In 1993, the American Dialect Society defined information superhighway as their word of the year. In the decades since, the superhighway has allowed for the rapid development and capture of data – enabling the modern data scientist’s development in large and small businesses.
The need for a corporate data strategy has evolved as data has evolved. Beyond simply looking at simple clusters, modern businesses want to take ownership of their data and develop meaningful and valuable insights. University online courses such as the Master of data science provide an invaluable opportunity for those looking to dive into the complex problems that businesses face today.
As businesses look to capitalize on their data streams, the role of the data scientist in the workplace will become critical to business success
A recent study in Raconteur estimated that by 2025, approximately 463 billion gigabytes of data will be created daily. As a result, existing businesses will need to understand what components of their data can be useful or detrimental to business operations. Understanding how data streams can be used can be an incredible asset for business – however, not truly understanding how your data sources can assist business operations can have a rapidly detrimental effect.
Take, for example, the Facebook gaming powerhouse of the late 2000s known as Zynga. As developers of titles such as FarmVille, Zynga’s data teams sought to use insights from their successful title launches to spin off into alternative game offerings. As a result, the data teams sought to transplant data learnings into other titles in the gaming space.
However, this didn’t succeed. Using data alone is one part of the problem – understanding an issue’s nuances is, in many cases, just as important. In Zynga’s case, data users didn’t understand how user preferences and changing user trends (i.e., the shift to smartphone gaming) would impact their games. As a result, Zynga fell behind mobile game companies for a time as they sought to make ground in this competitive business area.
Qualified analysts will have potential career opportunities spanning various fields in a highly competitive field
Historically, data science has been considered a role in communicating business outcomes between corporate departments and the executive suite. However, as data volume, variety, and velocity explode, data stories will become more ingrained into business operations, and data scientists will spend more time communicating across a broader range of stakeholders.
Understanding data will become imperative for most organizations that wish to gain a competitive advantage. This isn’t simply restricted to one industry or another, however – ultimately, there will be a need for data scientists across most, if not all, industries currently in place today.
No matter your passion, there’s potentially a data role out there for you. For example, perhaps you are interested in understanding hospital inventories and can develop logistical tools that ensure the right medications are stocked at the right time. Maybe you’re interested in the charities sector, diving into the data to identify trends that could improve donations. Or perhaps you’re interested in motor vehicles and using transport data to develop vehicle safety standards that are safer and more rigorous than current standards.
A career in data science allows graduates to get exposure to a wide range of fields – ultimately, you’re only limited by your imagination.
Data are more than numbers on a screen – with the right analyst, immense value can be leveraged from the data and processes businesses use today
Sometimes data insights come from outside organizations – providing valuable insight as to how simple changes to operational procedures may result in immense savings in the long term.
Take, for example, the work of Suvir Mirchandani. As a fourteen-year-old, Suvir explored the capabilities of inkjet printers after noticing that he received a lot more printed handouts at school. His findings? Change a font slightly and potentially save the school district tens of thousands of dollars annually.
Data scientists can drive change in an organization – and while it can seem scary, it doesn’t have to be. Data is a way to help your business – and that’s not something managers should be afraid of.
For startups such as ride-sharing app Uber, the role of data has become omnipresent in business operations – much to the benefit of their data science teams
For some startups, data has become heavily ingrained into corporate culture – and for Uber’s data science teams, that’s no exception. As a result, data Scientists within Uber’s teams have the opportunity to tackle a range of real-world problems. From understanding traffic flows, optimizing customer priority flows, and improving the quality of geolocation data. While these issues seem complex, data scientists within Uber’s teams can leverage the benefits of a well-structured data operation to build effective tools and solutions for their stakeholders.
Looking even further forward, there’s massive potential for data scientists to leverage modern artificial intelligence and machine learning (AI & ML) techniques to optimize business operations
Some legacy businesses, such as national logistics provider Australia Post, use their data to drive operational efficiencies in a rapidly changing logistics environment. For a company that delivers more than 2.7 billion items annually, with a rapidly growing parcel business, being able to leverage data is crucial – even improvements at a small scale can have massive implications.
Data science will remain one of the most in-demand careers, and it’s undeniable that the challenges of data will present unique, diverse challenges for those that wish to take advantage of it. If you want to pursue a career in data science, there’s never been a better time to speak to a career advisor and explore your options.
