DataRobot Overview

DataRobot

DataRobot is a company that sells software that helps companies to develop and deploy in-house AI models. The company aims to automate many aspects of the traditional jobs of data scientists, including every step that is needed in the preparation, development, deployment, monitoring and maintenance of AI applications. The concept the company brings, enables customers to bring their data and business questions to the DataRobot system for it to in turn give customers accurate models for their tasks.

Companies that have used this service are; Lenovo which used the company’s software to estimate the retail demand in Brazil and United Airlines which used the software to predict which passenger might gate-check bags.

DataRobot helps to boost business impact by using artificial Intelligence. Stake holders can also utilize the company’s AI platform and automated decision intelligence to collaborate in extracting business value from the data given to the AI. The company’s users range from data scientists, business analysts, and IT teams responsible for the smooth running of technological solutions to business executives and analytics leaders who can derive increased business impact from the models that were deployed.

The growing demand for AI is at an unprecedented rate and this growth of demand is being hampered by the low rate of data scientists and machine learning experts. In a quest to address this talent gap came the rapidly evolving field of on-code AI tools that make the creation and deployment of ML models accessible to companies that do not have enough highly skilled data scientists and machine learning engineers.

In an interview with Tech Talks, the chief product officer at Datarobot, Nenshad Bardoliwalla discussed the problems faced while meeting the needs of machine learning and data science in different sectors and how no-code platforms are helping to democratize artificial intelligence. The reason behind the spike in the demand for AI is due to the amount of digital exhaust generated by businesses and the number of ways that this digital exhaust can be used to solve real business problems. As all this is going on, there are nowhere near enough data scientists with vast expertise to exploit the data in the world.

“We knew 10 years ago when DataRobot began that there was no way that the number of expert data scientists that the world would have will be enough to satisfy the demands for AI driven businesses outcomes” Bardowliwalla said. And as the years passed the company has seen the demands for machine learning and data scientists sky rocket from sector to sector in companies as businesses are coming to the realization of the values of machine learning, weather it is predicting customers churn Ad clicks, possibility of engine failure, medical outcomes or other things that need extreme precision. As the demand of data scientist as driven a wedge into the AI talent gap, everyone isn’t being served equally.

This shortage has created a serious competition for data science and machine learning talent. The financial sectors leading the way, hiring AI personnel at large numbers and putting machine models into use. Big tech companies with deep pockets are also hiring experienced data scientists and machine learning engineers or acquiring AI labs with all the engineers and scientists working with them to exploit their data driven commercial empires. Smaller companies are left out because of limited resources to hire enough data scientists and machine learning experts.

As machine learning requires knowledge of programming languages like phython and complicated libraries like tensorflow, most business people cannot create and test models without data scientists. This area is where no-code AI platforms come to play.

DataRobot and other providers of no-code AI platforms create tools that allows this domain experts or business savvy people create and deploy machine learning models without any need to script a code.

With DataRobot, clients can upload their data sets on the platform, perform the necessary preprocessing steps, choose and extract features and create and compare a range of different machine learning models, all through an easy to use graphical user interface.

The no-code AI is not created as a replacement for data scientists or machine learning engineers but a way to increase ML productivity across industries, empowering more people to create models. This eases the stress level of the data scientist and the machine learning engineer and allows them put their skills into work in a more efficient way.

Machine learning tools evolved rapidly. A decade ago, the ability to query data and generate report at organizations was limited to people who had the special coding skill set required to manage databases and data warehouses. But today non coders and less technical people can perform most of their querying tasks through easy to use graphical tools without assistance from data science experts. DataRobot launched the first set of no-code AI tools in 2014 and then expanded at a rapid pace since then in the applied machine learning industry. The company unified its tools into the AI cloud in 2021 and in Mid-March, that same year, the company released AI cloud 8.0 the latest version of its platform.