Paxata today announced it has raised 33.5 million to bolster the machine learning and semantic analysis foundations of its enterprise information platform. Led by Intel Capital, today's investment is Paxata's fourth funding round and brings its total capital raised to 61.5 million. Paxata's platform provides a self-service, visual approach for information management to large corporations. "We target the one billion people in the enterprise who know how to use Microsoft Excel and want to use data to make business decisions," said Nenshad Bardoliwalla, cofounder and chief product officer of Paxata, at the Intel Capital Global Summit. According to Bardoliwalla, Paxata helps those who need fast access to meaningful data without having to write code or learn to use Hadoop.
BOSTON – December 12, 2019 – DataRobot, the leader in enterprise AI, today announced that it has entered into a definitive agreement to acquire Paxata, the pioneer of self-service data preparation and leading data fabric provider, to fulfill its mission to build the world's first automated end-to-end enterprise AI platform. While the massive impact of AI on enterprises is well understood -- PwC forecasts by 2030 AI could contribute $15.7 trillion to the global economy -- companies must overcome several key challenges associated with AI in order to reap the benefits and become successful. Data preparation is one area that has historically held companies back. Creating a dataset for training predictive models, deploying data prep steps with AI models, and preparing data specific to AI routines are all major challenges companies face when it comes to leveraging data at scale. By providing tools that help users build automation into their data prep processes, the Paxata acquisition will alleviate these pain points for customers and dramatically enhance their ability to achieve AI-driven outcomes rapidly.
Paxata, the pioneer in self-service data preparation, today announced that it was named an innovator in Enterprise Management Associates (EMA) "Innovation in the Use of Artificial Intelligence (AI) and Machine Learning (ML) for Data Integration and Preparation" Top 3 report. According to the findings, more than half of all participants (52 percent) said that the use of AI or ML to automate the data preparation or integration process is important to their organization. Because of the prominent role of data integration and preparation in any analytics project, the report stated that AI-enablement should be a priority for analytics leaders at all levels as it provides organizations with the ability to overcome the constraints of legacy or less-automated data processing. The complimentary report can be downloaded here. "The next major shift in the analytics, business intelligence, and data management markets is coming from the use of AI and ML across the entire information supply chain. Along with using machine learning to find the next-best offer, companies can now point algorithms at modern data platforms to find links between data sets, automate data preparation, or breaches in data governance," said John Santaferraro, Research Director at EMA and lead author of the report.
Data science tools are evolving. Becoming data scientist is hard. In any hard task, focus is critical. As a data scientist, Python should probably be the first tool you should master. Kaggle, the community for data science competitions, publishes surveys of data scientist such as their "2017 the State of Data Science" report.
Today, I'm excited to share another significant commitment by Microsoft to democratize AI: a new Microsoft Ventures fund for investment in AI companies focused on inclusive growth and positive impact on society. I also have an update about the growth of our overall portfolio of companies. AI holds great promise to augment human capabilities and improve society by tackling some of the world's biggest problems. Our recently announced partnership with OpenAI is a key example of us working to use AI to address important issues such as climate change, inequality, health and education. Building on that, our participation in the Partnership on AI, and other efforts, we'll make investments in startups that are responsibly harnessing the promise of AI to empower people and businesses.