Uncover the Facts about Data Science
The term Data science was fundamentally introduced in 1974 by Peter Naur. Predominately, data science can be interpret as study of data. Later, this data can be altered in a way that it generates meaningful consequential inputs, which helps to produce better business strategies. To get desirable reports from data, the well-extracted data goes through a few steps. Starting from data extraction, data wrangling, data exploration, the process is followed by data modeling and report.
After attaining relevant data from database management, before you start doing next step it’s extremely important to put data in an understandable order in order to analyze it. Subsequently, data modeling is also known as machine learning which takes commands and brings forward solutions on its own.
How Much Data Is Created and Used Everyday
Ever wondered how much data is created every day? According to research almost 2.5 quintillion bytes data is created every single day. Roughly, every user creates 1.7 MB per second. However 1GB can create 350,000 emails. As claimed by the world is expecting to generate 200+ zettabytes data and will be uploaded in cloud storage around the globe. Moving onto how much do we use so it’s quite difficult to calculate and give exact numbers on how much data do we use per day.
Data and Business Analytics Revenue Worldwide
Back in 2018, the global big data and business market (BDA) was valued at 168.8 billion U.S dollars and it was forecasted that it would grew up to 215.7 billion U.S dollars. IT services were expected to make around 85 million dollars approximately and expected to rapidly grow 10 time more rapidly in terms of of its ROIs by 2022.
The US Leads the Data Scientist Market
US data science markets are creating humongous opportunities for data scientist. Global online program for data science market is forecasted to hit 356.27 million by 2026. In US Data is largely consumer driven and consumer oriented. With every click and swipe, unique data is generated and goes into database. The same data is used for driving huge marketing campaigns using AI. And this is because everyone now has phones in their hands and they are always on the go for exploring more. The mobile phone usage is also expected to grow contributing to more data generation in the coming years. As a result the world will see more targeted and meaningful advertisements surprising the crowds by offering needful.
A Data Scientist Earns More than the Average Employee
As we know, the world is all about data these days and for the most desirable results industries eagerly need data scientists and data analysts. Data sorting is the most crucial phase that requires most skill and techniques to arrange and sort the data according to the need – that’s where the demand for data scientists arises. According to rough estimates the average salary of a data scientist is around 100,000 US dollars and according to the bureau of labor scientists, the salary of a data analyst is around 70,000 US dollars.
How Much Bad Data Cost In US
In simpler words bad data means bad decision making. Bad data for any company means loss of revenue which is not good for any business. The cost of bad data in US economy is estimated up to 3.1 trillion US dollars each year with average American company sacrificing around 12% of its total revenue. However, with good data scientists onboard, it can easily be avoided.
Conclusion
This is a modern era where Data itself is viewed as the world’s most important resource. This makes Data Science equally important to all other business and marketing models. Companies can easily analyze their marketing strategies by extracting relevant data. Market forecasting can also be done by using data science. Given the research on this subject, it is quite clear that Data Science shows immense potential and will be extremely fruitful for business that embrace it.