Securden Password Vault is an enterprise-grade password management solution that allows you to securely store, organize, share, manage, and keep track of all human and machine identities. With a sleek access management system, Securden lets your IT teams share administrator credentials and effectively automate the management of privileged accounts in your organization. Securden seamlessly integrates with industry solutions like SIEM, SAML-based SSO, AD, and Azure AD among others to provide a smooth deployment in any organization. With Securden, organizations can rest easy as all their sensitive data is protected with strong encryption methods and supported by a robust high availability setup. Securden offers drilled-down granular access controls that allow users to grant access to accounts without revealing the underlying credentials in a just-in-time fashion. Securden Password Vault can be deployed both on-premise for self-hosting and on the cloud (SaaS).
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AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack.
Its Governed Control Model connects business meaning, data structures, transformation rules, dependencies, lineage and technical implementation in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design.
Generated outputs can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, supported Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns.
Because generated outputs are native Microsoft technology, no AnalyticsCreator runtime is required in production. Organisations retain ownership of the resulting implementation and can integrate generated assets into Git, Azure DevOps and CI/CD workflows.
Lineage, documentation and dependency information remain connected to the design, helping teams understand change impact before regenerating affected assets.
Design Intelligence extends this governed project context into AI-assisted data engineering by providing authorised AI tools and agents with structured access to metadata, lineage, dependencies and design rules.
Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery and repeatable data product engineering.
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AutoRABIT Vault
Vault provides comprehensive solutions for backing up and swiftly recovering essential data, including metadata, file attachments, chatter feeds, knowledge feeds, and all the necessary content to restore the full Salesforce experience. Additionally, Vault includes integrated archival features. Leveraging a scalable enterprise-level cloud infrastructure, AutoRABIT offers an economical archival solution. This platform empowers organizations to adhere to IT governance policies while fulfilling their data recovery requirements to ensure compliance with regulatory standards. Furthermore, for business continuity managers, Vault guarantees the quickest Recovery Time Objectives (RTOs), reinforcing its value in strategic planning. Ultimately, Vault stands as a vital resource for organizations seeking robust data protection and recovery strategies.
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biGENIUS
biGENIUS automates all phases of analytic data management solutions (e.g. data warehouses, data lakes and data marts. thereby allowing you to turn your data into a business as quickly and cost-effectively as possible. Your data analytics solutions will save you time, effort and money. Easy integration of new ideas and data into data analytics solutions. The metadata-driven approach allows you to take advantage of new technologies. Advancement of digitalization requires traditional data warehouses (DWH) as well as business intelligence systems to harness an increasing amount of data. Analytical data management is essential to support business decision making today. It must integrate new data sources, support new technologies, and deliver effective solutions faster than ever, ideally with limited resources.
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