65+ Big Data Statistics to Know in 2026

Every minute of every day, the world produces more data than ever, and the software built to make sense of it has grown into a market worth hundreds of billions of dollars. What stands out is how little of that data actually gets used.

The numbers tell two stories at once. Data creation keeps increasing, and spending on the tools that capture, store, and analyze it keeps rising alongside it. Understanding both sides is useful no matter how your business uses data today.

To see where big data really stands in 2026, it helps to look at the macro forecasts from research firms and the on-the-ground signal from buyers at the same time. On G2, 100+ products compete in the Big Data Analytics category, and their reviews show how teams actually adopt and rate these tools. The statistics below pull both together, and each figure is sourced to the organization that produced it.

In this piece, I pull together the big data statistics that matter most in 2026, grouped by how much data we create, what the market looks like, who is hiring, where data lives, and what review data says about the tools themselves.

Big data statistics in 2026: At a glance

Here is a snapshot of where big data stands this year, across data creation, market value, talent, and the tooling that powers it.

Now let us go deeper into each area and what the figures actually signify.

How much data do we create in 2026?

No single odometer can capture it, but the freely published measures all point the same direction: up. Network traffic, internet users, and connected devices each tell part of the story.

• Global mobile data traffic is projected to reach about 310 exabytes per month by 2031, continuing a multi-year rise.
• Most of that traffic is video. According to Ericsson, video made up 76% of all mobile data traffic at the end of 2025, and total mobile network data traffic reached 200 exabytes per month in the fourth quarter, with growth driven mainly by streaming and social video.
• 6.12 billion people were using the internet at the start of April 2026, about 73.8% of the world's population.
• The number of connected IoT devices reached 21.1 billion by the end of 2025, a 14% increase over 2024, and is forecast to hit 39 billion by 2030.
• AI has become a data source in its own right. An Ahrefs study that ran 900,000 newly created web pages through its AI-content detector found that 74.2% contained AI-generated content as of April 2025, though only 2.5% were purely machine-written, with most pages a blend of human and AI work.
• Social platforms are the largest single source of user-generated content. DataReportal counts 5.79 billion social media identities as of April 2026, growing by 9.3 new users every second; each contributing a steady stream of text, images, and video, the unstructured data that makes up the bulk of what big-data systems ingest.
• Commerce generates data with every click and transaction. Global e-commerce sales are projected at about $7.4 trillion in 2026, while the total value of digital payments is forecast to reach $26.89 trillion — each order, payment, and browsing session producing transactional and behavioral records at scale.

Where is big data stored in 2026?

As data volumes rise, more of it is moving to the cloud, a growing share of it is sensitive, and a small group of hyperscalers now holds most of the capacity it sits on.

• According to Thales, 54% of all data stored in the cloud is now classified as sensitive, up from 47% in 2024, yet only 8% of organizations encrypt 80% or more of it.
• Thales also finds that 64% of enterprises rank cloud security among their most pressing security disciplines, and 55% say securing the cloud is more complex than on-premises environments, up from 51% a year earlier.
• The capacity itself is consolidating. Hyperscale operators held 44% of total data center capacity in early 2025 across 1,189 facilities, with on-premises at 34% and colocation at 22%, and hyperscale is set to reach 61% by 2030.
• Worldwide public cloud end-user spending reached about $723.4 billion in 2025, up 21.5% year over year, and Gartner expects 90% of organizations to adopt a hybrid cloud approach through 2027.

What happens online in 60 seconds?

In a single internet minute, the world runs 5.9 million Google searches, views 3.4 million videos, and sends over 250 million emails. According to Domo's Data Never Sleeps 12.0, here is what happens every 60 seconds:

• 5.9 million Google searches are run.
• 3,472,222 videos are viewed on YouTube.
• 138.9 million reels are played on Facebook and Instagram.
• 251.1 million emails are sent.
• 18.8 million text messages are sent.
• 362,962 hours of content are streamed on Netflix.
• 229 million minutes are spent in Microsoft Teams meetings.
• 1.04 million messages are posted on Slack.
• 16,000 videos are uploaded to TikTok.
• $43.6 million is spent by online shoppers during Cyber Week.

Every one of those actions becomes a row in a database somewhere, which is why the software that queries and analyzes it has become essential.

How are businesses using big data?

Data is growing faster than most companies can put it to work, and that gap is what drives big data analytics adoption. According to Fortune Business Insights, enterprises' stored data is estimated to grow roughly ten times year over year, yet nearly 90% of it goes unused.

What G2 reviews reveal: across the category, big data analytics skews enterprise. Among reviewers of the tools on G2's Summer 2026 Grid for Big Data Analytics, 42% come from enterprises with 1,000 or more employees and just 25% from small businesses. 

Is big data analytics worth the investment?

For all the money flowing into big data tools, the more useful question is whether buyers feel they get their money back. G2's review data suggests they do, and by a wide margin.

What G2 reviews reveal: According to G2's 2026 Grid report on Big Data Analytics, buyers recoup their investment in roughly 12 months and report 54% average user adoption. Satisfaction runs high: on average, 91% say the tools meet their requirements, 89% would recommend them, 88% rate them easy to use, and the category carries an average Net Promoter Score of 64.

What is the size of the big data market?

Big data's business value has turned into a very large market. Depending on how you draw the boundaries, the totals run from the high hundreds of billions into the trillions.

• According to Fortune Business Insights, the big data analytics market was valued at $394.70 billion in 2025, and is projected to grow from $447.68 billion in 2026 to $1,176.57 billion by 2034, a 12.80% CAGR.
• The broader big data technology market, also tracked by Fortune Business Insights, was valued at $454.00 billion in 2025 and is projected to grow from $521.09 billion in 2026 to $1,412.45 billion by 2034, a 13.30% CAGR.
• The big data and business analytics market was valued at $309.68 billion in 2025 and $343.4 billion in 2026, and is projected to reach $970.44 billion by 2035, a 12.1% CAGR.

Those totals differ because they measure different things. Big data analytics, big data technology, and big data and business analytics are distinct market definitions, so it is worth checking which one a figure refers to before quoting it.

Within the big data analytics market specifically, Fortune Business Insights puts the 2026 segment leaders as software (47.15% share, and the fastest-growing), large enterprises (60.67%), data discovery and visualization (57.34%), and BFSI by vertical (22.31%), with healthcare growing fastest.

How does the big data market break down by region?

North America leads, with Europe and Asia Pacific close behind, and every region is growing into 2026. The figures below come from the same Fortune Business Insights report.

At the country level, Fortune Business Insights projects the United States market to reach $248.89 billion by 2032. By 2026, it puts the UK at $27.57 billion and Germany at $32.95 billion, while in Asia Pacific, China reaches $44.294 billion, Japan $24.772 billion, and India $16.621 billion.

What other big data technologies are growing?

Beyond cloud storage, the engines that process big data, including Hadoop and Spark, data lakes, and their successors, are still expanding as markets of their own.

• The Hadoop big data analytics market is projected to reach $74.8 billion by 2034, a 12.55% CAGR from 2026 to 2034.
• The data lake market was valued at $22.8 billion in 2026 and is projected to reach $61.84 billion by 2031, a 22.08% CAGR.
• Augmented analytics, which uses AI and machine learning to automate data preparation and surface insights, is one of the faster-growing segments. Fortune Business Insights values it at $20.04 billion in 2026 and projects $113.43 billion by 2034, a 24.20% CAGR.
• Data observability, the practice of monitoring the health and reliability of data pipelines, is a smaller but fast-emerging market. Mordor Intelligence puts it at $3.51 billion in 2026, growing to $6.03 billion by 2031, an 11.42% CAGR.
• Edge computing is moving processing closer to where data is created, pushed by the spread of IoT, 5G, and on-device AI. Estimates of its market size vary widely by scope, but Fortune Business Insights values it at $25.63 billion in 2026 and projects $267.42 billion by 2034, a 34.10% CAGR.
• Data mesh, which decentralizes ownership of data to the teams closest to it, was valued at $1.95 billion in 2026 and is projected to reach $7.11 billion by 2034, a 17.56% CAGR.
• Serverless data processing, which removes the need to manage infrastructure, was valued at $2.97 billion in 2026 and is projected to reach $9.41 billion by 2034, a 15.52% CAGR.

What G2 reviews reveal: Reviewers rate the core big data capabilities of these tools highly. On average, big data analytics products on G2 score 92% on data querying, 90% on data lake support, 90% on data transformation, 88% on multi-source analysis, and 86% on Hadoop integration.

What are the biggest big data challenges?

The hardest part of big data in 2026 is not collecting it. It is trusting it, connecting it, and turning it into something usable. Precisel and Drexel University's LeBow College of Business, capture the trust gap clearly.

• 64% of data professionals name data quality their top data integrity challenge, up from 50% in 2023.
• 51% cite data governance as a major challenge, up from 27% in 2023, and 67% say they do not completely trust their data for decision-making, up from 55% the prior year.
• 77% rate their own data quality as average at best, and the most-cited blocker to high-quality data is inadequate tools to automate data quality, at 49%.
• Even high-quality data is wasted if it is trapped. The average enterprise runs 897 applications but has only 29% connected, leaving an estimated 19% of company data siloed or unusable, and 70% of data leaders believe their most valuable insights are locked inside that inaccessible 19%.

What G2 reviews reveal: even well-reviewed tools have gaps. Across G2's Summer 2026 Grid for Big Data Analytics, the lowest-rated capabilities are mobile user support at 77% and report design at 82%, both worth probing in a demo if either matters to your team.

Is big data still a good career in 2026?

Demand for people who can work with big data remains some of the strongest in the US labor market, and it still outpaces supply. The figures here come from the U.S. Bureau of Labor Statistics.

• US data scientist employment is projected to grow 34% from 2024 to 2034, much faster than the average for all occupations, adding about 82,500 jobs to a 2024 base of 245,900. That makes data scientist the fourth fastest-growing occupation in the US economy.
• There are an estimated 23,400 data scientist openings per year, on average, over the decade, and the median annual wage was $112,590 in May 2024.
• More broadly, computer and IT occupations earned a $105,990 median wage in May 2024, more than double the $49,500 median for all occupations, with about 317,700 openings projected each year.

What does the future of big data look like?

Big data's next chapter is converging with AI, and the biggest gains are expected in real-time and physical-world data.

• More of that data will come from the physical world. Gartner projects that by 2029, AI agents will generate 10 times more data from physical environments than all digital AI applications combined, as AI gets embedded in machines and devices and collects data in real time.
• The streaming analytics market is growing quickly, from $35.17 billion in 2025 to $146.59 billion by 2030, a 33% CAGR, with North America the largest region and Asia Pacific the fastest-growing.

What do these big data statistics mean for you?

Data growth is not slowing down, but the advantage has shifted. The companies that win in 2026 are not the ones sitting on the most data. They are the ones that trust it, connect it, and analyze it quickly, which is why challenges like data quality and trapped data now matter more than raw volume.

On the tooling side, the bar is high. Buyers report strong satisfaction, a 64 average Net Promoter Score, and roughly 12-month payback on the big data analytics tools they adopt.

Learn more about big data examples and applications to see how it's transforming processes across industries.

*This article was originally published in 2024. It has been updated in 2026 with new information.