DataRobot is clearly on an acquiring spree. In an endeavour to allow firms to harness the power of artificial intelligence, DataRobot acquired California-based Paxata earlier this month. With this, the firm has now completed three acquisitions in 2019 to enhance its offering and allow their customers to manage their machine learning workflows effectively.
Built to automate machine learning, DataRobot is leaving no stone unturned in delivering superior solutions to firms for driving their business by integrating the latest technologies such as AI and data science. Since its inception in 2012, the firm has acquired five startups that were making new advancements in allowing IT firms to automate the machine learning activities.
- Nutonian – 2017
- Nexosis – 2018
- Cursor – 2019
- ParallelM – 2019
- Paxata – 2019
As companies are looking to imbibe intelligence, many AutoML providers such as H20.ai, Azure AutoML, among others, are striving to take the lead in the landscape. Thus, DataRobot is quickly acquiring various companies to deliver a solution that will streamline the complete AI workflows.
In 2017, DataRobot acquired Nutonian, an AI-powered modelling engine that specialises in time-series analytics modelling. The first acquisition allowed it to provide predictive analytics for firms that highly rely on time-series analytics. And to further enhance its capabilities, in 2018, DataRobot acquires Nexosis, while keeping the terms of acquisition confidential. The motive with this was to provide ML at the hands of everyone with the enterprise-grade platform.
Further, the firm acquired Cursor and ParallelM in 2019 to enable data collaboration from different sources and assist companies in scaling the development, governance, management of ML-based solutions in production, respectively.
After integrating its platform with numerous capabilities through acquisition, it extended its AutoML solution’s dexterity and allowed firms to do more than just model selection. But a lack of functionality to prepare datasets for training the models caused hindrance in AI workflows with its solution.
Manual data analysis can never match up the speed at which firms collect the data, thereby, the need for automation in AI workflows is of paramount importance. Therefore, it was natural for DataRobot to acquire Paxata that could empower companies to make high-quality data for ML models. Paxata would also provide its AutoML solutions to help firms quickly deploy machine learning models for obtaining informed insights into the information they collect.
Challenges Faced By DataRobot
With a little more than 1,000 employees, DataRobot is an AutoML provider that offers its solutions in more than 12 countries. Today, AutoML is being adopted by different companies to train high-quality ML models specific to their business needs, even without data science experts. As per a report, around 86% of the companies are willing to integrate AutoML next year. Such trends are helping DataRobot to gain clients across different countries.
However, numerous limitations in AutoML makes it difficult for companies to be confident about the products they offer. For one, preparing high-quality data for feeding into AutoML is a strenuous task for data scientists. “We repeatedly received feedback from our customers that they wanted us to deliver additional capability, which was to simplify how they prepare data required for AI,” mentioned DataRobot in the announcement.
To mitigate such challenges, DataRobot acquired Paxata – a self-service data integration and management firm – that enables companies to transform data into information quickly. Using Paxata, developers can efficiently perform data cleaning and build datasets that can be fed to the AutoML solution of DataRobot. “Two companies were a great fit, and it made a lot of sense to come together, it will allow our customers to go from data to value quickly,” says Prakash Nanduri, CEO and co-founder at Paxata. According to leading research and advisory firm, hyper-automation was one of the top strategic technology trends for 2020. This demonstrates the importance of the need for automating the AI activities in coming years.
The integration of Paxata’s solution with DataRobot’s AutoML will allow them to provide end-to-end automation products to firms. “To resolve pressing problems and deliver value through AI to the enterprise, DataRobot is focused on building an enterprise AI platform that provides automation for gaining ROI from raw data,” mentioned Igor Taber, SVP of corporate development and strategy at DataRobot in the announcement.
Unlike other AutoML companies, DataRobot is committed to enhancing its platform not only to carry out model selections and hyperparameter optimisation but also the collection and preprocessing of data for becoming a one-stop-shop for AI-based activities. This will decrease the dependency of other applications for deploying ML models. However, we are way behind in streamlining the entire workflow with one platform, but DataRobot is arduously trying to accomplish that.
Working on the same objective, DataFlow is also raising funds and has now raised more than $431 million, of which $206 was raised in Series E funding in September. The firm is further poised to gain momentum in the AutoML landscape and democratise AI technology.