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Future of big data:
key statistics & forecasts
April 14, 2026
Big data landscape
Due to the increase in the number of internet users across the globe, business operations’ digitalization, and the proliferation of smartphones and IoT devices, the amount of data generated has seen an exponential rise. Large and complex datasets that can’t be managed using traditional tools and techniques are considered big data. Big data collection and analysis provide businesses with comprehensive insights, driving innovation and effective business growth.
Data trends
| It is predicted that the total volume of data produced, recorded, transferred, and used worldwide will reach 527.5 zettabytes in 2029, up from 173.4 zettabytes in 2025. | |
|---|---|
| Over 18 billion text messages are estimated to be sent daily worldwide | |
| Unstructured datasets make up 90% of all enterprise-generated data and are usually large, reaching terabytes or petabytes | |
| The volume of data that large enterprises gather and store is expected to increase tenfold every year, with about 90% of that data being either unused or not properly utilized |
Big data adoption
| Among advanced digital technologies, big data ranks third, with a 37% adoption rate in the UK, following cloud computing and AI |
|---|
Scheme title: Motivations to adopt big data
Data source: The University of Manchester
Scheme title: Barriers to adopting big data
Data source: The University of Manchester
Scheme title: Impact of big data adoption
Data source: The University of Manchester
Prepare your business for the future of big data with our dedicated services
Big data market
The global big data market and its related segments, such as big data analytics, engineering services, and big data platforms, are expected to grow in the upcoming years, driven by such factors as the increased need for data-driven decision-making and the expansion of cloud computing.
Overall market size & growth
| The global big data market is forecasted to grow from $224.46 billion in 2025 to $573.47 billion by 2033 at a compound annual growth rate (CAGR) of 12.44% from 2025 to 2033. | |
|---|---|
| By deployment model, cloud holds a prominent share of the worldwide big data market, accounting for 58.3%. | |
| Large enterprises are believed to be the major adopters of big data technology, with a 65.93% share of the big data technology market, while big data technology adoption by small and medium enterprises is projected to grow faster at a CAGR of 13.66% from 2024 to 2030. |
Future of big data analytics
| The global big data analytics market was worth $394.7 billion in 2025 and is expected to reach $1,176.57 billion by 2034. | |
|---|---|
| The global big data analytics market is forecasted to expand, exhibiting a CAGR of 12.8% from 2025 to 2034. |
Scheme title: Largest and fastest-growing big data analytics markets
Data source: SkyQuest Technology Consulting
| The US big data analytics market is projected to reach $248.89 billion by 2032. |
|---|
Scheme title: Top 5 big data analytics providers’ (Microsoft Corporation, IBM Corporation, Oracle
Corporation, SAP SE, SAS Institute Inc.) market share against other players
Data source: Fortune Business Insights
| The big data and analytics services market is forecasted to expand to $440.03 billion by 2030, exhibiting a CAGR of 21.5%. |
|---|
Big data engineering services market
| The market for big data engineering services is projected to be worth $105.39 billion in 2026 and grow at a CAGR of 15.12% to $213.07 billion by 2031. |
|---|
Scheme title: Big data engineering services market growth by region
Data source: Mordor Intelligence
Big data platform market
| With a CAGR of 13.38% from 2026 to 2035, the big data platform market is projected to reach $314.35 billion by 2035, up from $101.55 billion in 2026. | |
|---|---|
| With a market share of 32%, North America dominates the big data platform market, followed by Europe and Asia Pacific. | |
| Cloud-based solutions are projected to hold 79% of the big data platform market, with cloud platforms typically favored for their scalability and cost-effectiveness. |
Big data consulting market
Scheme title: Big data consulting market value in 2025 and 2030
Data source: Mordor Intelligence
Scheme title: Big data consulting market growth by region
Data source: Mordor Intelligence
Big data trends
Companies are increasingly applying advanced technologies like cloud, artificial intelligence, and machine learning to further streamline big data processing. While AI algorithms facilitate real-time data analysis, predictive analytics, and automation of decision-making processes, cloud big data solutions can provide accelerated software deployment and greater scalability. However, as companies embrace technological advancements, data analysts are pushed to expand their skill sets to work with big data.
At the same time, as big data analytics platforms collect large volumes of information, including sensitive data, data protection and fraud detection will come to the forefront of big data projects. Businesses will be required to develop robust big data governance frameworks and ensure compliance with data security regulations like GDPR or HIPAA.
AI/ML integration
| 48% of companies employ AI for effective big data management | |
|---|---|
| The big data and artificial intelligence market is anticipated to increase from $456.35 billion in 2025 to $884.42 billion by 2029. | |
| The global big data and artificial intelligence market is forecasted to exhibit a CAGR of 18% between 2025 and 2029. |
Cloud adoption
| As of 2025, 51% of businesses said they chose public clouds for data storage | |
|---|---|
| According to a poll conducted in 2025, 62% of SMBs said they kept data in the public cloud | |
| The global big data as a service (BDaaS) market is predicted to increase from $47.21 billion in 2026 to $226.81 billion in 2035, demonstrating a CAGR of 19.11% during this period. |
Scheme title: Market share of big data as a service by region
Data source: Precedence Research
| The US BDaaS market was valued at $9.94 billion in 2025 and is projected to expand at a CAGR of 19.4% from 2026 to 2035. | |
|---|---|
| 64% of the BDaaS market is held by the public cloud segment, being the largest one by deployment. | |
| Large enterprises are the main BDaaS adopters, while small and medium-sized businesses are projected to adopt BDaaS at the highest CAGR from 2025–2034 |
Growing demand for data science roles
| Data scientists will be among the top 4 fastest-growing occupations between 2024 and 2034. | |
|---|---|
| A data scientist earns a median salary of $112,590 per year | |
| Data scientists are expected to see a 34% increase in employment between 2024 and 2034, which is significantly higher than the average for all occupations. | |
| Employers around the world say that the most crucial skills are big data and AI |
Scheme title: Big data and AI seen as core skills for 2025–2030 by employers worldwide
Data source: Statista
Increasing importance of big data security
| The global average cost of a data breach reached $4.4 million in 2025, a 9% decrease over the previous year. | |
|---|---|
| The widespread usage of AI in data security saves $1.9 million. | |
| 27% of business leaders named “data protection/data trust” as their top 3 cybersecurity priorities for using managed services over the next 12 months. | |
| Only 14% of security & risk management (SRM) executives can both secure organizational data assets and ensure the usage of data to accomplish business goals. | |
| Organizations are switching focus from protecting structured data to protecting unstructured data, such as text, images, and videos. | |
| The global big data security market is expected to increase from $31.85 billion in 2026 to $104.79 billion by 2034, growing at a CAGR of 16.05% during the forecasted period. | |
| North America dominates the big data security market, with a market value of $10.15 billion and 37.04% market share. |
Scheme title: Big data security market growth rate by region
Data source: Mordor Intelligence
Scheme title: Solutions used for big data security
Data source: Pro Market Reports
Big data across industries
| Global big data technology market analysis indicates that, by end-use industry, 25.67% of demand for big data technology is generated by the BFSI industry, while healthcare and life sciences are growing at the fastest CAGR of 15.13%. |
|---|
Scheme title: Adoption of AI and big data across sectors in 2025
Data source: Statista
Information & technology
services
services
Financial
services &
capital markets
services &
capital markets
Education &
training
training
Medical &
healthcare
services
healthcare
services
Electronics
Real estate
Retail &
wholesale of consumer goods
wholesale of consumer goods
Professional services
Chemical & advanced
materials
materials
Telecommunication
Insurance &
pensions
management
pensions
management
Automotive &
aerospace
aerospace
Government &
public sector
public sector
Supply chain &
transportation
transportation
Production of
consumer
goods
consumer
goods
Infrastructure
Advanced
manufacturing
manufacturing
Scheme title: Share of employers across different industries considering AI and big data to be core skills
from 2025–2030
Data source: Statista
Healthcare
| Valued at $67.32 billion in 2025, the market for big data analytics in healthcare is projected to grow nearly fivefold by 2034, reaching $327.57 billion. | |
|---|---|
| The big data analytics in healthcare market is anticipated to increase at a CAGR of 9.12% from 2026 to 2032, with key use cases including clinical, financial, and operational analytics. |
Image title: Key drivers of big data analytics implementation in healthcare and their impact value
Image source: Verified Market Research
Image title: Main big data analytics implementation restraints in
healthcare and their impact
Image source: Verified Market Research
Retail & ecommerce
| The market for big data analytics in retail is expected to grow by around two times in value, reaching $22.37 billion by 2030, up from $10.54 billion in 2025. | |
|---|---|
| The CAGR at which the big data analytics market in retail will grow is forecasted to be 16.24% during 2025–2030. |
Finance
| By 2030, the big data analytics in banking market is projected to grow to $29.87 billion, up from $10.56 billion in 2025 | |
|---|---|
| The big data analytics in banking market is forecasted to grow at a CAGR of 23.11% during 2025–2030. | |
| By solution type, advanced analytics accounts for 41.42% of big data analytics in banking market revenue, which is indicative of the extensive application of machine learning models to support financial analytics operations. |
Scheme title: Big data analytics in banking market growth by region
Data source: Mordor Intelligence
Automotive
Scheme title: Growth of the global market for big data in the automotive industry
Data source: Mordor Intelligence
| The market for big data in the automotive sector is anticipated to expand at a CAGR of 16.55% between 2026 and 2031. | |
|---|---|
| By application, intelligent transportation and connected vehicles account for 42.7% of the big data market share in the automotive sector, growing at a 16.95% CAGR. |
Manufacturing
| The size of the global market for big data in manufacturing is expected to increase from $7.94 billion in 2025 to $30.15 billion in 2034. | |
|---|---|
| The global big data in manufacturing market is expected to expand at a CAGR of 16.1% from 2026 to 2034. | |
| With a 39.5% market share in 2025, North America leads the big data in manufacturing sector. |
Logistics
| The size of the big data market in logistics was valued at $6.3 billion in 2025 and is estimated to reach $44.5 billion in 2035. | |
|---|---|
| The big data in the logistics market is expected to grow at a CAGR of 21.5% from 2025 to 2035. | |
| With over 45% of the global market for big data in logistics, North America holds the largest market share, followed by Europe with about 30% and Asia-Pacific with about 20%. | |
| The most popular application of big data in the logistics sector is supply chain management, with a market value of $20 billion . |
Construction
| The market for big data analytics in construction was worth $9.83 billion in 2025 and will have an estimated value of $14.37 billion by 2030. | |
|---|---|
| The market for big data analytics in construction is forecasted to expand at a CAGR of 7.8% from 2026 to 2030. | |
| The big data analytics in construction market is dominated by the solution component, with a 55% share of the overall market. | |
| China leads the big data analytics in construction market with a 14.9% growth rate, followed by India with 13.8%, owing to fast urbanization and considerable infrastructural development. |
Itransition’s big data services
We implement big data solutions aligned with clients’ business strategies, enabling them to harness measurable value from big data to make informed decisions, enhance customer experiences, and improve revenue.
Consulting
Our data engineers develop a holistic big data strategy tailored to your business needs and help bring it to life.
- Big data requirements elicitation
- Creating a roadmap for big data solution implementation
- Assistance with developing and deploying big data solutions
- Post-implementation support
Implementation
Itransition offers big data implementation services, setting up the right technologies, processes, and infrastructure to help businesses turn their big data into useful insights.
- Analysis of business requirements and technical capabilities
- Assessing the current data quality and data management workflows
- Developing/configuring suitable storage solutions, such as data lakes or data warehouses
- Defining data governance frameworks
- Setting up data pipelines for data cleaning, transforming, and structuring
- Implementing solutions for big data analysis
- Delivering customizable dashboards and reporting functionality
- User onboarding
- Post-launch performance, security, and usability monitoring and troubleshooting
Derive valuable insights from your big data with Itransition
Transforming large volumes of complex data into meaningful insights
With data being extremely important for decision-making, businesses will continue to implement Internet of Things, business intelligence, analytics tools, and big data technologies to collect and use as much information as possible from diverse data sources.
However, implementing big data solutions can be challenging due to the need to handle diverse data types and formats while ensuring robust data privacy. That’s where partnering with a trusted big data company like Itransition becomes essential for properly capturing and turning big data into actionable insights.
FAQs
The big data market is steadily growing, fueled by the increasing volumes of operational, production, and personal data as well as the need to process these datasets to derive hidden data patterns, market trends, and data correlations and make informed decisions. Key drivers of big data adoption include massive online user activity on search engines, social media, and websites, the widespread implementation of cloud computing solutions, and the proliferation of IoT devices and artificial intelligence.
The main trends for big data include the increasing adoption of AI-powered solutions for natural language processing and real-time analytics, the expansion of edge computing to ensure low-latency data processing, and growing interest in quantum computing to solve complex data problems.
There are four main types of technologies used when dealing with big data:
- Data storage solutions for hosting big data
- Data mining technologies, including machine learning that help uncover patterns and other valuable information from large data sets
- Data analytics systems, which help transform raw data into valuable insights
- Data visualization solutions, presenting big data analysis results in the form of charts, graphs, dashboards, and reports
While AI software can collect and analyze data faster and more accurately than people, it will not replace big data analysts altogether, as it cannot replace human judgment and strategic thinking. However, the widespread adoption of AI tools, including those for data analysis, will reshape the role of data analysts, so they will have to develop skills that AI cannot replace and learn to use AI-powered solutions to boost operational efficiency amid increasing workloads.
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