dbt
dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow.
Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.
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AnalyticsCreator
AnalyticsCreator is a metadata-driven data warehouse automation application for teams working in the Microsoft data ecosystem. It enables data engineers to design, generate, and maintain production-ready data products across Microsoft SQL Server, Azure Data Factory, and Microsoft Fabric.
By using centralized metadata, AnalyticsCreator generates ELT pipelines, dimensional models, historization logic, and analytical models in a consistent, version-controlled way. This reduces manual implementation effort and tool sprawl while ensuring transparency through built-in lineage tracking and clear visibility into data dependencies and change impact.
With CI/CD integration via Azure DevOps and GitHub, plus support for custom SQL, AnalyticsCreator helps data teams scale delivery, enforce standards, and maintain control as complexity grows.
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Rocket Data Intelligence
Rocket® Data Intelligence (RDI) delivers comprehensive visibility into enterprise data across mainframe, distributed, and cloud environments. It automatically discovers metadata, lineage, and data relationships so organizations can see where critical data resides, how it moves, and which applications and processes rely on it. RDI supports legacy and modern platforms, including Db2, VSAM, IMS, Adabas, Datacom, relational databases, ETL tools like Informatica and DataStage, code such as COBOL, Python, and Java, and cloud data stores.
RDI provides enterprise-grade capabilities including automated data discovery and code parsing, impact analysis, lineage filtering, role/LOB-based categorization and governance, workflow management, business glossary, and dependency mapping. By unifying data asset visibility across hybrid environments, RDI reduces operational risk and accelerates data modernization, compliance reporting, discovery, and rationalization initiatives.
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