data science and social media

The Data Science Goldrush

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Data science is one of the hottest areas both in the job market and in the tech sector. The reason is that companies are beginning to make use of data analytics, data modeling, and data-based operations research to make more informed decisions, to produce forecasts, and to learn more about their customers.

Social media has given companies an incredible array of data points on individuals including their hobbies, their list of friends and contacts, and their likes and dislikes. Every time a person makes a post or even looks at a post, social media keeps track. Other companies such as Google can also keep track of which videos people watch on YouTube, what purchases, people make, as well as what they search for in the Google search engine.

We Give Away Data

Smartphones, whether they use android or an Apple operating system also keep track of what people do, where they go, the images they take, the messages they send.

The vast majority of phone users voluntarily give away this data whenever they download and install new apps or they log in to social media pages.

Fortunately, certain kinds of other data this is more private and protected, but still somewhat available such as your credit score.

Your health records are generally not available, but your insurance company has access to them.

Another source of data is from the Internet of Things. Now, even refrigerators, some thermostats, personal health monitors such as Fitbit, and certain LED lights are connected to and can even be controlled from the Internet. These devices produce a stream of data.

All of these devices, our social media, and our smartphones, produce an ongoing stream of data for almost every person.

Companies are just beginning to realize what they can do with this data.

One thing that is often overlooked in this is that data without analysis is virtually meaningless to humans. That is where data scientists and data analysts come in.

Companies will pay a lot of money to gain valuable insights about their businesses, their services, and their customers. Data scientists, data analysts, and statisticians are the ones who can help make sense of this data boom and show others what the data reveals.

This boom coincides with the availability of inexpensive and powerful computing resources.

One such programming language that is taking off because of its simplicity and its ability to calculate statistics and use linear algebra to predict, model, and correlate is Python. Python is one of the key topics that I intend to cover and explain on this site.

After writing this article, I found a similar sentiment in a recent blog post at

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