AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack.
At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design.
Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, 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.
Changes made in the model can be propagated across dependent project assets, while lineage, documentation and impact analysis remain connected to the underlying design. This helps teams reduce repetitive engineering work, standardise delivery and understand the effect of change before regenerating affected assets.
AnalyticsCreator generates native Microsoft technology rather than requiring a proprietary runtime. Organisations retain ownership of the resulting implementation and can integrate generated assets into existing Git, Azure DevOps and CI/CD processes.
Design Intelligence extends this governed project context into AI-assisted data engineering by giving authorised AI tools and agents 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, SAP-to-Microsoft analytics architectures and repeatable data product engineering.
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Empower Your Current Team to Achieve Enterprise-Level Security
An all-in-one solution with SIEM, endpoint visibility, 24/7 monitoring, and automated response to reduce complexity, increase visibility and speed up time to respond.
We handle the security heavy lifting, so you get time back in your day. With out-of-the-box detections, pre-filtered alerts, and response playbooks, IT teams can achieve real security value with Blumira.
Quick Deployment, Immediate Results: Integrates with your tech stack and fully deploy, with no warm-up period, in hours
All-You-Can-Eat Data Ingest: Predictable pricing and with unlimited data logging for full-lifecycle detection
Compliance Made Easy: 1 year data retention included, pre-built reports, and 24/7 automated monitoring
99.7% CSAT Support: Solution Architects for product support, the Incident Detection and Response Team creating new detections, and 24/7 SecOps support
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Data Lakes on AWS
Many Amazon Web Services (AWS) customers require a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is a new and increasingly popular way to store and analyze data because it allows companies to manage multiple data types from a wide variety of sources, and store this data, structured and unstructured, in a centralized repository. The AWS Cloud provides many of the building blocks required to help customers implement a secure, flexible, and cost-effective data lake. These include AWS managed services that help ingest, store, find, process, and analyze both structured and unstructured data. To support our customers as they build data lakes, AWS offers the data lake solution, which is an automated reference implementation that deploys a highly available, cost-effective data lake architecture on the AWS Cloud along with a user-friendly console for searching and requesting datasets.
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