97 Big Data Statistics You Must Learn: 2024 Market Share & Data Analysis

Information is power. But only in so far as the insights they reveal. The 2.5 quintillion bytes of data we create every day is useless unless we crunch it using big data analytics. This is where things get exciting for businesses as we can now predict market behavior with laser-focus accuracy at a personal level. We know data will only get bigger and tech more sophisticated as the months—not years—roll in. You either get up to speed with big data statistics or run the risk of living under a rock.

Here then, is our big data report, comprising the key big data statistics and trends to keep you afloat and relevant in the years ahead, all culled from various big data market research labs all over the world.

State of Industry Statistics
Big Data Cost & Benefits Statistics
Big Data Global Penetration Statistics
Big Data Business Application Statistics
Ethical Implications of Big Data

1. State of Industry Statistics

While the big data market size and market share only indicate numbers by the billions, their total effect on the global economy easily ranges in the trillions. The path to growth is open in all directions, and market forecasts and industry projections easily confirm where big data is heading—spearheaded by its twin, business analytics, and the best business intelligence software applications that it spawns.

This is evident in both pre-pandemic and post-pandemic forecasts. If anything else, the COVID-19 outbreak accelerated the adoption of Big Data technologies. It’s because agility in the business and public policy sphere has been in high demand when it comes to decision making. And, having all the data you need at your fingertips helps a ton.

Pre-Pandemic State of Big Data and Outlook

$189.1 billion – projected worldwide revenues for big data and business analytics (BDA) solutions for 2019. (IDC)
12% – the rate of increase for big data and business analytics use from 2018 to 2019. (IDC)
$274.3 billion – projected worldwide revenues for big data and business analytics (BDA) solutions by 2022. (IDC)
13.2% – projected compound annual growth rate (CAGR) of BDA within the five-year period, 2018-2022. (IDC)
$77 billion – projected big data market size by 2023. (Entrepreneur, 2019)
$103 billion – projected value of the big data analytics market by 2023. (TechJury, 2021)
20% – projected growth rate of the big data market in 2019. (TechJury, 2021)

Pre-Pandemic Drivers of Big Data Growth

Big data exponentially grows with the increasing use of more powerful technologies. This is more so as businesses and institutions pursue competitiveness in all matters digital.

Digital transformation is a key driver of BDA growth. (IDC)
In terms of big data market share, IT services will have the largest category of the BDA market in 2019 ($77.5 billion), followed by hardware purchases ($23.7 billion), and business services ($20.7 billion). Combined, IT and business services will account for more than half of all BDA revenues throughout the forecast and will be among the categories with the fastest growth. (IDC)
In terms of deployment, on-premises solutions will take more than 70% of BDA software revenues in 2019. However, revenue for BDA software delivered via the public cloud will experience remarkable growth over the five-year forecast (32.3% CAGR). This represents more than 44% of the total BDA software opportunity in 2022. (IDC)

Big Data and Top Companies: State of Adoption 2019

59.5% of executives state that they are driving innovation using data. (NewVantage Partners, 2020)
47.6% compete on data and analytics. (NewVantage Partners, 2020)
46.9% state that they manage data as a business asset. (NewVantage Partners, 2020)
31% say that they have created a data-driven organization. (NewVantage Partners, 2020)
28.3% claim that they have forged a data culture. (NewVantage Partners, 2020)

Big Data and Top Companies: State of Adoption 2020

64.2% claim that they use data to drive innovation. This is a 4.7 percentage point increase from the past year. (NewVantage Partners, 2020)
45.1% claim that they are competitive on data and analytics. This is a 2.5 percentage point drop from the previous year. (NewVantage Partners, 2020)
50% state that they manage data as a business asset. This is a 3.1 percentage points increase from 2019. (NewVantage Partners, 2020)
37.8% managed to create a data-driven organization. This is a 6.8 percentage points increase from 2019. (NewVantage Partners, 2020)
26.8% claim that they have forged a data culture; a 1.5 percentage points drop from last year. (NewVantage Partners, 2020)

2. Big Data Cost & Benefits Statistics

Cutting-edge customer service software can already work through massive amounts of data to profile customer needs and behavior. This helps agents engage with customers better and add more value to the overall customer experience. CRM solutions deal with its own data sets to improve the profiles of both leads and customers. The leading marketing software can gather crucial information about leads and customers, allowing marketers to increase their sales leads and conversion. These and other examples show how big data address business challenges from multiple fronts.

Principles for AI/Big Data Investments in 2020

53% cite transformation as the main driver for AI/Big Data investments. (NewVantage Partners, 2020)
26.8% cite innovation as their main driver for investments. (NewVantage Partners, 2020)
Other drivers for investment include competition (8.5%), cost-savings (6.1%), and regulation (4.9%). (NewVantage Partners, 2020)

Benefits of Big Data

Using big data, Netflix saves $1 billion per year on customer retention. (TechJury, 2021)
$1 trillion – the amount businesses will save from IoT by 2020. (Grazitti Interactive)
$40 billion – the projected financial impact of AI by 2025. (Informa)
8–10% – profit increase for businesses that use big data. (Entrepreneur, 2019)
Data wrapped in stories are 22x more memorable than bare facts. (Chicago Analytics Group)
70% of businesses believe that data warehouse optimization is critical to their success. (Forbes)
Data analytics top 4 benefits: 25% faster innovation cycles; 17% improved business efficiencies/higher productivity; 13% more effective R&D; and 12% product/service. (Chicago Analytics Group)

The Cost of Big Data

$3.1 trillion a year – the cost of poor data quality to the US economy. (IBM)
91% of companies feel poor data wastes revenue. (Chicago Analytics Group)
79% of enterprise executives say that not embracing big data will cause them to risk competitive position and face extinction. (Forbes)
83% of enterprise executives are pursuing big data projects to gain a competitive advantage. (Forbes)
10% – reduction in overall cost for businesses that use big data. (Entrepreneur, 2019)

Source: NewVantage Partners, 2020

3. Big Data Global Penetration Statistics

Nothing keeps big data statistics analysis churning in any part of the world like social media and mobile devices. With these, billions of users and thousands of businesses interact daily to produce a staggering amount of data. Only the best-designed data mining and business intelligence could hope to process these. Add to that the myriad social media management tools diving into the data pool and you see data is truly fueling businesses, now and for years to come.

Every day, we produce 2,500,000,000,000,000 bytes of data. That’s 2.5 quintillion or 2.5×1018 bytes of data (2.3 trillion gigabytes). (IBM)
40 zettabytes (43 trillion gigabytes) of data will be created by 2020, up 300% from 2015. (IBM)
90% of the total amount of all data ever made on Earth was produced by humans in the last two years alone. (Forbes)
1.7 megabytes – new information created every second by every human being. (Grazitti Interactive)
6 hours and 42 minutes is the average number of hours per day users spend on the internet. (TNW)
1.2 billion years – number of years humanity will collectively spend online in 2019. (TNW)
44 zettabytes (44 trillion gigabytes) – the volume of global IT traffic projected by 2020. (Grazitti Interactive)
50 billion – number of smart connected devices in the world by 2020, collecting, analyzing, and sharing data. (CISCO)

The Dead Figures in Big Data

How does big data figure in big data accounting? Many die while their social accounts remain active. Multiply that by the years ahead, and you get the picture. Of course, that does not take away from how many of the current world population make it into the big data numbers.

181 million – number of years it would take an individual to download all the data from the internet. (IOP)
50 years from now – when the dead may outnumber the living on Facebook. (Phys.org)
7.697 billion global population (urbanization 56%). (We Are Social, 2019)
5.110 billion unique mobile users (66% penetration). (We Are Social, 2019)
4.437 billion Internet users (58% penetration). (We Are Social, 2019)
3.499 active social media users (45% penetration). (We Are Social, 2019)
3.429 mobile social media users (45% penetration). (We Are Social, 2019)

4. Big Data Business Application Statistics

US companies are storing big data at a mind-boggling rate. However, data is almost evenly split between structured and unstructured/semi-structured data. That means there is a lot of work ahead for vendors and their clients to fully maximize big data. And they may be falling behind the race as we see even faster big data traction. These are all thanks to technologies like cloud computing, augmented reality (AR) and artificial intelligence (AI).

100 terabytes – volume of data stored by most US companies. For perspective, a year of it is enough to fill ten thousand Libraries of Congress. (IBM)
1 terabyte of trade information – average volume of data captured by the New York Stock Exchange each trading session. (IBM)
45% – the percentage of companies that run big data workloads in the cloud. (ZDNet, 2019)
100 sensors – average number of sensors used by modern cars to monitor items such as fuel level and tire pressure. (IBM)
51% of data is structured, 27% of data is unstructured, and 21% of data is semi-structured. (TCS)

How big data will look for companies and employees

30% of web browsing will be done without a screen by 2020. (Grazitti Interactive)
220 million – number of connected cars by 2020. (Grazitti Interactive)
100 million consumers will shop via AR by 2020. (Grazitti Interactive)
1 billion – number of global workers whose behavior will be altered by algorithms. (Grazitti Interactive)
40% of employees can cut their healthcare costs by wearing fitness trackers. (Grazitti Interactive)
$9 billion – data investments in the financial services industry in 2018 alone. (Research and Markets)
97.2% of organizations are investing in big data and AI. (TechJury, 2021)
By 2020, the customer will manage 85% of relationships with an enterprise without interacting with a human. (Chicago Analytics Group)
By 2020, self-service spending on data tools will grow 2.5x higher than traditional data tools spending. (Chicago Analytics Group)
In 2019, there are 2.3 billion active Facebook users, and they generate a lot of data. (TechJury, 2021)

Top Industries Served by Big Data and Analytics

32% – Media, Advertising, and Entertainment (Insights Association, 2020)
31.4% – Healthcare Products, Services, OTC Medicines (Insights Association, 2020)
12.1% – Consumer Durables, Non-Durables (Insights Association, 2020)
10.2% – Government, Associations, Non-Profits, Public Service (Insights Association, 2020)
5% – Technology (Insights Association, 2020)
4% – Financial Services and Insurance. (Insights Association, 2020)
3% – Telecommunications. (Insights Association, 2020)
2.5% – Consulting (Insights Association, 2020)
1.9% – Automotive (Insights Association, 2020)
1.7% – Retailers/Wholesalers (Insights Association, 2020)
1.2% – Education (Insights Association, 2020)
The following have less than 1%: restaurants, utilities, hospitality and tourism, agricultural, and political/legal. (Insights Association, 2020)

Top Big Data and Analytics Services by Revenue

23.2% – Audience Measurement (Insights Association, 2020)
18.4% – Data, Text, and Predictive Analytics (Insights Association, 2020)
13% – Information Technology (Insights Association, 2020)
9.8% – Custom Research (Insights Association, 2020)
7.1% – Syndicated Research (Insights Association, 2020)

Companies still need to address big data challenges

88% of data is ignored (Big Data Made Simple)
Most companies only analyze 12% of their data. (Big Data Made Simple)
40% of businesses say they need to manage unstructured data frequently. (Forbes)
95% of businesses need to manage unstructured data. (Forbes, 2019)
27% of people are uncertain about the accuracy of their data. (IBM)
80% of leaders measure the impact of data analytics investments. (iView Systems)
60% of leaders have predictive analytics capabilities. (iView Systems)
85% of leaders have some form of shared analytics resources. (iView Systems)
99% of organizations think data is essential to marketing success. (Chicago Analytics Group)
Leaders are 166% more likely to make most decisions based on data. (iView Systems)
75% of leaders cite growth as the key source of value from data analytics. (Chicago Analytics Group)
Leaders are 2.2x more likely to have a formal career path involving analytics. (iView Systems)

Source: Insights Association, 2020

5. Ethical Implications of Big Data

Big data offers vast potential for organizations to analyze and leverage information, but it also raises significant ethical concerns that must be addressed. Some of the key ethical implications of big data include:

Privacy Concerns: One of the biggest ethical issues is collecting and using personal data. Vast information gathered from social media, transactions, and online activity can compromise individuals’ privacy. Companies must ensure they are transparent about what data they collect and how it is used. They must also seek consent from users whenever necessary.
Data Ownership: As data becomes more valuable, questions about ownership arise. Who owns the data collected about individuals? Is it the individual, the company, or a third party? Ethical questions emerge regarding who controls the data and how it can be used, especially when individuals are unaware of how their data is accessed or shared.
Bias in Data: Big data systems can perpetuate or even amplify biases if the data they are trained on reflects historical inequalities or biases. For example, biased data used in hiring algorithms can lead to discriminatory hiring practices. Organizations must regularly audit their data and algorithms to avoid bias in decision-making processes.
Security of Data: The storage and handling of big data raise concerns about data security. Companies must implement strong security protocols to prevent data breaches, which could expose sensitive personal or financial information. Ensuring that data is protected from cyberattacks is essential for maintaining public trust.
Informed Consent: Users often do not fully understand the extent of the data they provide or how it will be used. Organizations need to ensure that they obtain informed consent from users by explaining the risks and benefits of data collection clearly and understandably.
Impact on Employment: The increasing reliance on big data and automation can lead to job displacement as certain roles become automated or outsourced. While big data can improve business efficiencies, it can also create ethical dilemmas related to employment practices and economic inequality.

Let big data work for you

Big data brings a long list of statistics, as this article clearly shows. If your business works with massive volumes of data, a compilation like this sets you in the right direction to steer your business for many years ahead. Hidden in the vast array of data lying in your databases is information that you could use to your advantage.

It could be about discovering a new line of products or services with a ready market that no one has even heard of. It could be about a new way of doing things, and you just need to gather the right people to see it implemented in your organization.

No matter what it is, it simply reinforces the need for vigilance when it comes to thinking about how data could alter the course of your business. With the right business and productivity tools, you put yourself in the right place and the right time to get ahead of the pack.

Key Insights

Exponential Growth: The big data market is experiencing rapid growth, with projected revenues of $274.3 billion by 2022, and a compound annual growth rate (CAGR) of 13.2% from 2018 to 2022.
Pandemic Acceleration: The COVID-19 pandemic has accelerated the adoption of big data technologies, highlighting the need for agility in decision-making in both business and public policy.
Industry Adoption: A significant percentage of companies are utilizing big data to drive innovation (64.2%), manage data as a business asset (50%), and create data-driven organizations (37.8%).
Cost Savings and Efficiency: Businesses using big data can increase profits by 8-10% and reduce overall costs by 10%. For instance, Netflix saves $1 billion per year on customer retention using big data.
Data Quality Concerns: Poor data quality costs the US economy $3.1 trillion annually, with 91% of companies acknowledging revenue losses due to poor data.
Widespread Data Generation: Daily global data production is staggering, with 2.5 quintillion bytes created every day. By 2020, 40 zettabytes of data were projected to be created.
Sector Impact: The media, advertising, and entertainment sectors are the top industries utilizing big data, followed by healthcare, consumer durables, and government/public service.
Cloud Adoption: 45% of companies run big data workloads in the cloud, emphasizing the importance of scalable and flexible data management solutions.
Advanced Analytics and AI: Nearly all organizations (97.2%) are investing in big data and AI to gain a competitive edge, highlighting the importance of advanced analytics capabilities.

FAQ

What is the projected revenue for the big data and business analytics market by 2022?
The projected worldwide revenue for big data and business analytics (BDA) solutions by 2022 is $274.3 billion.
How has the COVID-19 pandemic impacted the adoption of big data technologies?
The COVID-19 pandemic has accelerated the adoption of big data technologies, as agility in decision-making has become critical in both business and public policy spheres.
What percentage of companies are using big data to drive innovation?
According to a survey, 64.2% of companies are using data to drive innovation.
How much can businesses save annually by using big data for customer retention?
Businesses like Netflix can save $1 billion per year on customer retention by using big data.
What are the main drivers for AI and big data investments?
The main drivers for AI and big data investments are transformation (53%), innovation (26.8%), competition (8.5%), cost savings (6.1%), and regulation (4.9%).
What is the estimated cost of poor data quality to the US economy annually?
Poor data quality costs the US economy an estimated $3.1 trillion annually.
How much data do humans create daily?
Humans create approximately 2.5 quintillion bytes of data every day.
What industries are the top users of big data and analytics?
The top industries using big data and analytics are media, advertising, and entertainment (32%), healthcare (31.4%), and consumer durables (12.1%).
What percentage of companies run big data workloads in the cloud?
Approximately 45% of companies run big data workloads in the cloud.
Why are companies investing in advanced analytics and AI?
Companies are investing in advanced analytics and AI to gain a competitive advantage, improve efficiency, and drive innovation, with 97.2% of organizations pursuing such projects.

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By Allan Jay

Allan Jay is FinancesOnline’s resident B2B expert with over a decade of experience in the SaaS space. He has worked with vendors primarily as a consultant in the UX analysis and design stages, lending to his reviews a strong user-centric angle. A management professional by training, he adds the business perspective to software development. He likes validating a product against workflows and business goals, two metrics, he believes, by which software is ultimately measured.