Secure Eraser: Secure Data Deletion, Shredders Your Files & Folders.
Just because it has been removed from your hard drive doesn't mean that it is gone forever. Anyone can restore the information as long as it was not overwritten. It becomes more difficult if the computer has been resold, or given away.
Secure Eraser employs the most well-known method of data disposal. It overwrites sensitive information so that it cannot be recovered even with specialized software. Our award-winning solutions for permanently destroying data eliminate cross-references that may leave traces of deleted files within the allocation table of your hard disk.
This Windows software is easy to use and can overwrite sensitive data up to 35 times, regardless of whether they're files, folders or drives, recycle bins, or traces of surfing. You can also delete files that you have already deleted but not for good.
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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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OLake Go
OLake Go is a versatile open-source platform designed for the replication of operational data into data lakehouse environments. It provides connectivity to a wide array of databases, including PostgreSQL, MySQL, MongoDB, Oracle Database, SQL Server, and IBM Db2, along with integration capabilities for Apache Kafka and object storage solutions. The platform enables both full-load and incremental data ingestion, featuring change data capture for various supported connectors, and efficiently writes the ingested data to Apache Iceberg tables and Parquet files through compatible catalogs and storage targets. Data engineers and analytics teams can initiate ingestion tasks seamlessly via the OLake user interface or through command-line operations, and they have the flexibility to deploy the software within their own infrastructure to create synchronized datasets for further querying and analytics. With Docker-based deployment options and connector-specific configurations, teams can effectively manage their source connections, data destinations, and the overall data movement process in a self-hosted setting, thereby enhancing their operational efficiency. This empowers organizations to leverage their data more strategically while ensuring streamlined access to critical insights.
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IOMETE
IOMETE is a sovereign data lakehouse platform built to support modern data analytics and AI-driven workloads at enterprise scale. The platform allows organizations to store, manage, and process massive datasets within infrastructure they fully control. Unlike traditional cloud-only solutions, IOMETE can be deployed on-premises, in private clouds, public clouds, or hybrid environments. This flexible architecture helps organizations maintain full ownership of their data while avoiding vendor lock-in. The platform integrates data lakehouse capabilities with tools such as Spark processing, SQL query editors, Jupyter notebooks, and orchestration engines. These components allow data engineers, analysts, and data scientists to build pipelines, analyze datasets, and develop machine learning models in one environment. IOMETE also provides a centralized data catalog to help teams discover, manage, and understand their data assets. Advanced security controls allow organizations to manage access permissions across users, teams, and datasets with detailed governance rules. By reducing reliance on SaaS-based infrastructure, the platform can also help organizations optimize storage and compute costs. Overall, IOMETE delivers a flexible and secure data platform built specifically for the growing data demands of the AI era.
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