Big Data Statistics: Number of Data Generated per Day

List of Big Data Statistics and Key Figures

1. Volume of Data Created

In 2023, the number of data produced per day is enormous, every minute the internet sees 241 million emails sents, illustrating the intensity of digital communication and the search for information online.

The Video streaming, with Netflix and its 209 million subscribers, dominates online media consumption, benefiting from improved digital infrastructures.

Messaging apps like WhatsApp, Facebook Messenger, and Telegram, popular for their extensive services, including photos, videos, and free calls, are redefining global communication.

• In 2024, the total volume of digital data created in the world will reach 147 zetta bytes, compared to only 9 zetta bytes of data in 2013.
• 1 zettabyte = 1 trillion gigabytes, or 1 followed by 21 zeros!
• Each human being generates an average of 1.7 megabytes of data per second.
• 80 to 90% of this data is unstructured (images, videos, audios, social networks...).
• To download all the data on the Internet, it would take more than 180 million years for an individual.

These figures are dizzying and illustrate the titanic challenge of processing such large amounts of data. But they also offer huge opportunities for businesses that can extract actionable insights from them. All of this shows the complete breadth of the data generated and the growing importance of analyzing it.

2. A Booming Market

In its recent history, in 2021, the value of the global data analytics market exceeded 240 billion US dollars.

A significant increase is expected, with an expected market value of over $655 billion by 2029, stressing the rise and increasing importance of data analysis issues or problems in the global economy.

• The global market for big data and analytics is worth 274 billion dollars in 2024.
• It is expected to reach 655 billion dollars in 2029, an average annual increase of +19%.
• The market for big data analytics in the banking sector is expected to reach 62 billion dollars in 2026.
• In scientific research for health, this market will weigh 68 billion in 2026, 4 times more than in 2018.
• 97% of companies are actively investing in big data and AI.

These figures show that companies have fully understood the strategic challenge of Big Data.

They are devoting colossal budgets (and are right) to develop ever more advanced analytical capabilities and gain a competitive advantage.

3. Transformed Sectors

According to a global survey conducted in 2023, a growing number of businesses believe that they are using data effectively.

More than three-quarters of respondents said they drive innovation through data, while half saw their businesses as competitive through data and analytics.

• Thanks to recommendation algorithms based on Big Data, Netflix saves $1 billion a year in customer loyalty.
• Data-driven businesses are 23 times more likely to win customers.
• 72% of manufacturing executives rely on big data analytics to boost productivity.
• 83% of users TikTok Indonesians have a better opinion of car brands after seeing them on the app.

These concrete examples show how Big Data makes it possible to better understand and serve their customers, to optimize their operations and to innovate. Marketing, finance, health, media... no sector is immune to this revolution.

4. Obstacles and Challenges to Overcome

The global big data security market is expected to know an increase of 14.90% between 2023 and 2032.

Valued at $19.76 billion in 2022, the market is expected to reach $55.16 billion by 2032, reflecting the growing importance and rapid evolution of technological security.

• For 95% of companies in the world, the main challenge is dealing with unstructured data.
• Half of managers believe that current data solutions lack flexibility.
• Only 25% of employees are actively using analytics and BI tools.
• Les Cyber scams jumped by 400% since the start of the health crisis.

While the potential is immense, its democratization still faces problems such as lack of skills, silos, volume, security breaches or resistance to change.

5. Towards an Increasingly Data-Driven Future

In 2023, video represented 65.93% of total data volume on the Internet, an increase of 24% compared to 2022.

This figure includes everything from TV to streaming and video downloads.

The marketplace, gaming, and social media sectors each contributed to more than 5% of traffic, confirming video as the main component of online business

• By 2026, 30% of the world's data will be processed in real time.
• The market for”Analytics-as-a-Service“(AaaS) will reach $69 billion in 2028.
• 72% of businesses plan to incorporate AI into their data visualization tools.
• The number of connected objects, the main suppliers, will jump to 29 billion in 2030.

One thing is certain: the flood of databases is far from receding.

To remain competitive, companies will have to rely more than ever on cutting-edge technologies such as artificial intelligence, quantum computing or edge computing.

In an ultra-connected and digital world, data and its challenges are the new cornerstone of business performance.

6. Correlation of Big Data and Artificial Intelligence

Big Data and Artificial Intelligence (AI) are two transformative forces of our time. But it is their convergence that promises to change our societies in the coming decades.

• According to a 2022 study, there are 50% chance that AGI (artificial general intelligence) will be reached by 2059.
• Experts like Geoffrey Hinton and Elon Musk even talk about a deadline between 5 and 20 years.

To make this leap to AGI, researchers are banking on a new generation of AI models powered by pharaonic quantities of data.

Beyond the quantitative aspect, the road to AGI will also involve algorithmic innovations:

• Unsupervised learning, symbolic reasoning, bio-inspired neural architectures, reinforcement learning...
• Cicero (Meta) : language module + strategic reasoning + long-term memory. Performs as well as a human in the Diplomacy game.
• Gato and Flamingo (DeepMind) : trained on text, images and interactions. Outstanding ability to adapt to a variety of tasks.

Challenges and opportunities The prospect of an AI with superhuman abilities, nourished by the flow of Big Data, is both fascinating and worrying.

• opportunities : solving major challenges such as climate change, diseases, poverty...
• Challenges : existential questions about our place in the universe, risks of an uncontrollable AI...

One thing is certain: the convergence of Big Data and The AI promises us unprecedented upheavals.

It is up to us to guide and manage this technological revolution now so that it benefits the greatest number of people.

The advent of AGI is no longer science fiction, it is a horizon that is fast approaching. Let's make sure that this new chapter in the human adventure brings hope and progress!

7. Ranked Companies

In the world of Big Data, some companies stand out for the massive amount they generate and collect.

Here is a ranking of the companies that produce the most data in the world every day

Thanks to their global reach and large user base, all of them have become major players in this ecosystem.

8. Hardware Solutions for Storage

Here is an overview of the main hardware solutions used for storage, along with some key figures and statistics:

Distributed File System

Distributed file systems, such as Hadoop Distributed File System (HDFS) and Google File System (GFS), are designed to store and manage massive data across server clusters.

They distribute information across multiple node forms, ensuring high availability and fault tolerance.

• HDFS is used by over 70% of organizations that have adopted Hadoop for storing and processing big data.
• HDFS can store multi-terabyte files and supports clusters of up to thousands of nodes.

According to a study by MarketsandMarkets, the global distributed file system market is expected to reach $24.45 billion by 2026, with an increase of 14.2% between 2020 and 2026.

Object Storage

Object storage is a storage approach that manages data as objects, rather than as files or blocks.

Each object is associated with metadata and a unique identifier, allowing fast and scalable access to data.

• Amazon S3, the AWS object storage service (Amazon Web Services), stores more than 100 trillion objects and processes an average of 63 million requests per second.

According to an IDC study, the global object storage market is expected to reach $129.19 billion by 2026.

NoSQL Storage System

By definition, NoSQL databases, such as MongoDB, Cassandra, and HBase, are designed to store and manage unstructured and semi-structured data at scale:

• MongoDB, a popular NoSQL database, is used by over 18,000 customers in over 100 countries, including eBay, Adobe, or SAP.
• Cassandra, another NoSQL database, can handle up to 600 terabytes of data and 1 million write operations per second across a cluster of 400 nodes.

The global NoSQL database market is expected to reach $10.16 billion by 2026.

Memory Storage

Memory storage uses random access memory (RAM) to store and process data, offering significantly better performance than hard drive storage systems.

• Apache Spark, an in-memory computing framework, can process data up to 100 times faster than disk-based storage systems.
• SAP HANA, an in-memory processing platform, can process 1 billion rows of data in under one second.

The global market is expected to reach $12.12 billion by 2026.

Hyperconverged Infrastructure

Hyperconverged infrastructures combine compute, storage, and virtualization in a single system, simplifying the management and deployment of big data resources.

• Nutanix, a leader in hyperconverged infrastructure solutions, has more than 17,000 customers in 140 countries, including companies such as JetBlue, Volkswagen, and Hyundai.
• Dell EMC vxRAIl, another popular hyperconverged infrastructure solution, saw a 60% increase in revenue in Q4 2020.

The global hyperconverged infrastructure market is expected to reach $27.1 billion by 2026.

These numbers and statistics highlight the increasing importance of hardware solutions in the big data ecosystem. Companies are investing heavily in these technologies to effectively manage ever-increasing volumes of content and take full advantage of the potential of information.

9. Ranking of Countries That Produce the Most Big Data

The production of Big Data is dominated by several countries, thanks to their technological infrastructures and their connected populations. Here is a ranking based on the numbers:

• USA. : Around 40% of global data production, with giants like Google, Amazon, Meta, Microsoft, and IBM.
• China : Contributes to 20% of global production, thanks to companies like Alibaba, Tencent, and Baidu.
• India : Produces around 12% of the world's data, with leaders like Tata Consultancy Services and Infosys.
• European Union : Around 15% of global production, mainly from countries such as Germany, France and the United Kingdom.
• Japan : Responsible for around 7% of global production, with companies such as Sony, Panasonic and Toyota.

10. Mobile Applications

In the age of big data, mobile applications play a crucial role in the production and collection of data.

With billions of active users around the world, mobile applications generate colossal amounts of information every day.

Here is a ranking of the mobile applications that produce the most data:

11. Social Media

Social networks have become an essential source of data for businesses.

Every day, billions of users share information, interact with content, and communicate with each other, generating a colossal amount of usable data:

FAQs

How much data is generated every day?

By 2024, it is estimated that the volume of data generated every day in the world will reach a volume of 463 exabytes (463 billion gigabytes).

What are the main trends in Big Data?

The main big data trends in 2024 include real-time analytics, artificial intelligence and machine learning, edge computing, and the democratization of access to data analysis tools.

What are 3Vs?

These are the initials for Volume (quantity of data), Velocity (speed of data processing), and Variety (diversity of data types).

Conclusion

In the end, big data statistics illustrate its growing importance and its many challenges.

This new era brings exciting opportunities, but also raises crucial questions about confidentiality and ethics, especially with social networks.

Those who do not adapt by not giving themselves the means and by forgetting all the recommendations risk being left behind by competitors who are more responsive and better aligned with the expectations of their customers.

Transition is not an option, but a necessity to remain competitive in a dynamic environment.

For every business, adoption is essential to innovate, meet customer needs and ensure sustainable growth.