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Have you ever looked at the night sky and thought to yourself: How many stars are out there? Well, you could ask a similar question about big data. While nothing quite compares to the infinity of the universe, the amount of data generated throughout the expansion of the internet certainly comes close.
We dare you to check out the big data statistics we’ve compiled below. Once you’ve processed these 30 stats, we’re sure you’ll have a clearer picture of what’s in store for one of the fastest-growing sectors of the IT industry.
Big Data Stats – Key Findings
- The big data analytics market for software and services is forecast to be worth $103 billion by 2023.
- There are 2.5 quintillion bytes of data created each day by internet users worldwide.
- By 2023, the big data market in China is estimated to reach a value of more than $22 billion.
- 97.2% of major worldwide organizations are focusing investments into big data and AI.
- Despite great investments, only 15% of organizations claim to have managed to turn their big data analytics into an effective and reliable customer experience.
- In 2012, as much as 88% of customer data was considered irrelevant by companies.
Big Data Market Statistics
The global big data and business analytics market was worth $168.8 billion in 2018.
Big data statistics from 2018 reveal the size of the global big data and analytics market, which is forecast to grow at a compound annual growth rate (CAGR) of 13.2% to a staggering $274.3 billion by 2022. Predictive analytics and data mining that helps produce insights are becoming priceless these days, as companies race to get a hold of massive user patterns that could very well define the future of business.
The big data analytics market for software and services is forecast to be worth $103 billion by 2023.
If you’re wondering how big data translates into money, take a look at the big data analytics statistics ahead. While it’s estimated that the overall cash value of the market will reach $103 billion in the next three years, this figure could double by 2027.
The customer experience management market is estimated to be worth $14.5 billion by 2024.
(Markets and Markets)
The overall big data market includes a variety of sophisticated software programs designed to derive descriptive and inferential statistics on big data. Big data stats from 2019 showed the market to be worth around $7.8 billion. By 2024, this figure is expected to effectively double at a CAGR of 13.3%. The need to improve customer engagement and reduce customer churn rate is on the rise. So is the growth of data that increases day by day.
Big data statistics reveal that insight-driven businesses will by 2021 take as much as $1.8 trillion per year from competitors that have fallen behind.
Data-driven businesses understand the value of counting customers and constantly analyzing their habits and preferences. Companies that use big data effectively and manage to implement it to their advantage are considered to be at the forefront of future success. In fact, according to statistics on big data, such companies are already thriving, reporting an average growth of more than 30% annually.
The big data market is estimated to have grown by 20% in 2019.
Data growth trends over the past seven years have been pointing towards unprecedented growth. According to big data growth statistics, the market in 2019 was expected to grow by 20% compared to 2018. However, if we go further back, we’ll see that in 2012 and 2013 the growth rates were as high 61% and 60% respectively. Although a slowdown is expected in the next few years, big data statistics suggest a 7% increase between 2025 and 2027.
The annual revenue of the global big data market is expected to increase to $49 billion in 2019.
The largest share of this revenue comes from spending on services, which accounted for around 39% of the market in 2019. Forecasts are quite optimistic regarding growth in this field, with data stats suggesting that services will continue dominating the big data market.
In 2018, banking accounted for the single greatest share of global data and analytics revenue at 13.6%.
Apart from banking, other industries that hold a major share of the market when it comes to big data analytics revenue are discrete manufacturing (11.7%), process manufacturing (8.7%), professional services (7.9%), and governments (7.1%). Together with banking, these five industries make up almost half of the global big data revenue.
However, forecasts suggest that a slight change is on the horizon. Deduced from data volume growth, experts estimate that retail will take the biggest share between 2018 and 2022, at a CAGR of 13.5%, with banking landing coming in second at a CAGR of 13.2%.
In 2017, IBM’s revenue from big data and analytics was $2.66 billion.
The computer giant is now the leading vendor when it comes to big data and analytics. The revenue IBM has reaped from the recent information growth rate stems from services, as well as hardware and software, all for the purpose of deriving the most precise predictions and conclusions from big data. Apart from IBM, other major players in the big data game include PwC, Dell, Teradata, HP, SAP, Accenture, Oracle, Deloitte, SAS Institute, and Palantir.
By 2023, the big data market in China is estimated to reach a value of more than $22 billion.
It’s no secret that China is generating great interest in big data analysis. The country has already seen significant growth in the big data sector between 2014 and 2020, and the latest statistics reveal that this shows no signs of stopping. In 2019, the revenue stemming from big data was estimated to be $9.6 billion. At a 23.5% compound annual growth rate, this figure is expected to hit $22.49 billion in the period between 2019 and 2023. With other superpowers boosting their big data market size to incredible proportions, we can expect data stats such as this to become more and more impressive.
How Big is Big Data?
Big data statistics from 2017 determined that 90% of online data in the world had been generated just two years earlier.
The period between 2014 to 2019 saw several important milestones in terms of internet usage. In 2014, there were approximately 3 billion registered internet users, all of whom brought a never-before-seen amount of data online. By 2019, this figure had reached 4.1 billion. With this in mind, it comes as no surprise that there has been an unprecedented and exponential global data increase.
In a 2018 survey, more than 80% of respondents listed data warehouse optimization and forecasting as important issues regarding data in 2018.
The top two issues are followed closely by customer/social analysis and predictive maintenance at 70%. Then there are security issues like fraud detection, as well as clickstream analysis. The least-reported area is IoT, despite the fact it has seen great expansion worldwide in recent times.
There are 2.5 quintillion bytes of data created each day by internet users worldwide.
For the sake of illustration, the daily output of data in bytes is equivalent to the total number of ants on the planet multiplied by 100. Furthermore, with only a quintillion pennies, it would be hypothetically possible to cover the Earth’s surface 1.5 times. If we consider that the amount of data is increasing exponentially over time, we can expect these figures to skyrocket in the near future.
Big data statistics estimate that, given the current course, there will be 40 zettabytes of data clogging the web by 2020.
(Tata Consultancy Services)
How many gigabytes is a zettabyte? Well, zetta is a decimal unit prefix that denotes a factor of 1021, or one sextillion, meaning that this figure represents 40 trillion gigabytes. Although measuring such vast numbers – especially regarding something as abstract as online data – can never be precise, figures such as these give us some perspective on the question: How big is big data today? If we take a look at how data growth projections stand today, compared to 2010 when big data size amounted to 1.2 zettabytes, it’s clear that the exponential growth of data shows no signs of stopping.
According to big data statistics from 2019, a single internet user is expected to generate 1.7 megabytes of data per second within the next year.
If we assume these data stats are correct, by 2020, each person online is on track to create as many as 146,880 gigabytes per day. Given the predictions that by 2025, the internet will total 165 zettabytes worth of data, we can only presume that the individual footprint is set to rise dramatically.
How Do Businesses Perceive Big Data?
Big data statistics show that 97.2% of major worldwide organizations are focusing investments into big data and AI.
A study conducted over 60 Fortune 500 corporate giants concluded that as many as 62% of companies appoint a chief data officer (CDO), whose job is to run data analytics and statistics. The figure dating from 2018 indicates that the number of CDOs in large companies has increased five times since 2012. As for investments, around 60% answered that their big data analytics budget is under $50 million. As for those companies that invest more, 27% confirmed their budget stretches between $50 and $500 million, with another 12.7% of those going beyond $500 million when it comes to big data statistical analysis.
When it comes to primary drivers for investing in big data and AI, 91.7% of CEOs say business transformation and agility are major factors.
In addition, 75% of the executives who took part in the survey agreed that fear of disruption from competitors also serves as a great driving force when it comes to motivation for big data investments. While the majority of high-rolling companies can see the benefits of big data when it comes to cost savings, only 4.8% of respondents consider saving their budget to be a major factor that drives investments.
58.5% of worldwide organizations of all sizes and fields of interest are still in the planning phase of big data technology implementation.
Although huge corporations like Motorola and American Express are conducting cutting edge research in the field of big data statistics, mid-to-low-tier companies are still pedaling back and forth in trying to figure out what their clients want. The big data technology adoption rate remains relatively low. A 2018 survey showed that 30% of global organizations (both commercial and non-profit) were planning to implement uses of statistics in big data management sometime in 2019. Another 12% said they had planned to do so in 2018.
Despite great investments, only 15% of organizations claim to have managed to turn their big data analytics into an effective and reliable customer experience.
(Harvard Business Review)
Big data remains a mystery for businesses. Although everyone is aware of its potential, only a handful manage to get the alchemy right and create a successful practice. According to statistics for big data based on a 700-participant survey, as few as 3% of the respondents reported they were capable of answering their customers’ requirements by using data analytics and statistics. On the other hand, 21% said they make little use of their analysis.
If a single person tried to download all the data from the internet today, it would take them around 3 million years.
Big data volume is so incomprehensible for mere mortals like us that when you translate its actual size into a timeframe, you get this staggering figure. If we could go 3 million years back in the past, instead of going forward into the future, we would end up somewhere in the Pliocene epoch, prior to humans actually existing. It is big data volume statistics such as this one that fully illustrate the size of the corpus with which analysts are dealing.
In 2012, as much as 88% of customer data was considered irrelevant by companies.
This particular set of big data statistics dates back to the early days of research when this topic was yet to be examined closely. The companies that took part in the 2012 survey pinpointed reasons why they were only capable of analyzing around 12% of the available data. Among those reasons they listed issues like a general lack of analytics tools, repressive data silos, and uncertainty in deciding which information was relevant and which wasn’t. At the time, researchers dealing in the field believed that 22% was the maximum potential a company could draw from big data usage.
13% of companies that work in big data volume, velocity, and variety say they take big data security analytics into account.
With big data becoming useful in practically every walk of life, cybersecurity is the one field where its insight could matter most. Threats from cyberattacks are becoming an everyday issue, but with the help of new tools based on big data analytics, they could be prevented before even happening. However, in order for this to become reality, more companies need to funnel their investments and take a more decisive stand towards the development of these tools.
21% of companies consider statistics and big data security analytics to be of great importance for business today.
Although some see the future of cybersecurity aligned with big data and artificial intelligence, not everyone takes these matters seriously. This study based on 330 participants also concluded that as many as 31% of respondents consider the issue to be “not very important.” However, 42% agree that big data security analytics will become an issue of great importance in the future.
It’s estimated that, in 2020, the amount of useful data derived from big data and statistics analysis is set to rise to 37%.
Contrary to what you might think, not all data is actually useful when crunching numbers that are intended to boost sales or improve customer relations. The previous entry showed how less than a quarter of data collected for analysis gets used in helping commercial ventures predict customers’ needs. However, even by today’s estimates we are still only discovering the tip of the iceberg when it comes to using all the data available.
Global healthcare big data statistics show that the analytics sector is set to be worth $68.03 billion by 2024.
Largely driven by investments from North America, the big data sector is thriving in healthcare. Seeing as they handle millions, potentially billions of patient records, hospitals are expected to benefit the most from big data expansion. In the United States and other places, large sums of money are already being poured into electronic health records, practice management tools, and workforce management solutions. This proves that the future of healthcare lies in big data, as it can be used for numerous causes － from registering spikes in certain diseases to combating upcoming epidemics.
Facebook’s big data statistics show 2.3 billion active users, all of whom are responsible for generating huge amounts of data.
Facebook has been setting and breaking its own records for a while now, and with 2.3 billion active users, the social network reigns supreme among its peers. Every 60 seconds, Facebook users generate millions of posts, whether those be photos, comments, or status updates. For example, in 2015, when Facebook had 1.44 billion active users, there were 4.1 million posts created every 60 seconds. This big data generation is, of course, subject to analysis. Since Facebook is the biggest add space on the web, you won’t be surprised to hear that it’s used pretty extensively.
Another great contributor to big data volume is Twitter, with its users posting more than 473,000 tweets per minute.
Facebook isn’t the only social media site generating huge stacks of data from its users; Twitter is also still a heavy-hitter. Big data statistics from 2018 suggest that the number of tweets per minute grew to 473,400, up from an average of 456,000 in 2017. Apart from using big data to constantly run user analysis, Twitter is implementing AI to prevent inappropriate content.
According to every day big data statistics, Americans used an average of 3,138,420 GB of internet data per minute in 2018.
While this statistic is a direct result of big data analysis, it also illustrates how the rise of streaming services has accompanied an increase in data usage. Amazon, YouTube, and Netflix are the biggest users of internet bandwidth on the web. In recent years these services have seen unprecedented penetration rates among the American population. The same source calculated that just one year before, this figure was around 2,657,700 GB of data per minute, which shows a significant increase in data usage over a one-year period.
The big data statistics industry is forecast to open 2.7 million job postings in the US by 2020.
Data statistics and analytics have proven to be a promising new field － one that is set to generate millions of new jobs in the upcoming period. The figure represents a 35% increase compared to 2015 when the last estimate regarding data science job openings was made.
It goes to show how the industry has positioned itself as one of the fastest-growing employers in the United States. However, the US isn’t the only one opening job posts for big data experts. Other industrialized countries across the planet are also investing in the field, with new jobs in sight.
Netflix has more than 100 million subscribers worldwide, and the company is keeping them happy thanks to big data. Excellent customer retention saves Netflix $1 billion a year.
(Inside Big Data)
Netflix has long held the throne as the king of online streaming. With more than 100 million regular subscribers, you’re probably wondering how Netflix uses big data, given that it collects so much. Well, for one thing, this data helps the company direct preferences via a big data recommendation system that influences 80% of the content you are offered. The company has been at the forefront of data statistics, offering high-stakes prizes to contributors willing to improve their algorithms. In fact, as early as 2009, Netflix arranged a $1 million prize to be given to an individual or group that could design the best algorithm for predicting customers’ preferences based on their previous ratings.
Colleges are picking the best and the brightest students by using big data.
About a decade ago, Saint Louis University started slowly implementing big data as part of its recruitment strategy. By using Big Data to compile lists of preferred students, the University has reduced its reliance on services such as the College Board and ACT by 40%. Also, the number of students enrolling in freshman classes has grown significantly. In fact, five of the six largest classes in the history of Saint Louis University have come since the college began using big data in campuses, statistics have shown.