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On June 8, secure data access platform Immuta announced that it had raised $100M in Series E funding. NightDragon led the round, with participation from new investor Snowflake Ventures, and prior investors Dell Technologies Capital, DFJ Growth, IAG, Intel Capital, March Capital, StepStone, Ten Eleven Ventures, and Wipro Ventures. Immuta will use the funds for additional hiring in sales, marketing, and customer success, as well as continued R+D and building out strategic partnerships with other vendors in the cloud data space.
Enterprise cloud data integration platform Matillion announced a strategic investment from Citi Ventures this week for an undisclosed amount. Matillion’s last publicly shared valuation was $1.5B, after their series E round last September for $150M.
Launches, Updates, and Partnerships
Databricks announced that data lineage for Unity Catalog is now available in preview on AWS and Microsoft Azure. The data lineage feature will let customers understand the history of any data in their lakehouse – where it came from, when was it created, who created it, how has it been modified from the original raw data import, and how it’s being used, among other features. Because this is done automatically, the results save time and provide better accuracy compared to manually tagging data with the relevant metadata, and allow organizations to better meet compliance standards and relevant regulations.
Dataiku announced a partnership with Microsoft Azure this week, launching the Dataiku cloud AI platform in the Azure cloud. Dataiku’s new cloud stack accelerator capability allows for automated deployment, configuration, and management of Dataiku’s Everyday AI platform on Azure with a template-based approach.
At DataRobot AIX 2022, DataRobot announced a number of improvements to their AI Cloud product. Notable enhancements include code-first notebooks integrated into AI Cloud, bringing capabilities from the recent Zepl acquisition into DataRobot’s offerings and augmenting support for code-centric data scientists; expanded enterprise-level MLOps capabilities for the full model lifecycle, including integrations with GitHub, SumoLogic, Splunk, Datadog, and Zendesk; bias mitigation that automatically identifies and adapts machine learning models exhibiting detectable bias prior to deployment; and automated compliance documentation, even for models built outside of DataRobot. DataRobot also broadened their partnership with Google Cloud, launching AI Cloud in the Google Cloud Marketplace.
Expert.ai announced this week that it has joined the Qlik Technology Partner Program. Qlik users will be able to use expert.ai language intelligence within Qlik Cloud, including natural language capabilities such as sentiment analysis, document categorization, and text disambiguation.
At this week’s Google Cloud Applied ML Summit, Google revealed numerous new features and partnerships for their applied machine learning product, Vertex AI. Google’s existing NVIDIA partnership yielded one-click deploy of NVIDIA AI solutions to Vertex AI Workbench, as well as the new Vertex AI Training Reduction Server, which optimizes multi-node distributed training on NVIDIA GPUs, reducing training time for large language models like BERT. Google also announced a new data partnership with Neo4j, allowing data scientists to work with data and build models in Neo4j Graph Data Science, then deploy the models using Vertex AI. One more partnership with Labelbox provided yet another integration, reducing the time required to label unstructured data and speed up the model development process. Finally, Google also announced the preview of several standalone features: Vertex AI Tabular Workflows, allowing users to choose which parts of the model building and deployment processes they want to use AutoML for while being more hands-on with other parts; Serverless Spark for Vertex AI Workbench for data scientists to launch a server less spark session within a notebook; and Vertex AI Example-Based Explanations, which helps data scientists diagnose issues in their models using explainable AI techniques.
Informatica revealed enhancements for its Global Channel Partner Program this week to boost partnered sales and support efforts for cloud modernization with joint customers. The new initiatives include incentives to source bookings for Gold and Platinum-level partners; sales, delivery, and technical certifications to help partners in their engagements with joint customers; and a points-based Channel Rewards program to recognize individuals for their contributions.
Open source data science company KNIME announced a strategic partnership with Snowflake. Users will be able to use the low/no-code KNIME Analytics Platform to perform analytics on data stored in Snowflake.
RapidMiner announced the release of a new version of their data science platform. The latest version marks a move to the cloud as a multi-tenant, SaaS offering.
Enterprise data platform Teradata introduced Teradata Vantage, a multi-cloud analytics platform integrated with machine learning service Amazon SageMaker. The partnership will allow Teradata customers to access machine learning capabilities via Amazon and apply it to data and analytics hosted on Teradata.
TIBCO Analytics Forum (TAF) returns June 13-15, 2022. The online-only event has a theme of “Analytics in Time and Space.” Featured speakers include Ben Shneiderman, computer science professor and founding director of the Human-Computer Interaction Laboratory at the University of Maryland; data visualization guru Nadieh Brehmer; David Baltar Boilève, data scientist at Hospital Universitario Lucus Augusti; Mark Lora, director of enterprise data systems, Taylor University; and Birchcliff Energy analytics engineer Monica Brookwell, among others. To register for the event, please visit TAF 2022