AnalyticsCreator
Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs.
Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding.
Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow.
Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives.
By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.
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dbt
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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Gearset
Gearset is a full‑featured Salesforce DevOps solution built for the enterprise, giving teams the tools to adopt best practices across every stage of the DevOps lifecycle. From metadata and CPQ deployments to CI/CD, testing, code analysis, sandbox seeding, backups, archiving, and observability, Gearset gives teams unmatched insight and control over their Salesforce workflows. Over 3,000 organizations — including names like McKesson and IBM — rely on Gearset to deliver with security and scale in mind.
With advanced governance, detailed audit trails, SOX/ISO/HIPAA support, multi‑team pipelines, integrated security checks, and adherence to ISO 27001, SOC 2, GDPR, CCPA/CPRA, and HIPAA, Gearset combines enterprise‑ready compliance with rapid onboarding and an intuitive interface — all in one platform. Leading firms in finance, healthcare, and tech trust Gearset to power their DevOps initiatives without adding complexity.
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OneTrust Privacy Automation
Transparency, choice and control are key to trust. Organizations have the opportunity to leverage these moments to build trust, and provide more valuable experiences. People expect greater control over their data. We offer privacy and data governance automation to help organizations better understand and comply with regulatory requirements. We also operationalize risk mitigation to ensure transparency and choice for individuals. Your organization will be able to achieve data privacy compliance quicker and build trust. Our platform helps to break down silos between processes, workflows, teams, and people to operationalize regulatory compliance. It also allows for trusted data use. Building proactive privacy programs that are rooted in global best practice and not just reacting to individual regulations is possible. To drive mitigation and risk-based decision-making, gain visibility into unknown risks. Respect individual choice and integrate privacy and security by default in the data lifecycle.
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