Question: Can you recommend a solution that allows data engineers to work with any data, anywhere, and securely access, explore, transform, and clean data?

Airbyte is an open-source data integration tool that supports more than 300 sources of structured and unstructured data. It's got a Connector Builder, support for extracting unstructured data for destinations like vector stores, and integrations with OpenAI and dbt. Airbyte has single sign-on, role-based access control and compliance with major regulations for data security. It can be used in cloud-hosted or self-managed configurations, making it good for big data integration projects or smaller ones.

Another strong contender is Cloudera, a hybrid data platform that ingests, processes and analyzes data in the cloud and on-premises environments with end-to-end security. Cloudera can consolidate vast amounts of data from many sources into a single trusted system for insights and AI model training. It can provide real-time insights, automated data pipelines, big data analytics and large-scale application deployment.

Dataiku is designed to make data a systematic part of business operations for better results, and to make AI a tool for everyday work. It can handle data preparation, machine learning, MLOps, collaboration and governance. Dataiku is a Leader in the Gartner Magic Quadrant for Data Science & ML Platforms, and it offers a variety of products for AI and Machine Learning, Data Analytics and Enterprise AI.

For data workspaces that span multiple people, Deepnote offers an environment where teams can explore, analyze and share data with Python, SQL and no-code tools. It can connect to data warehouses, databases and lakehouses, and it's got features like AI-powered code completion, interactive visualizations and real-time commenting. Deepnote offers role-based access control, single sign-on, directory synchronization and HIPAA and SOC 2 compliance for data security.