28 Astonishing Big Data Statistics to Analyze

Today, big data statistics are widely used in medicine, agriculture, environmental protection, and across many other industries. With the rising digital age, there is now an opportunity to use big data to make precise predictions, trend analyses, and observations about almost anything.

The biggest benefits of big data are related to understanding data-driven marketing, identifying employee efficiency processes, and improving customer engagement.

Still, someone has to know how to do all of that, creating a huge new market for data science analysts and more.

Big Data Stats (Editor’s Choice)

  • Every human on Earth generated 1.7 Mbs of information per second in 2020
  • About 65% of organizations claim they’ll invest more in hiring data and analytics talent
  • The amount of data generated per second in the financial industry will grow by 700% in 2021
  • Businesses that use big data see a profit increase of 8% to 10%
  • Only 26% of companies managed to achieve data-driven culture
  • In 2018, the US was the largest market for big data
  • By 2025, the global big data market is expected to grow by $247.30 billion
  • By 2025, 90 zettabytes of data will belong to IoT devices

General Statistics for Big Data

The internet may still be in its beginnings, but the amount of data that is being collected across the globe as a result of digitization is unlike anything seen before. Big data is now a possibility.

The benefits of analyzing massive data sets has the potential to create precise and insightful predictions and descriptions on so many facets of human life and business.

1. It would take 181 million years for someone to download all the data from the internet.


Data growth statistics for 2021 indicate that people have so much information stored online that it would take 181 million years to download it all. Even more astonishing is that 90% of that data was generated over just the last two years, showing just how much data is being created every single day.

2. Every human on Earth generated 1.7 Mb of information per second in 2020.


The amount of data people generate is rapidly growing with an increasingly online culture worldwide. During 2020, every human in the world created 1.7 Mb of data per second, based on big data growth statistics. It’s no wonder since more than ever, we live, breathe, work, and play all online. 

3. In 2018, the US was the largest market for big data. 


The US has had an incredible impact on the big data market and its related growth. Notably, the US was the largest market in 2018, delivering about $88 billion and holding about half of the global market’s worth. Western Europe was the second-largest market with a revenue of $35 billion.

4. By 2025, the global big data market is expected to grow by $247.30 billion.


When it comes to the total big data industry size, its global market is expected to grow by $247.30 billion by 2025, with an 18% CAGR during the forecasted four-year period. One of the main contributors to this growth is the interest and pursuit of developing smart cities.


The three major trends that help with the big data revolution include the rapid increase of the amounts of data available, accelerated and affordable data storage, and the evolution of machine learning. All three are crucial for proper big data analytics and utilization. 

Big Data Growth Statistics for 2021

Big data is becoming an ever-expansive tool mainly due to the amount of information that can be recorded in today’s digital age.

The use of Google search alone provides enough data to run analyses on entire population sectors, and the expansion and usage of smart technology and Internet of Things also contributes to these mass data sets. Here’s a closer look at just how much data will grow over the next few years. 

6. Google processes 40,000 search queries each second.


According to big data statistics, the search engine processes 40,000 searches each second. That’s about 3.5 billion daily searches and 1.2 trillion yearly searches globally. For comparison, when it was founded in 1998, it had only 10,000 searches per day. 

7. Google accounts for 78% of the global web search share.


When it comes to market share, Google hosts 78% of web searches globally. Baidu is second, with 9.9%. Yahoo is in third place, with 5.8%, and Microsoft has the lowest percentage of global yearly searches, with 3.1%.

8. Big data market research shows that approximately 80% to 90% of data people generate is unstructured. 


There are three types of big data: structured, semi-structured, and unstructured. About 80-90% of data that people generate belongs to the unstructured group.

This type of data is harder to analyze since only a few softwares can provide solutions to sort the information properly. Examples of unstructured data are media like photos and videos, voice recordings, surveillance data, and much more. 

9. Companies generate 2,000,000,000,000,000,000 bytes of data per day. 


All industries combined generate 2,000,000,000,000,000,000 bytes of data each day, according to big data statistics from 2021. It’s no question that our digital world creates immense amounts of data everyday, but even more so, its future value is what’s notable. This data will be worth around $77 billion by the end of 2023, experts report.

10. With IoT devices approaching 4.16 billion units, big data from IoT will exponentially increase. 


IoT is a growing network of smart and automated devices, many of which record immense amounts of data to function and connect with the rest of the network. As such, the amount of information with the potential for big data analysis is expanding on a daily basis. Big data statistics from 2021 show that 127 new devices connect each second, generating about five quintillion bytes of data each day. 

11. By 2025, 90 zettabytes of data will belong to IoT devices. 


By 2025, worldwide data collection will reach 175 zettabytes, 90 of which will belong to IoT devices. Moreover, 51% of this data will be in data centers, and 49% will be stored in the public cloud. 

12. World public cloud spend will grow 18% in 2021.


The utilization of public cloud services is greater than ever before. According to the 2021 data growth statistics from Gartner, the global public cloud spend will grow by 18% in 2021, led by organizations quickly adapting to the digital demands implicated by COVID-19 restrictions. 

13. By 2023, the majority of organizations will have their data stored on the cloud.


Cloud storage is already present and brings various benefits to companies that use it. For example, it’s more affordable, allows for better scalability, and is more secure. As cloud security becomes more reliable, it’s only a short matter of time before most organizations use this method of data storage. 

Big Data Popularity: The Benefits of Using Big Data

The numbers don’t lie, and they’re changing the game of almost every major industry across the globe. While it once may have been adequate to follow gut instincts or be business savvy, the modern enterprise now needs to use big data analyses to stay competitive in today’s market.

With quantifiable benefits such as greater ROI, employee efficiency, and customer retention, big data is changing how we do business. 

14. Big data stats show that businesses using big data see a profit increase of 8% to 10%. 


Big data has become an irreplaceable technology in business. So much so that those businesses that use it see a profit increase of 8-10%.

Big data allows businesses to extract more information about their customers and identify new opportunities, leading to smarter business moves, more efficient operations, and according to big data business application statistics, happier customers.

15. Netflix saves $1 billion each year because it leverages big data.


Netflix is the perfect example of how companies can benefit from using big data to increase revenue. Netflix uses big data to improve customer retention, saving up to $1 billion each year because of the strategic use of customer data. 

16. Data-driven companies are 23x more likely to get customers.


There’s nothing wrong with trusting your gut, but big data facts show that companies who opt for this data-informed strategy are 23x more likely to gain new customers and six times more likely to retain current customers. 

17. About 79% of employees in companies believe that failing to utilize big data can lead to bankruptcy. 


Data-driven employees are aware that big data can bring multiple benefits to a company. So much so that 79% of them believe that failure to use big data may risk bankruptcy. For most, the ability to deny the significance of big data analytics is quickly becoming obsolete, with 51% of companies agreeing that big data will change the way they do business. 

18. About 94% of enterprises claim big data is crucial for business growth. 


The potential uses of big data are numerous, and almost all companies believe it’s a critical component of success. As business is conducted increasingly in a digital atmosphere, the collection, organization, and big data statistical analysis is a central component to addressing weak points in business strategy and becoming more efficient. 

19. Only 26% of companies managed to achieve data-driven culture. 


Data-driven culture refers to replacing the gut feeling with decisions based on pure information. The use of big data to inform business processes creates evidence-based best practices, with outcomes that can be quantitatively measured. Even though businesses are aware of the importance of big data, only 26% have managed to achieve a data-driven culture. 

Big Data Jobs Statistics: More Data, More Data Analysts

As the digital stratosphere becomes even more pervasive in our daily lives and tasks, the information collected will only continue to grow.

Most businesses acknowledge the untapped potential of using big data to make business strategies, but few are able to analyze or even organize it properly in order to do so.

Data science analysts are becoming a critical part of any industry team and are well worth the investment. 

20. Only 3% of employees can find the data they need quickly to make a business decision. 


According to big data trends, many organizations claim that the collection and analyses of these data sets are crucial to success. Still, only 3% of employees can find the data they need fast enough to make a business decision, and 60% of them report it taking days.

21. 63% of companies can’t collect insights from big data.


Over half of businesses struggle to make use of collected data before it becomes irrelevant, according to big data industry trends. Mismanagement, lack of organization, and low data analysis skill sets are some of the major reasons for missing the opportunity to see what big data has to say. 

22. Job listings for data science reached 2.7 million in 2020.


Enterprises know how crucial big data is, but they also lack the talent among employees to utilize that data. According to big data growth statistics in 2020, this need for qualified professionals has led to an increased job listing for data science, so much so that the number reached 2.7 million available jobs in 2020. 

23. About 65% of organizations claim they’ll invest more in hiring data and analytics talent. 


Big data analysis is a unique skill set that is increasingly valuable. Based on the latest facts about big data, 65% of companies say they need to invest in finding someone to work with big data. Notably, 75% of large enterprises are willing and planning to make the investment. 

24. By the end of 2021, the business intelligence and analytics software application market will reach $16 billion. 


The market size for business intelligence and analytics software applications is rapidly growing, and by 2024, it’s expected to reach 17.6 billion. Enterprises will use these programs to collect and analyze current data that will help them reach corporate goals. 

Big Data Industry Statistics

Big data is relevant across all industries, and many are already taking the steps towards utilizing its potential. Some markets are more privy to big data use—such as finance, manufacturing, marketing, and healthcare. 

25. About 14% of banking and 12% of discrete manufacturing industries provide big data investments. 


One of the industries that utilize big data the most is banking. About 14% of the financial industry invests in big data industry analysis for making precise predictions and estimations. Discrete manufacturing comes in second to streamline processes and improve efficiency. 

26. By 2025, the big data analytics market in the healthcare industry will be worth $67.82 billion.


There’s an evident rise in big data adoption in the healthcare industry. As a result, there’s an increase in demand for analytics solutions to help health systems management. This is why big data growth projections show that by 2025, the big data analytics market in healthcare will be worth $67.82 billion. 

27. The amount of data generated per second in the financial industry will grow by 700% in 2021.

(Sigma Computing)

The banking sector also generates vast amounts of big data. In 2021, the amount of generated information in the financial industry will grow by 700%. Still, the financial service companies have the lowest rate of analytics and business analyses adoption, according to big data industry stats. 

28. Global big data analytics revenue will reach $68 billion by 2025.


The global big data analytics market will also grow with a compound annual growth rate of 30%, likely reaching $68 billion by 2025. Comparatively, it was worth just $15 billion in 2019. 


The potential in the amount of data recorded every day in all types of activities is undeniable. Big data statistics can provide calculated and evidence-based predictions and observations that simply can’t be provided without it.

Companies that invest in big data analyses show greater ROIs, improved employee efficiency, and better customer retention than their competitors. As such, the demand for data scientists is extensive, as most companies may know that big data can help them but have no idea how to use it. 

People Also Ask

Big data is defined as large sets of information that are too complex for traditional data analytics applications. In simple terms, big data contains more variety and is collected faster from various data sources. 

Once the data sets get analyzed and placed in groups, they receive a certain value or show a certain pattern. When it comes to statistics, it’s one of the key disciplines related to big data. Since big data is often delivered at random, statistical methods help to organize it better and identify trends.

At the moment, the popularity of big data is just beginning. While individuals can hardly find the benefits of big data, organizations are working on improving the adoption of this technology. About 52% of global organizations are using big data, and 38% more plan to use it in the future. 

Some of the most common industries that use big data include banking and security, media and entertainment, healthcare, education, manufacturing, government, retail and wholesale, and others. Spotify, Netflix, and Starbucks are some of the companies that use big data as well.

Statistics is defined as the science of collecting, analyzing, and understanding data, and as such, its relationship with big data is crucial. Since big data often comes in clusters of random information, statistics can help sort the information out and give answers. 

Statistics are also crucial in ensuring that meaningful and accurate information is extracted from big data. Besides statistics, big data also requires machine learning that involves AI. Still, with statistics, organizations can overcome uncertainty, deal with missing data, develop models for analyses, and so on.

There are three main types of big data: structured, unstructured, and semi-structured. Structured data is the easiest to work with. It involves information sorted in groups and columns, defined by set parameters. 

Unstructured data is the opposite, where nothing is categorized per parameter. Reading unstructured data is challenging, and the worst part about working with it is teaching the machine to understand it. Finally, semi-structured data includes unstructured data with metadata attached to it. Semi-structured data can be a huge asset if people can teach the AI to match patterns with meta.

Big data growth trends show that humans generate more data today than they ever did before. In 2020, each person generated 1.7 megabytes of information per second. Today, the accumulated world data is around 4.4 zettabytes. In just a year, that number will grow to 44 zettabytes. 

When it comes to the big data industry, the increasing volume of data, cloud computing, and IoT are driving growth. The global big data market was worth $37.34 billion in 2018. By 2027, it’s expected to reach $105.08 billion with a CAGR of 12.3%.

Statistical data is the raw information used to generate the statistics. Examples of statistical data can be a person’s weight or height or the number of stocks someone owns. There are two types of statistical data: numerical and categorical.

Big data represents the massive amount of randomly collected different types of information in one cluster. Big data is collected faster than statistical data, and there are three types: structured, unstructured, and semi-structured. Big data statistics show that structured data is easiest to work with.