ecurity issue<\/a>s 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.<\/p>\n\n\n\nThere are 2.5 quintillion bytes of data created each day by internet users worldwide.<\/h4>\n\n\n\n
(Domo)<\/p>\n\n\n\n
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\u2019s 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.<\/p>\n\n\n\n
Big data statistics estimate that, given the current course, there will be 40 zettabytes of data clogging the web by 2020.<\/h4>\n\n\n\n
(Tata Consultancy Services)<\/p>\n\n\n\n
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\u2019s clear that the exponential growth of data shows no signs of stopping.<\/p>\n\n\n\n
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.<\/h4>\n\n\n\n
(Domo)<\/p>\n\n\n\n
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.<\/p>\n\n\n\n
How Do Businesses Perceive Big Data?<\/h3>\n\n\n\nBig data statistics show that 97.2% of major worldwide organizations are focusing investments into big data and AI.<\/h4>\n\n\n\n
(NewVantage)<\/p>\n\n\n\n
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.<\/p>\n\n\n\n
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.<\/h4>\n\n\n\n
(NewVantage)<\/p>\n\n\n\n
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.<\/p>\n\n\n\n
58.5% of worldwide organizations of all sizes and fields of interest are still in the planning phase of big data technology implementation.<\/h4>\n\n\n\n
(NewVantage)<\/p>\n\n\n\n
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.<\/p>\n\n\n\n
Despite great investments, only 15% of organizations claim to have managed to turn their big data analytics into an effective and reliable customer experience.<\/h4>\n\n\n\n
(Harvard Business Review)<\/p>\n\n\n\n
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\u2019 requirements by using data analytics and statistics. On the other hand, 21% said they make little use of their analysis.<\/p>\n\n\n\n
If a single person tried to download all the data from the internet today, it would take them around 3 million years.<\/h4>\n\n\n\n
(physics.org)<\/p>\n\n\n\n
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.<\/p>\n\n\n\n
In 2012, as much as 88% of customer data was considered irrelevant by companies.<\/h4>\n\n\n\n
(Forrester)<\/p>\n\n\n\n
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\u2019t. At the time, researchers dealing in the field believed that 22% was the maximum potential a company could draw from big data usage.<\/p>\n\n\n\n
13% of companies that work in big data volume, velocity, and variety say they take big data security analytics into account.<\/h4>\n\n\n\n
(BI-Survey)<\/p>\n\n\n\n
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.<\/p>\n\n\n\n
21% of companies consider statistics and big data security analytics to be of great importance for business today.<\/h4>\n\n\n\n
(BI-Survey)<\/p>\n\n\n\n
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 \u201cnot very important.\u201d However, 42% agree that big data security analytics will become an issue of great importance in the future.<\/p>\n\n\n\n
It\u2019s estimated that, in 2020, the amount of useful data derived from big data and statistics analysis is set to rise to 37%.<\/h4>\n\n\n\n
(Forrester)<\/p>\n\n\n\n
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\u2019 needs. However, even by today\u2019s estimates we are still only discovering the tip of the iceberg when it comes to using all the data available.<\/p>\n\n\n\n
Global healthcare big data statistics show that the analytics sector is set to be worth $68.03 billion by 2024.<\/h4>\n\n\n\n
(Healthcare Weekly)<\/p>\n\n\n\n
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 \uff0d from registering spikes in certain diseases to combating upcoming epidemics.<\/p>\n\n\n\n
Facebook\u2019s big data statistics show 2.3 billion active users, all of whom are responsible for generating huge amounts of data.<\/h4>\n\n\n\n
(Domo)<\/p>\n\n\n\n
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\u2019t be surprised to hear that it\u2019s used pretty extensively.<\/p>\n\n\n\n
Another great contributor to big data volume is Twitter, with its users posting more than 473,000 tweets per minute.<\/h4>\n\n\n\n
(Domo)<\/p>\n\n\n\n
Facebook isn\u2019t 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.<\/p>\n\n\n\n
According to every day big data statistics, Americans used an average of 3,138,420 GB of internet data per minute in 2018.<\/h4>\n\n\n\n
(Domo)<\/p>\n\n\n\n
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.<\/p>\n\n\n\n
The big data statistics industry is forecast to open 2.7 million job postings in the US by 2020.<\/h4>\n\n\n\n
(PwC)<\/p>\n\n\n\n
Data statistics and analytics have proven to be a promising new field \uff0d 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.<\/p>\n\n\n\n
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\u2019t 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.<\/p>\n\n\n\n
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.<\/h4>\n\n\n\n
(Inside Big Data)<\/p>\n\n\n\n
Netflix has long held the throne as the king of online streaming. With more than 100 million regular subscribers, you\u2019re 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\u2019 preferences based on their previous ratings.<\/p>\n\n\n\n
Colleges are picking the best and the brightest students by using big data.<\/h4>\n\n\n\n
(The Atlantic)<\/p>\n\n\n\n
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.<\/p>\n","protected":false},"excerpt":{"rendered":"
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