely used in product development, predictive maintenance, to enhance customer experience and operational efficiency, fraud and compliance, machine learning, and to drive innovation.
Companies such as Netflix and Procter & Gamble employ big data to predict customer demand. The companies construct predictive models for novel products and services by categorizing main characteristics of past and current products or services and modelling the association between those features and the commercial success of the offerings. P&G also utilizes data and analytics from focus groups, social media, test markets, and early store rollouts to plan, produce, and launch new products. Such applications are expected to drive the global big data technology market. Factors capable of predicting mechanical failures may be rooted in structured as well as unstructured data. By analysing such data for indications of possible issues before problems occur, organizations can deploy maintenance more efficiently and maximize parts and equipment uptime.
Big data enables a clearer view of customer experience through collection of information from social media, web visits, call logs, and other sources; such information helps enhance interaction experience and maximize value delivered, and enables companies to deliver tailored offers, decrease customer churn, and manage issues proactively. Big data helps identify patterns in data that signify fraud and aggregate large volumes of information to quicken regulatory reporting.
Innovation Enabled by Big Data Technologies and Increasing Use of Such Technologies by Organizations Expected to Stimulate Market Growth
Big data helps analyse and evaluate production, customer feedback and returns, and other aspects to decrease outages and predict future demands. Big data may also be used to enhance decision-making in line with current market demand.
The global big data technology market is expected to be driven by big data technologies that can drive innovation by enabling the study of interdependencies among humans, institutions, entities, and process, and identification of new ways to use those understandings.
Organizations are increasingly leveraging big data to extract value and insights from data. With the exponential increase of data, distributed storage and compute solutions such as Hadoop offer the framework for storing, processing, and analysing big data.
Microsoft Azure offers several options to run big data workloads in the cloud.
Big Data Technology Market Segmentation
By offering, the market is segmented into
- Solution
- Services
By deployment, the market is divided into
- Cloud
- On-premises
- Hybrid
- Customer Analytics
- Operational Analytics
- Fraud Detection and Compliance
- Enterprise Data Warehouse Optimisation
- Data Analytics
- Small and Medium Size Enterprises
- Large Enterprises
- BFSI
- Retail
- Manufacturing
- IT and Telecom
- Government
- Healthcare
- Utility
- Education
- Others
- North America
- Europe
- Asia Pacific
- Latin America
- Middle East and Africa
The report presents a detailed analysis of the following key players in the global big data technology market, looking into their capacity, and latest developments like capacity expansions, plant turnarounds, and mergers and acquisitions:
- IBM Corporation
- Microsoft Corporation
- Infosys Limited
- Oracle Corporation
- Cloudera, Inc.
- Others
Table of Contents
156 Pages
- 1 Executive Summary
- 1.1 Market Size 2024-2025
- 1.2 Market Growth 2025(F)-2034(F)
- 1.3 Key Demand Drivers
- 1.4 Key Players and Competitive Structure
- 1.5 Industry Best Practices
- 1.6 Recent Trends and Developments
- 1.7 Industry Outlook
- 2 Market Overview and Stakeholder Insights
- 2.1 Market Trends
- 2.2 Key Verticals
- 2.3 Key Regions
- 2.4 Supplier Power
- 2.5 Buyer Power
- 2.6 Key Market Opportunities and Risks
- 2.7 Key Initiatives by Stakeholders
- 3 Economic Summary
- 3.1 GDP Outlook
- 3.2 GDP Per Capita Growth
- 3.3 Inflation Trends
- 3.4 Democracy Index
- 3.5 Gross Public Debt Ratios
- 3.6 Balance of Payment (BoP) Position
- 3.7 Population Outlook
- 3.8 Urbanisation Trends
- 4 Country Risk Profiles
- 4.1 Country Risk
- 4.2 Business Climate
- 5 Global Big Data Technology Market Analysis
- 5.1 Key Industry Highlights
- 5.2 Global Big Data Technology Historical Market (2018-2024)
- 5.3 Global Big Data Technology Market Forecast (2025-2034)
- 5.4 Global Big Data Technology Market by Offering
- 5.4.1 Solution
- 5.4.1.1 Historical Trend (2018-2024)
- 5.4.1.2 Forecast Trend (2025-2034)
- 5.4.1.3 Breakup by Type
- 5.4.1.3.1 Big Data Analytics
- 5.4.1.3.2 Data Discovery
- 5.4.1.3.3 Data Visualisation
- 5.4.1.3.4 Data Management
- 5.4.2 Services
- 5.4.2.1 Historical Trend (2018-2024)
- 5.4.2.2 Forecast Trend (2025-2034)
- 5.4.2.3 Breakup by Type
- 5.4.2.3.1 Managed Services
- 5.4.2.3.2 Professional Services
- 5.5 Global Big Data Technology Market by Deployment
- 5.5.1 Cloud
- 5.5.1.1 Historical Trend (2018-2024)
- 5.5.1.2 Forecast Trend (2025-2034)
- 5.5.2 On-premises
- 5.5.2.1 Historical Trend (2018-2024)
- 5.5.2.2 Forecast Trend (2025-2034)
- 5.5.3 Hybrid
- 5.5.3.1 Historical Trend (2018-2024)
- 5.5.3.2 Forecast Trend (2025-2034)
- 5.6 Global Big Data Technology Market by Application
- 5.6.1 Customer Analytics
- 5.6.1.1 Historical Trend (2018-2024)
- 5.6.1.2 Forecast Trend (2025-2034)
- 5.6.2 Operational Analytics
- 5.6.2.1 Historical Trend (2018-2024)
- 5.6.2.2 Forecast Trend (2025-2034)
- 5.6.3 Fraud Detection and Compliance
- 5.6.3.1 Historical Trend (2018-2024)
- 5.6.3.2 Forecast Trend (2025-2034)
- 5.6.4 Enterprise Data Warehouse Optimisation
- 5.6.4.1 Historical Trend (2018-2024)
- 5.6.4.2 Forecast Trend (2025-2034)
- 5.6.5 Data Analytics
- 5.6.5.1 Historical Trend (2018-2024)
- 5.6.5.2 Forecast Trend (2025-2034)
- 5.7 Global Big Data Technology Market by Organisation Size
- 5.7.1 Small and Medium Size Enterprises
- 5.7.1.1 Historical Trend (2018-2024)
- 5.7.1.2 Forecast Trend (2025-2034)
- 5.7.2 Large Enterprises
- 5.7.2.1 Historical Trend (2018-2024)
- 5.7.2.2 Forecast Trend (2025-2034)
- 5.8 Global Big Data Technology Market by End Use
- 5.8.1 BFSI
- 5.8.1.1 Historical Trend (2018-2024)
- 5.8.1.2 Forecast Trend (2025-2034)
- 5.8.2 Retail
- 5.8.2.1 Historical Trend (2018-2024)
- 5.8.2.2 Forecast Trend (2025-2034)
- 5.8.3 Manufacturing
- 5.8.3.1 Historical Trend (2018-2024)
- 5.8.3.2 Forecast Trend (2025-2034)
- 5.8.4 IT and Telecom
- 5.8.4.1 Historical Trend (2018-2024)
- 5.8.4.2 Forecast Trend (2025-2034)
- 5.8.5 Government
- 5.8.5.1 Historical Trend (2018-2024)
- 5.8.5.2 Forecast Trend (2025-2034)
- 5.8.6 Healthcare
- 5.8.6.1 Historical Trend (2018-2024)
- 5.8.6.2 Forecast Trend (2025-2034)
- 5.8.7 Utility
- 5.8.7.1 Historical Trend (2018-2024)
- 5.8.7.2 Forecast Trend (2025-2034)
- 5.8.8 Education
- 5.8.8.1 Historical Trend (2018-2024)
- 5.8.8.2 Forecast Trend (2025-2034)
- 5.8.9 Others
- 5.9 Global Big Data Technology Market by Region
- 5.9.1 North America
- 5.9.1.1 Historical Trend (2018-2024)
- 5.9.1.2 Forecast Trend (2025-2034)
- 5.9.2 Europe
- 5.9.2.1 Historical Trend (2018-2024)
- 5.9.2.2 Forecast Trend (2025-2034)
- 5.9.3 Asia Pacific
- 5.9.3.1 Historical Trend (2018-2024)
- 5.9.3.2 Forecast Trend (2025-2034)
- 5.9.4 Latin America
- 5.9.4.1 Historical Trend (2018-2024)
- 5.9.4.2 Forecast Trend (2025-2034)
- 5.9.5 Middle East and Africa
- 5.9.5.1 Historical Trend (2018-2024)
- 5.9.5.2 Forecast Trend (2025-2034)
- 6 North America Big Data Technology Market Analysis
- 6.1 United States of America
- 6.1.1 Historical Trend (2018-2024)
- 6.1.2 Forecast Trend (2025-2034)
- 6.2 Canada
- 6.2.1 Historical Trend (2018-2024)
- 6.2.2 Forecast Trend (2025-2034)
- 7 Europe Big Data Technology Market Analysis
- 7.1 United Kingdom
- 7.1.1 Historical Trend (2018-2024)
- 7.1.2 Forecast Trend (2025-2034)
- 7.2 Germany
- 7.2.1 Historical Trend (2018-2024)
- 7.2.2 Forecast Trend (2025-2034)
- 7.3 France
- 7.3.1 Historical Trend (2018-2024)
- 7.3.2 Forecast Trend (2025-2034)
- 7.4 Italy
- 7.4.1 Historical Trend (2018-2024)
- 7.4.2 Forecast Trend (2025-2034)
- 7.5 Others
- 8 Asia Pacific Big Data Technology Market Analysis
- 8.1 China
- 8.1.1 Historical Trend (2018-2024)
- 8.1.2 Forecast Trend (2025-2034)
- 8.2 Japan
- 8.2.1 Historical Trend (2018-2024)
- 8.2.2 Forecast Trend (2025-2034)
- 8.3 India
- 8.3.1 Historical Trend (2018-2024)
- 8.3.2 Forecast Trend (2025-2034)
- 8.4 ASEAN
- 8.4.1 Historical Trend (2018-2024)
- 8.4.2 Forecast Trend (2025-2034)
- 8.5 Australia
- 8.5.1 Historical Trend (2018-2024)
- 8.5.2 Forecast Trend (2025-2034)
- 8.6 Others
- 9 Latin America Big Data Technology Market Analysis
- 9.1 Brazil
- 9.1.1 Historical Trend (2018-2024)
- 9.1.2 Forecast Trend (2025-2034)
- 9.2 Argentina
- 9.2.1 Historical Trend (2018-2024)
- 9.2.2 Forecast Trend (2025-2034)
- 9.3 Mexico
- 9.3.1 Historical Trend (2018-2024)
- 9.3.2 Forecast Trend (2025-2034)
- 9.4 Others
- 10 Middle East and Africa Big Data Technology Market Analysis
- 10.1 Saudi Arabia
- 10.1.1 Historical Trend (2018-2024)
- 10.1.2 Forecast Trend (2025-2034)
- 10.2 United Arab Emirates
- 10.2.1 Historical Trend (2018-2024)
- 10.2.2 Forecast Trend (2025-2034)
- 10.3 Nigeria
- 10.3.1 Historical Trend (2018-2024)
- 10.3.2 Forecast Trend (2025-2034)
- 10.4 South Africa
- 10.4.1 Historical Trend (2018-2024)
- 10.4.2 Forecast Trend (2025-2034)
- 10.5 Others
- 11 Market Dynamics
- 11.1 SWOT Analysis
- 11.1.1 Strengths
- 11.1.2 Weaknesses
- 11.1.3 Opportunities
- 11.1.4 Threats
- 11.2 Porter’s Five Forces Analysis
- 11.2.1 Supplier’s Power
- 11.2.2 Buyer’s Power
- 11.2.3 Threat of New Entrants
- 11.2.4 Degree of Rivalry
- 11.2.5 Threat of Substitutes
- 11.3 Key Indicators for Demand
- 11.4 Key Indicators for Price
- 12 Competitive Landscape
- 12.1 Supplier Selection
- 12.2 Key Global Players
- 12.3 Key Regional Players
- 12.4 Key Player Strategies
- 12.5 Company Profiles
- 12.5.1 IBM Corporation
- 12.5.1.1 Company Overview
- 12.5.1.2 Product Portfolio
- 12.5.1.3 Demographic Reach and Achievements
- 12.5.1.4 Certifications
- 12.5.2 Microsoft Corporation
- 12.5.2.1 Company Overview
- 12.5.2.2 Product Portfolio
- 12.5.2.3 Demographic Reach and Achievements
- 12.5.2.4 Certifications
- 12.5.3 Infosys Limited
- 12.5.3.1 Company Overview
- 12.5.3.2 Product Portfolio
- 12.5.3.3 Demographic Reach and Achievements
- 12.5.3.4 Certifications
- 12.5.4 Oracle Corporation
- 12.5.4.1 Company Overview
- 12.5.4.2 Product Portfolio
- 12.5.4.3 Demographic Reach and Achievements
- 12.5.4.4 Certifications
- 12.5.5 Cloudera, Inc.
- 12.5.5.1 Company Overview
- 12.5.5.2 Product Portfolio
- 12.5.5.3 Demographic Reach and Achievements
- 12.5.5.4 Certifications
- 12.5.6 Others
Pricing
Currency Rates
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