All the devices, sensors, and electronic gadgets connected to the internet create an increasing amount of data daily. The amount of data and the frequency at which it is produced is overwhelming. This blog discusses the top 25 data science stats and facts to help you understand how much data we produce, the constituents of data, challenges, trends, and the future predictions for data science and data scientists.
Data science was a term minted back in 1960, highlighting a professional skill set necessary to understand and interpret a large amount of generated data. Since then, using computer science and statistical methodology, Data science has evolved as an expert profession for extracting insights from the data.
When choosing right or wrong, confusion always holds us back. However, due to this confusion, we lose the most valuable asset – Time. Data science helps us save time, overcome confusion, and put the right foot forward confidently. The data science stats in 2022 will reinforce the truth that “Data science isn’t the end; it’s the beginning of a new era.”
Statistics and statistical and mathematical models are the early roots of data science. With the technological evolution in the twenty-first century, data science also evolved to include advanced technologies such as artificial intelligence, machine learning, the Internet of Things, and more.
We believe data science and its applications will continue to grow in the coming years as big data will become even bigger. For example, 95 percent of the US population own a smartphone, about eight adults out of ten own a laptop or desktop, half of them own a tablet, and around one in five readers own an e-reader device. Besides, 78% of healthcare consumers use wearable gadgets to track their lifestyle and vital signs.
The amplification in the number of mobile users, increasing internet penetration rate, and the availability of numerous eCommerce apps at the fingertips generate a huge amount of data daily. Data science is a field responsible for collecting, processing, modeling, and analyzing data to gain deeper insight into the data. Businesses seek data science to increase business profits, make better decisions, and achieve growth.
Since data science plays a vital role in the modern business ecosystem, let’s examine the top 25 data science stats to determine its importance and effectiveness,
1. According to Statista, in the past year (2021), the estimated volume of data/information created, consumed, captured, and copied worldwide was about 79 Zettabytes.
COVID-19 Pandemic was responsible for the growth in data generation as more people worked and students learned from home. Besides, families consumed a larger amount of data for entertainment.
2. Domo estimated that every person on earth contributed to creating around 2.5 quintillion bytes of data per day in 2020.
3. In the same report, DOMO states that every human was responsible for creating about 1.7 MB of data per second in 2020.
It does not matter whether you are watching Netflix, YouTube, surfing the web, sharing images, posting tweets, or sending emails; you create an abundance of valuable information with every click, swipe, share, and like. These data science stats comprise every single byte of data created by each individual.
4. The research report shared by Statista states that as of April 2022, around 5 billion people are using the internet today. It is equivalent to 63% of the total world population.
From April 2020 to April 2022, about 200 million people got added to the world’s connected population. The population of internet users grew at an annual rate of 4%, and if we consider this a benchmark, then in the coming year, two-thirds of the world population will be connected to the internet.
5. The Digital 2022 Global Overview Report suggests that 6.58 hours is people’s average time on the internet across all devices.
The same report suggests that the world will spend more than 12½ trillion hours online in 2022 alone. However, there are considerable differences when we consider geography.
6. According to a DM News report, about 70% of the world’s data is user-generated if we consider all the globally existing data.
User-generated content includes all forms of content like images, videos, reels, text, audio, etc. Anything posted by a user online or on social media, including online reviews, websites, forums, and bogs, comes under the UGC category. These data science stats give us a fair idea of the amount of data generated globally and how much less prepared we are to process this data.
7. Referring to one of the articles published on CIO, about 80-90% of the data present in the global digital universe is unstructured.
Since COVID Pandemic, countless organizations have embarked on their data science journey. Many have started to realize the importance of having a data-driven approach to running the business. However, success is uncertain, even with a great plan, positive intentions, and willingness to make an effort.
Here are some data science statistics that will help us understand specific roadblocks and tangible issues creating challenges to adopting a data science approach.
8. According to a study report published by Columbia Business School’s BRITE conference, 39% of marketers agreed that their data is often inappropriate and too infrequent for real-time decision-making.
9. In a joint report published by Informatica and Capgemini on the keys to operationalizing Big Data projects, IT budget restraints are a top challenge for 50% of United States executives and 42% of European executives and 42% of European executives in exercising the data science approach.
It is sad but true! Even though we are in the middle of the ongoing technology revolution, many organizations still face barriers and challenges typical of any major enterprise technology initiative, such as budget constraints, data security concerns, and integration issues.
10. In one of the surveys conducted by Dell, 43% of Business decision-makers feel their IT infrastructure is unable to handle future data demands.
For example, suppose humans and machines generate about 175 zettabytes of data over the next five years. In that case, the existing IT infrastructure cannot handle this huge amount of data influx at speed.
11. According to PragmaticWorks, global organizations incur 20-35% losses in operating revenue due to poor data quality.
12. IBM published the research findings in its annual report in 2020; it estimates that the American economy is losing $3.1 Trillion every year due to bad data quality.
13. According to data science stats mentioned by the MIT technology review, we are processing only 0.5% of the available data. The percentage is shrinking as we are racing to collect more and more data.
Data science has immense potential; already, we are using it for drug discovery, predicting diseases, decoding DNA, and similar complicated tasks that were not possible before. The best thing to carry on your data science journey is a set of questions. Unless you have questions, data is of no value.
14. As per the survey report published by Sigma, 63% of companies cannot gather insights from the organizational data.
The data science facts mentioned in the report suggest that many executives believe it will take time for their businesses to be driven by data insights. Many companies are aware of the terms and benefits of data science. Still, they lack IT infrastructure and necessary talent and are still working on data silos to make data work in their favor.
15. According to data science statistics, even though big data and data science are the buzzwords now, 60% of companies still feel it’s hard to find skilled data scientists due to a severe talent shortage.
Let us understand this with an example; out of every million jobs posted online, a thousand are job postings, but there are only 600 data scientist job searches per million. Besides, only 500 people apply to those 1000 job postings, only 300 are selected, and 200 are rejected due to skill set issues. In any scenario, the bargaining power still rests with the applicant. Therefore, this situation might still create a talent shortage for many companies.
16. According to the Statista Research Department, about 68% of global travel brands heavily invested in business intelligence and predictive analytics capabilities in 2019.
The travel and hospitality industry took a severe hit during the COVID pandemic. After learning lessons from the past, traveling brands and the hotel industry are aggressively becoming more innovative and tech-savvy to attract, gain, retain, and satisfy customers. The emerging data science stats are enough to establish its importance in helping the travel and hospitality industry analyze demand and customer behavioral patterns and effectively handle the customer base.
17. As per the facts presented by the BCG-WEF project report, 72% of Manufacturing companies rely on advanced data analytics to enhance their productivity.
The manufacturing industry is another important industrial sector badly impacted due to COVID. The post-COVID data science stats in the manufacturing industry show an upward trend in using data science applications in various business functions like product launches, engineering, logistics, maintenance, and health and safety.
18. The Hechinger Report is known to cover innovation and inequality in education; according to one of its reports – about 1400 worldwide colleges and universities depend on predictive analytics to curate low graduation rates, reshape college experience, and help students to a narrow, data-driven path to graduation, with fewer dead ends and wrong turns.
19. Considering the predictions done by CrowdFlower in its Data Scientist Report – 91% of the data used in Data Science comprises text data. The same report also mentions that unstructured data comprises 33% images, 11% audio, 15% video, and 20% other data apart from the text.
20. The McKinsey survey on data monetization gives us some interesting facts – about 47% of survey respondents stated that data science has helped them get a competitive advantage as data analytics has reshaped the competition in their sector.
The data science stats in 2022 are enough to portray how the competitive landscape has changed in the last few years. Yet, the good thing is many businesses reacted positively to the change by adopting data science and a data-driven approach. However, many industries respond relatively slowly to these transformations, which might create a gap between them and the industry leaders leveraging data science.
21. The data science stats in one of the Statista reports that by the end of 2025 more than 75 billion Internet of Things (IoT) connected devices in use. The forecast predicts it will mark nearly a three-fold increase in IoT devices compared to 2019.
Cars, smart home devices, and connected industrial equipment are some of the IoT-connected devices that will make an impact compared to non-IoT devices like smartphones, laptops, and computers. With all these devices, the number of IoT-connected devices will jump to 10 billion. Besides, the 5G network’s rollout will be crucial in accelerating IoT deployment units by 2025, resulting in increased revenue and data generation.
22. According to a growth forecast study report by Markets & Markets, the market size of data science platforms is expected to reach 322.9 USD billion in 2026, which was USD 95.3 billion in 2021. The market size is projected to grow at a 27.7% CAGR.
23. The data science stats in 2022 estimate that 149 zettabytes of data will be copied, captured, and curated by 2024. It is huge compared to the two zettabytes we created back in 2010.
Global data is growing exponentially, and there is no sign of slowing down. The additional data that the increasing influx of IoT devices is supposed to generate will be another cause of concern. Big data will fuel the world in the coming years, and you need data science to harness complex data and process it to get actionable insights. Therefore, global organizations must stay prepared as data science will be the new frontier for innovation, automation, competition, and productivity.
24. According to PayScale, data science will be the next dream job as the estimated salary of a data scientist is predicted to reach $65k to $153k/year.
25. Recently the United States Data Science Institute published a report from the US Bureau of Labor Statistics that predicts by 2026, 11.5 million jobs will be created for data scientists.
Data science and quantum computing have a bright future and are expected to last longer decades. These data science stats make it clear that many businesses have started investing in data science and are sharpening their data-driven decision-making skills. The increasing adoption of data science will create a huge demand for data scientists trained and skilled at handling huge amounts of data and deriving sense from it. The Dice 2020 Tech job report shows that the demand for data science skills has grown by 50%.
Until 2010 we were worried about the growing amount of data, then we witnessed the era of big data that resulted in the development of frameworks and data storage solutions. Now it’s time to focus on data processing.
These data science stats have shown the importance of processing either a small amount of structured data or large chunks of unstructured and semi-structured data collected from multiple sources. The BI tools and technologies available in the market are inadequate when you want to analyze an exponential amount of data. The statistical and mathematical models, machine learning and artificial intelligence technologies, and more complex tools used in data science have set the future narrative for dealing with and processing whatever amount of data we generate in the future.
Data scientists with highly specific, highly specialized skill sets will be in demand. Yet, the shortage in the data science talent pool bothers many. If you have the same worry, hire the best data scientists from us who offer high-quality data science consulting services to all shapes and sizes of businesses.
Natural Language Processing, or NLP, is taking a front seat as businesses discover new ways and valuable data science applications developed using artificial technology. It is believed that in the coming years, NLP will grow in stature, usage, use cases, and data science applications.
Innovation in IoT technology will become necessary, and together with data science, it is predicted that it will play a pivotal role in realizing predictable, repeatable, and measurable outcomes.
AI-driven assistance will see an upward growth. There is a high possibility that it will replace the current dashboards and eliminate the existing ‘Swivel Chair’ interface.
Many such predictions hint toward the growth and maturity of data science platforms and associated technologies in the future.
Data science is still in its infancy and has a bright future that will last for long decades. Evolving technology and the generation of huge data are the two major reasons for the increasing demand for data science. Everything from the inability of organizations to handle large amounts of data, revising data regulation policies, and astonishing growth in data creating and handling will result in a better and long-lasting future for data science.
Data science has become an inherent part of every enterprise, and the upcoming trends in data science will boost its importance in every industry.
Some of the data science trends that are supposed to change the dynamics are offering data-as-a-service, use of augmented analytics, edge intelligence, hyper-automation, Internet of Things, automated data cleaning, the dominance of NLP, quantum computing for faster analytics, Automation of Machine Learning (AutoML), and democratizing AI and data science.
Until now, you might have understood that data science is here to stay. It has helped organizations grow beyond the conventional norms of data consolidation. Therefore until there is data science, there will be a need for data scientists. You need highly specialized knowledge and skills to become a data scientist. As of now, there’s a need right now for more than 150,000 data scientists alone in the US. Besides, there is also a global shortage of data science skills in Europe and Asia. Since 2011 94% of professionals who graduated in data science are expert data scientists today. Therefore, you can be very comfortable and confident if you choose data science as a career.
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