Top Facts about Data Science You Must Know

Top Facts About Data Science That Everyone Should Know About

The exponential growth of internet usage and high-speed technological improvements in device connectivity are managing the transfer of data at an exponential rate, forcing organizations to come up with new ways to flow the data influx into the insights of business that help them make better, more informed decisions. Here we gather up top facts regarding the importance of data science today and in the future.

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Most people are aware of how companies like eBay, Netflix, YouTube, and Amazon enhance the experience of users by making recommendations based on personal needs for what to purchase or watch. Such tasks would be very hard to complete without the use of data derived from users’ search histories.

Data science came to popularity around the year 2008 and has since gained traction to become a dominant trend in the IT sector. Data science’s popularity and acceptance have grown over time as a result of its ability to help businesses of all sizes identify patterns in data, allowing them to explore new markets, manage costs, improve operational efficiency, and gain a competitive advantage.

What Really Is Data Science?

Data science uses mathematical techniques, techniques, and algorithms to draw knowledge and business intelligence from both organized and unstructured data as interdisciplinary fields of large data and machine learning. The workflow in data science includes a range of dynamic processes such as data collection, data storage, data purification, data analysis, data staging, data clustering, data modeling, and summarization. Upon obtaining observations, data scientists carry out exploratory research, regression, text mining, statistical analysis, and qualitative analysis. Finally, data visualization lets managers take smart strategic decisions and share insight.

Deeds About Data Science in Terms of Data Sources

The three main classes in which data scientists categorize data are unstructured, semi-organized, and structured. Un-structured data are non-organization, semi-structured, but not standardized data, whereas structured data are well-organized data. Regardless of the classification of data, data scientists must assure that machines comprehend the data used.

Below, you can find some interesting facts about data science in data sources;

Text data consists of 91% of the data that are used in data science
41% of the data in the data science pipeline is contributed by public data
Internal systems create about 78% of the input data used in data science
15% of the data is video, 33% of the data is images, and 11% of the data is audio

Data Science Advantages

Data science helps organizations, which facilitate better strategic choices and offer superior results while minimizing risk, to track data patterns and changes in data. Below you can find some interesting facts on data science advantages;

Just a 10% rise in data usability will result in net increased revenues of 65 million dollars for Fortune 1000.
47% of businesses feel that data analysis has substantially or substantively changed their markets
73% of corporations spend about 20% of the overall infrastructure budget
Retail companies have obtained a comparative edge from data analytics, almost 62% of them.
In order to provide useful market insights, the effective management of unstructured data is a high priority for 40 percent of companies
70% of the online data are produced by individuals and 80% are saved, handled, and analyzed by companies.
Facebook’s Open Graph API adds 1 billion content bits a day.
By 2025 embedded devices will be in use for over 75 billion IoT, an improvement of 3 times in 2019 compared to those that are IoT-enabled.
The loss organizations incur from low data quality is 15 million dollars every year

Popular Programming Languages

Emerging areas of technology such as artificial intelligence, computer education, and data sciences need rigorous algorithms for smart models to run. One must have a thorough understanding of how algorithms function in programming languages. The programming languages for data science activities are diverse. The most prominent data science programming languages are as follows:

75 percent of data scientists claim they often or commonly use the open-source Python programming language for data science-related activities, according to a survey released by tech company Anaconda. The data science environment is dominated by Python and the development is predicted to begin in 2021. Below, there are some facts for other programming languages;

A global survey by Google LLC’s affiliate, Kaggle, shows that 36% of scientists prefer the R programming language for data science
In data scientists, 15% use Java Script, 10% are Java-based, 9% use C/C++, and 4% use C#

Data Science Facts About Job Opportunities and Salary in 2021

Website for corporate research for four consecutive years Glassdoor has been naming the “data scientist” as the number one work in the US. On the other hand, the Office of Labor Statistics estimates that employment prospects will rise by 27.9 percent by 2026 because of the increased need for data science expertise. Some interesting statistics on jobs and compensation are presented below;

According to a CrowdFlower poll, 50% of researchers said they “refreshed” their work and 90% said they were satisfied with what they were doing.
The CrowdFlower survey shows that companies are contacting 30 percent of data scientists several times a week for new jobs, with 50% once a week, and with 90 percent once a month.
Although 80% of data scientists spend time researching, arranging, and cleaning data, just 20% analyze the data, according to an IBM survey.
A computer technology engineer’s income is between 65 and 153 billion dollars per year, respectively.
An analysis of the study predicts that 3,037,809 new openings will be created by the end of 2021 by data science
More than 60% of businesses feel that it is not easy with extreme talent shortages to perform the task of data scientists.

Senior employment committees such as Dice.com, LinkedIn, and Glassdoor have released numerous studies on the prospective development of a data science career, as well as the market in recent years for trained data scientists. In this emerging field, there is however a large skill deficit of 58% worldwide. This lack of talent provides a great potential for people with non-IT backgrounds, as well as clinicians.

Bottom Line

Data science gained a lot of popularity over the last few years. It becomes a good career path for professionals. If you like spending hours on problem-solving you can think of data science as a career option. Here we discuss top facts about data science. Let me know in the comments section if you want to add something.