KNIME Announces Integration With Anaconda, Strengthening OSS Security Between the Python and Low-Code Communities
KNIME Data Experts Can Now Leverage Anaconda for Building and Deploying Reliable Data Apps and Services
ZURICH & AUSTIN, Texas–(BUSINESS WIRE)–#AI—KNIME AG, a data analytics platform company, today announced a new integration with Anaconda, Inc. to provide enterprise customers best-of-class options for managing secure Python dependencies within KNIME workflows across their corporate development, testing and production data science environments.
KNIME is an end-to-end platform that was built for data science as a collaborative discipline, enabling each team member to best contribute his or her expertise and to focus on what’s important. Each data or domain expert can work however they choose — all code, low code or no code — while still collaborating in a single intuitive environment and integrating the most advanced techniques in the industry. With the new ability to use Anaconda with KNIME, enterprise teams can take advantage of Anaconda’s additional enterprise benefits of a secure repository (through the procurement of a separate license), making KNIME workflows more securely deployed into production-ready data apps and API services.
The Anaconda integration and partnership is the next step for KNIME in a series of developments focused on strengthening the relationship between a no-code and a scripted approach to data science. KNIME takes a distinct open and integrative approach to ensure that every data expert can best utilize the tools they know and love, without compromising the collaboration that’s necessary for fully productionized data science solutions.
Current KNIME and Anaconda commercial customers can take advantage of KNIME’s integration with Anaconda’s tools through the Python Extension for KNIME and licensing Anaconda Commercial Edition® or Anaconda Team Edition®. Existing KNIME customers who are interested in learning more about the advantages of using KNIME with Anaconda’s repository should reach out to their contact at KNIME or email firstname.lastname@example.org.
With more than 25 million users, Anaconda is the world’s most popular data science platform and the foundation of modern machine learning. We pioneered the use of Python for data science, champion its vibrant community, and continue to steward open source projects that make tomorrow’s innovations possible. Our enterprise-grade solutions enable corporate, research and academic institutions around the world to harness the power of open source for competitive advantage, groundbreaking research, and a better world. Visit www.anaconda.com/.
KNIME helps individuals and organizations make sense of data.
The core software provides a single intuitive environment, appropriate for anybody working with data, from the analyst to the data scientist. For business and domain experts, KNIME Software serves as a no-code platform, lifting the ceiling beyond spreadsheets and BI. For data experts, KNIME Software serves as a low-code platform, giving them access to the widest range of tools and techniques available with or without coding. The platform is complemented by enterprise-grade features that facilitate collaboration and deployment via secure apps and services.
By bridging the worlds of dashboards and advanced analytics, KNIME shortens the distance between data and action. KNIME Software empowers more business experts to be self-sufficient and more data experts to push the business to the bleeding edge of modern data science, integrating the latest AI and machine learning techniques. KNIME is distinct in its open approach, which ensures easy adoption and future-proof access to new technologies. Learn more at www.knime.com.
KNIME, KNIME Analytics Platform, and KNIME Server are trademarks of KNIME. All other brand names and product names are trademarks or registered trademarks of their respective companies.
Tags: KNIME, KNIME Analytics Platform, Anaconda, Python, low code, no code, open source, data science, data scientist, enterprise architect, engineer, developer, data analytics, artificial intelligence, machine learning, AI, ML