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How Data Science has changed the world that we live in

26th May 2021
By Adam Boutouili
Delivery Consultant

Data science has impacted the world we live in through so many different ways. Just as well, businesses looked completely different prior to the emergence of data science. Without data science, the way organizations operate and the way data is collected would be completely different.

So how exactly has data science impacted the world? What does the future hold when it comes to data science?

Are you a data scientist or aspiring to pick up a career in this industry? Let’s explore the impact that data science has had on the world, so you can make a more informed decision.

Where did Data Science start?

The use of statistics is rooted in data science. In fact, it’s where the practice started, and has since evolved to include a wide range of concepts. Such concepts include artificial intelligence and machine learning, among others. As data continues to become more readily available, the way we collect, store, and use that data continues to evolve.

The timeline of data science starts here: .

  • 1962 – John Tukey began exploring the shift in statistics and the combining of statistics and computing technology.
  • 1974 –  Peter Naur wrote “Concise Survey of Computer Methods”, which used the “data science” term for the first time.
  • 1977 – The International Association for Statistical Computing was formed with the mission to connect statistics with modern computer technologies.
  • 1989 – The first workshop opened in the Knowledge Discovery in Databases.
  • 1994 – The first cover story about the use of data science for business was published in Business Week.
  • 1999 – Jacob Zahavi wrote about the need for new technology to take on the growing volume of data that had become available to organizations.
  • 2001 – Software as a Service, or SaaS, was created.
  • 2006 – The first open-source and non-relational database was released, called Hadoop 0.1.0.
  • 2009 – The phrase “NoSQL” was reintroduced by data scientist Johan Oskarsson.
  • 2011 – Job openings for data scientists exploded by 15000%, as well as workshops and conferences dedicated to data science and the concept of Big Data.
  • 2013 – IBM announced statistics that showed 90% of data present in the world at that time had been created in less than two years.
  • 2015 –  Google’s use of deep learning techniques improved in performance improved by 49%

In the years since then, data science has continued to evolve and is used by businesses and non-commercial organizations alike.

Why is Data so huge now?

To put it simply: As technology has continued to evolve, the devices we use on a daily basis have become increasingly important. Mobile devices, laptops, watches, tablets, and other devices generate a substantial amount of data. And with that data comes many opportunities for businesses and organizations to draw insights. If a company in today’s world doesn’t implement data science in some form into their business, they will quickly lose substantial market shares to their competitors.

Just as well, the equipment used for data processing has become less and less expensive and more accessible. The cost of storing data has dropped significantly in the last ten years or so. This is likely to do with the fact that GPUs have experienced significant capability improvements during this time and the onset of cloud computing and storage.

The Impact of Data Science

Data Science has made a substantial impact on many different areas of society today.

The healthcare industry is one industry that has benefited from the growth of data science. In 2008, employees at Google discovered that they could track flu strains in real-time. Existing technology could only update on cases week-by-week. Using data science, Google was able to launch one of the first systems for tracking the spread of illnesses.

Just as well, the sports industry has also benefited from data science. A data scientist in 2019 discovered how to quantify and calculate how goal attempts would improve a soccer team’s chances of winning, a concept that was once unachievable. In fact, data science is used to calculate statistics within different sports with ease.

Government entities also use data science regularly. In order to keep track of their citizens’ data, governments around the world use databases to track information about social security, taxes, and other data. The use of new technologies for government use cases is continuing to evolve.

As the Internet has become our main mode of communication as human beings, eCommerce has similarly exploded in popularity. Online brands can use data science to track everything involved in the customer journey– marketing endeavours, purchases, consumer trends, and so much more. One of the best examples of eCommerce companies using data science has to be the use of ads. Have you ever searched for something online or explored an eCommerce product page, only to see ads for that product everywhere across social media and blogs?

The use of ad pixels is directly tied to the collection and analysis of user data online. Brands use consumer behaviours online to retarget potential customers all over the internet. This use of customer data goes beyond eCommerce as well. Applications like Tinder and Facebook use algorithms to help users find exactly what they’re looking for. The Internet is a wealth of data that only continues to grow, and the capture and analysis of this data will only continue to grow.

What will Data Science allow us to achieve in the future?

As data science continues to grow and evolve, we’ll likely see some big changes in the future. To start, data science jobs will likely grow as more industries prioritize data science and technology. IT-focused positions have grown substantially, and that growth will likely only continue.

In terms of data science’s use cases, the future is all about artificial intelligence and machine learning. Once an unachievable concept reserved for science fiction books, AI and machine learning are already becoming an important part of business operations in a wide range of fields. In fact, a majority of businesses that have implemented AI and automation into their businesses have experienced competitive advantages.

Moving forward with Data Science

To summarize, data science has shaped business operations in today’s world in many ways. Not only does data science equip companies with the ability to gain insights into customer data, but it also helps businesses identify key information about their own businesses. That transparency and ease-of-access of data technology and tools have made Big Data a big part of our lives– and it doesn’t show signs of stopping anytime soon.

So what will we see moving forward? In the future, data science will continue to be a substantial part of businesses. In particular, the use of artificial intelligence, automation, and machine learning will only continue to grow as mainstream technology. If you’re considering your future as a data scientist or are considering entering the field, you surely won’t be left wanting for work.

What do you think about the history and future of data science? Tell us what made you consider this career path in the comments below, or get in touch with me at [email protected]!

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