Data Science has been a hot topic within the technology world in 2019, with the job title of Data Scientist being named the number one best job in America for the past three consecutive years. Given that companies need to use their data to improve services, boost productivity or drive sales, it is likely that we will see Data Science ingrained in everything we do in the future. And that is the key word - future. In comparison to Data Analytics where Big Data is used to look at how performance has been in the past, Data Scientists use Big Data to predict all eventual outcomes that could impact an industry.
Data Scientists at the cutting edge of their sector working within AI & Machine Learning can include the information gathered from Big Data sets to create models that can automatically learn from their mistakes.
Data Science has impacted almost every industry from healthcare, where their models can predict patient outcomes and side effects, to traffic, where algorithms can help to predict when rush hours will be and when best to travel at weekends. Of course, no algorithm or model is perfect, you can never truly predict a person’s behaviour and allowances need to be made for real life, but still in its best form Data Science can be used to make recommendations based on real life data to help predict certain outcomes.
Here are 5 industries where we can see Data Science at work;
Driving, flying or even cycling, travel is a necessity to pretty much every person. So, imagine if there was a model that could contribute to lowering emissions, shortening travel time and saving money. This is where Data Science comes in. Data Scientists can use Big Data to predict busy travel times in order to optimise routes - figuring out the quickest and most cost-effective option. This may sound simple and a minor change but when taken into account for the thousands of trips taken across the world this could help to save hundreds of litres of fuel as well as ultimately saving businesses and people time!
We’ve all heard of Uber whether that be as a taxi company or a food delivery service. Here’s how Uber has used Data Science to hit the road;
Uber Eat’s main goal = to deliver food and hot! How can Data Science help to achieve what seems like such a simple goal? With the help of machine learning, meteorologists and statistical modelling, staff at Uber can predict all possible variables from traffic to bad weather and how these will affect both travel and cooking times. Leading to the delivery process being as efficient as possible. Happy Customers = Bigger Business.
Statistics have always been a massive part of the sporting industry from how to play, how to win and how to pick teams. In fact BusinessWire has found that the global sports analytics market is expected to reach a revenue of $4.5 billion by 2024. So, with the rise in Data Science it is only natural that we would see this used in sport.
Whether you’re a football fan or not it is clear how statistics and analysis can help to pick teams and hopefully, win games.
Here’s how Liverpool nearly won the 2019 premier league using Data Science:
Liverpool have placed themselves at the cutting edge of Data Analysis and even have a dedicated Head of Research; Ian Graham. Ian is well known for using Data Science to beat wealthy football teams in securing great, undervalued players. Football is a chaotic game which can make it difficult to analyse who is performing well and likely to score. However, he created a model to figure out how every run, pass and attempt at scoring influenced the chances of winning the game. Liverpool now uses this model to recruit and for game winning strategies.
Although many wouldn’t think that the Government would class itself as ‘online’, the Government actually holds more information than Facebook and Google combined. If you think of the information the Government stores; phone records, Photo ID’s, fingerprints, information requested through warrants from companies such as Google, it is clear that there is wealth of data that can be used to analyse future outcomes.
Tax is a money maker for any Government. Here’s how Data Science can help the US Government find potential tax evaders;
It’s estimated that tax evasion costs the US Government $458 billion a year. Unsurprising then that in an age of technology the Government are looking to update their fraud detection capabilities. To do this the Government have taken full advantage of the data available to them and created taxpayer profiles. Using Data Science, they can pull information from social media, email analysis, electronic payment patterns and metadata to predict tax returns for each profile. This means that any returns that come back and wildly exceed expectations are automatically flagged to the audit team.
It’s no secret that online shopping is a booming market. Even at a basic Data Analytics level, retailers can change web page layouts and pricing based on typical buyer profiles. The emergence of Data Science has given retailers the ability to change the way they advertise and increase the use of product placement to drive sales and website traffic.
Here’s an example of how Instagram uses Data Science to fully tailor a shopper’s online experience.
Instagram is well known for their ability to push any product that you may have been looking at online to the top of your news feed in a slightly ‘creepy’ manner. Instagram is owned by Facebook; Facebook holds detailed information on you. Based on your likes, comments, personal information, web history and other apps, Data Scientist’s at Instagram can create algorithms that will predict the products you are most likely to buy and push them to the top of your profile. And with 500+ million worldwide profiles it is easy to see how Data Science can make a huge impact within ecommerce and even create jobs purely for people to advertise products via their Instagram profiles.
There are so many apps available for socializing, whether it be Facebook for connecting with old or new friends, Instagram to check out your favourite influencer or Tinder to find the perfect date. The rise of social networks has completely changed the way people connect. The amount of personal data that these apps hold makes it easy for Data Scientists to create algorithms that can suggest people you may know or your perfect match.
Here’s how Facebook uses Data Science to find those friends ‘you may know’:
When you log into Facebook you may notice “people you may know” pop up and wonder where they’ve found these people from your past! When you sign up to Facebook you give them permissions to search through your contacts, this allows Facebook to find those contacts already on the platform. Facebook also asks you for personal information about where you went to school, where you live etc. giving their algorithms more data to search potential connections with. Using what they call Network Science they can use the structure of your network to predict not only who you might know now but people you might also know in the future!
Data science is now part of everyday life. It is only going to get more popular and pivotal. The challenge facing the industry is ensuring that there are enough good quality data scientists entering and more importantly, keeping up with the developments that are ongoing. Once the challenges of a slower moving talent market can be overcome, it is likely that the things we have seen above are just the tip of the iceberg.