putilov_denis - stock.adobe.com
Tableau users will be able to accelerate the speed of their machine learning automation and add a visualization layer to model building with a new partnership with AI automation vendor DotData.
As an enterprise-grade AI automation platform, DotData uses AI-powered feature engineering to speed up the process of building AI and machine learning models.
A 2018 startup, DotData is based in San Mateo, Calif., and has raised about $43 million, according to Crunchbase.
The vendor's goal is to help enterprises lower the cost of model development while accelerating ROI using DotData's automated data science platform.
Low-code/no-code for Tableau users
By partnering with Tableau, one of the biggest analytics vendors, DotData said it will help citizen data scientists using Tableau get more direct access to DotData's low-code and no-code platforms.
Automated machine learning systems such as DotData streamline many of the manual steps involved in building the models, making data scientist and machine learning engineers more productive, said Kashyap Kompella, CEO and chief analyst at RPA2AI Research.
"Building machine learning models is iterative and time-consuming," Kompella said.
While it is common for Tableau to partner with multiple established and emerging technology players, the partnership benefits both Tableau and DotData users, he said.
Adding visualization layer to machine learning
Kashyap KompellaRPA2A1 Research
With the partnership, "Tableau users, who are also customers of DotData, will be able to add a visualization layer for their machine learning workflow," Kompella said.
According to DotData, combining Tableau's data preparation and visualization capabilities with its predictive modeling capabilities will enable users to perform full-cycle predictive analysis from raw data.
"Visualization is the last mile of analytics," Kompella said. "Auto machine learning has become more intuitive and powerful when used in tandem with visualization tools like Tableau."
DotData entered the IoT market in 2020 with a system designed for edge computing that provides real-time analytics in low-latency, low-memory conditions.