Teradata VantageCloud: Open, Scalable Cloud Analytics for AI
VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.
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dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use.
With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.
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Minitab Connect
The most accurate, complete, and timely data provides the best insight. Minitab Connect empowers data users across the enterprise with self service tools to transform diverse data into a network of data pipelines that feed analytics initiatives, foster collaboration and foster organizational-wide collaboration. Users can seamlessly combine and explore data from various sources, including databases, on-premise and cloud apps, unstructured data and spreadsheets. Automated workflows make data integration faster and provide powerful data preparation tools that allow for transformative insights. Data integration tools that are intuitive and flexible allow users to connect and blend data from multiple sources such as data warehouses, IoT devices and cloud storage.
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SCIKIQ
Every CXO wants one view of the enterprise: costs, revenue, and growth, in one place, in real time.
SCIKIQ powers that enterprise 360, in detail, on governed data.
SCIKIQ is an enterprise data fabric platform that unifies data integration, data quality, data governance, and master data management and makes data AI-ready through a semantic layer built on ontologies and knowledge graphs.
Instead of moving data into yet another warehouse, SCIKIQ connects to systems where they are and applies governance, lineage, and business context on top.
No migration. No rip-and-replace.
What's inside:
167+ pre-built connectors — SAP, Snowflake, Oracle, Kafka, and more
Data catalog with automated data lineage and active metadata
No-code ETL, orchestration, and data quality management
Semantic layer with ontologies and knowledge graphs for AI-ready business context
Agentic AI and conversational analytics — business users query governed data in plain language
Data Product Factory and internal data marketplace — package governed datasets into reusable data products
Data observability — catch schema changes, quality drift, and pipeline failures before they hit reports
Security and compliance: role-based access, column- and row-level security, audit trails, and policy automation for GDPR, India's DPDP Act, and regulated industries like banking and healthcare.
Deploys cloud-agnostic — AWS, Azure, GCP, or on-premises, and works alongside existing investments in Power BI, Tableau, and dbt rather than replacing them. API access included.
Live in 30–90 days.
Recognized by Forrester as a Top 34 AI Platform globally. NASSCOM League of 10.
Trusted by enterprises in banking, financial services, retail, manufacturing, and supply chain.
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