The demand for data analytics is just growing bigger each year. Companies across the world have realised the importance of data analytics and have started hiring for these positions in bulk.
While companies succeed in onboarding top data analysts, many settle for candidates who have no coding expertise and that could be seen during the real work. And this is where data analytics tools come into the scenario. These tools don’t require much/any coding and reduce the workload of data science professionals significantly, managing to deliver better results.
To fill the above-mentioned gap in the data science domain, MIT and the Brown University researchers have gone beyond the generic data analytics tools with their new platform Northstar.
The Northstar is an interactive data science platform that rethinks how people interact with data. The platform is designed and built in such a way that it allows non-specialists to use machine-learning models to make predictions. Simply put, users without programming experience, background in statistics or machine learning expertise can work on exploring and mining data along with building, analyzing, and evaluating ML pipelines.
It has always been intriguing to watch people in movies using holographic screens, dragging and dropping things from one end to another and do a lot of technical stuff. And with this new platform by MIT and Brown University, it seems the days are not so far when businesses wouldn’t need typical data science professionals to solve their complex problems — they would just need touchscreen device and any existing data sets in order to build powerful prediction tools.
Also called as the virtual data scientist (VDS), Northstar could be a great system for professionals as well as business of small and mid-size. When the research stated that the platform is built to keep non-specialists in mind, they meant professionals from other domains as well. For example, an average doctor’s office can use Northstar to come out predictions about their patients based on the historical medical data.
Another example would be business owners — they can use this platform to predict their sales based on the data about their previous sales and the ongoing sales. This would not only help professionals, but also business that doesn’t have a dedicated data science team or department. “Even a coffee shop owner who doesn’t know data science should be able to predict their sales over the next few weeks to figure out how much coffee to buy,” says co-author and long-time Northstar project lead Tim Kraska.
Talking about the interface of the Northstar and how it works, here it is:
- It is a blank canvas that supports several types of touch screens.
- User can upload their data sets (that shows in the form of boxes on the left.)
- Using the drag and drop, users can draw lines connecting boxes. Meaning, they should be processed with an algorithm of their choosing in combination with one another.
- combine inputs to generate predictive, AI-based analysis.
- Also, all data are stored and analyzed in the cloud.
“It’s like a big, unbounded canvas where you can layout how you want everything. Then, you can link things together to create more complex questions about your data,” says Emanuel Zgraggen, a postdoc and main contributor of Northstar.
Technology itself is a double-edged sword. Every time we witness a major breakthrough in the tech industry, we always end up thinking more and more about the way it is going to affect the human workforce.
You cannot deny the fact that there has always been a fear inside everyone, “what if robots and AI completely take off human jobs.” The data science domain is no exception; no matter how helpful or innovate Northstar is, there are definitely thoughts of platforms like this becoming more and more advance and take the jobs of a data science professional. And the thoughts are valid enough. A data scientist spends a significant amount of time and money to gain knowledge and land a job, and when out of the blue a platform like Northstar shows up, the concerns become real.
However, there are people as well, who thinks that this platform would only help existing data scientist with their job. It might become more advanced, but it won’t be able to beat the intelligence of a human mind.