About
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.
|
About
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
|
|||||
Platforms Supported
Windows
Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
|||||
Audience
Data Engineers, Data Architects, BI Engineers, Analytics Engineers, Heads of Data, BI Leads, Microsoft Data Platform Teams
|
Audience
Organizations that want all their data, analytics and AI on one unified data platform
|
|||||
Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
|
Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
|
|||||
API
Offers API
Not Supported
|
API
Offers API
Supported
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
PricingPricing for AnalyticsCreator depends on deployment size, number of environments, and user licenses required. Contact AnalyticsCreator’s sales team for a tailored quote based on your organization's data engineering needs.
Free Version
Not Supported
Free Trial
Supported
|
Pricing
No information available.
Free Version
Supported
Free Trial
Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Not Supported
|
Training
Documentation
Supported
Webinars
Supported
Live Online
Not Supported
In Person
Not Supported
|
|||||
Company InformationAnalyticsCreator
Germany
www.analyticscreator.com
|
Company InformationDatabricks
Founded: 2013
United States
databricks.com
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
||||||
CategoriesAnalyticsCreator is a metadata-driven design application for Microsoft data engineering teams. Engineers define structures, transformations, loading logic and dependencies centrally, then generate native SQL, SSIS, Azure Data Factory, Microsoft Fabric and Power BI assets. Repeatable patterns for ingestion, transformation, historisation, SCD processing and deployment reduce manual engineering while keeping lineage, documentation and change impact connected to the project design. AnalyticsCreator provides metadata-driven design and generation for data integration across Microsoft environments. Teams define sources, mappings, transformations, dependencies and loading rules centrally, then generate native SQL, SSIS and Azure Data Factory implementation assets. This helps standardise recurring integration patterns while preserving lineage, documentation and ownership of the resulting Microsoft technology. AnalyticsCreator helps Microsoft data teams design governed ingestion and transformation processes for data lake and analytical architectures. Metadata-defined sources, mappings, transformations and dependencies can be used to generate native Microsoft implementation assets for supported Azure and Microsoft Fabric scenarios. AnalyticsCreator provides the design and generation layer rather than acting as the data lake runtime itself. AnalyticsCreator captures lineage as part of the engineering model rather than as a separate documentation exercise. Sources, tables, transformations, references and downstream analytical structures remain connected through project metadata, allowing teams to trace data movement and understand dependencies across the solution. Lineage can also support impact analysis when models or transformations change. AnalyticsCreator helps Microsoft data teams manage the design and evolution of structured data estates through a central metadata model. Sources, schemas, tables, relationships, transformations and dependencies remain connected to the generated implementation. This provides greater visibility into project structure, lineage and change impact while helping teams apply consistent modelling and engineering standards. AnalyticsCreator provides model-driven design for data warehouses and data products across the Microsoft data stack. Teams can define dimensional, 3NF and hybrid models together with relationships, transformations, historisation rules and dependencies. The approved model then drives generation of native SQL, pipelines, documentation, semantic models and deployment artefacts, keeping design and implementation aligned as the project changes. Accelerate the development of your data warehouses by automating complex model designs, including dimensional, data mart, and data vault architectures. AnalyticsCreator enhances scalability for large data environments and ensures better governance through its automated features. Generate optimized code for leading platforms such as Snowflake, Azure Synapse, and MS Fabric. Improve data quality, consistency, and governance throughout the data warehouse lifecycle with automated tools for schema evolution and historical data handling. Enhance collaboration with version control and automated documentation, enabling seamless teamwork and rapid iteration. Leverage AnalyticsCreator to meet the demands of modern data warehouse development with CI/CD and agile workflows, reducing development cycles significantly. AnalyticsCreator provides metadata-driven design and generation for ETL and ELT processes across the Microsoft data stack. Data teams define mappings, transformations, loading logic, dependencies and historisation centrally, then generate native SQL procedures, SSIS packages and Azure Data Factory pipelines. Reusable patterns support ingestion, delta loading, SCD processing and repeatable transformations without introducing a proprietary production runtime. Metadata is the foundation of AnalyticsCreator. The central project model connects data structures, transformations, business rules, relationships, dependencies, lineage, documentation and generated implementation. This allows data teams to use metadata not only to describe a solution, but to actively drive generation, change analysis and controlled delivery across Microsoft data projects. AnalyticsCreator can generate governed analytical and semantic models for Microsoft Power BI and Analysis Services from the same metadata used to design the underlying data warehouse. Relationships, dimensions and model structures remain connected to the wider project design, helping teams keep analytical models aligned with upstream data structures and dependencies. |
Categories |
|||||
Data Lineage Features
Database Change Impact Analysis
Supported
Filter Lineage Links
Supported
Implicit Connection Discovery
Supported
Lineage Object Filtering
Supported
Object Lineage Tracing
Supported
Point-in-Time Visibility
Supported
User/Client/Target Connection Visibility
Not Supported
Visual & Text Lineage View
Supported
Data Management Features
Customer Data
Supported
Data Analysis
Supported
Data Capture
Not Supported
Data Integration
Supported
Data Migration
Supported
Data Quality Control
Supported
Data Security
Supported
Information Governance
Supported
Master Data Management
Supported
Match & Merge
Not Supported
Data Warehouse Features
Ad hoc Query
Supported
Analytics
Supported
Data Integration
Supported
Data Migration
Supported
Data Quality Control
Not Supported
ETL - Extract / Transfer / Load
Supported
In-Memory Processing
Not Supported
Match & Merge
Not Supported
ETL Features
Data Analysis
Supported
Data Filtering
Supported
Data Quality Control
Not Supported
Job Scheduling
Not Supported
Match & Merge
Supported
Metadata Management
Supported
Non-Relational Transformations
Supported
Version Control
Supported
|
Data Lineage Features
Database Change Impact Analysis
Supported
Filter Lineage Links
Supported
Implicit Connection Discovery
Supported
Lineage Object Filtering
Supported
Object Lineage Tracing
Supported
Point-in-Time Visibility
Supported
User/Client/Target Connection Visibility
Supported
Visual & Text Lineage View
Supported
Data Management Features
Customer Data
Supported
Data Analysis
Supported
Data Capture
Supported
Data Integration
Supported
Data Migration
Supported
Data Quality Control
Supported
Data Security
Supported
Information Governance
Supported
Master Data Management
Supported
Match & Merge
Supported
Data Warehouse Features
Ad hoc Query
Supported
Analytics
Supported
Data Integration
Supported
Data Migration
Supported
Data Quality Control
Supported
ETL - Extract / Transfer / Load
Supported
In-Memory Processing
Supported
Match & Merge
Supported
ETL Features
Data Analysis
Supported
Data Filtering
Supported
Data Quality Control
Supported
Job Scheduling
Supported
Match & Merge
Supported
Metadata Management
Supported
Non-Relational Transformations
Supported
Version Control
Supported
Artificial Intelligence Features
Chatbot
Not Supported
For eCommerce
Supported
For Healthcare
Supported
For Sales
Supported
Image Recognition
Not Supported
Machine Learning
Supported
Multi-Language
Supported
Natural Language Processing
Supported
Predictive Analytics
Supported
Process/Workflow Automation
Supported
Rules-Based Automation
Supported
Virtual Personal Assistant (VPA)
Not Supported
Big Data Features
Collaboration
Supported
Data Blends
Supported
Data Cleansing
Supported
Data Mining
Supported
Data Visualization
Supported
Data Warehousing
Supported
High Volume Processing
Supported
No-Code Sandbox
Supported
Predictive Analytics
Supported
Templates
Supported
Business Intelligence Features
Ad Hoc Reports
Supported
Benchmarking
Supported
Budgeting & Forecasting
Supported
Dashboard
Supported
Data Analysis
Supported
Key Performance Indicators
Supported
Natural Language Generation (NLG)
Supported
Performance Metrics
Supported
Predictive Analytics
Supported
Profitability Analysis
Supported
Strategic Planning
Supported
Trend / Problem Indicators
Supported
Visual Analytics
Supported
Dashboard Features
Annotations
Supported
Data Source Integrations
Supported
Functions / Calculations
Supported
Interactive
Supported
KPIs
Supported
OLAP
Supported
Private Dashboards
Supported
Public Dashboards
Supported
Scorecards
Supported
Themes
Supported
Visual Analytics
Supported
Widgets
Supported
Data Analysis Features
Data Discovery
Supported
Data Visualization
Supported
High Volume Processing
Supported
Predictive Analytics
Supported
Regression Analysis
Supported
Sentiment Analysis
Supported
Statistical Modeling
Supported
Text Analytics
Supported
Data Fabric Features
Data Access Management
Supported
Data Analytics
Supported
Data Collaboration
Supported
Data Lineage Tools
Supported
Data Networking / Connecting
Not Supported
Metadata Functionality
Not Supported
No Data Redundancy
Not Supported
Persistent Data Management
Supported
Data Governance Features
Access Control
Supported
Data Discovery
Supported
Data Mapping
Supported
Data Profiling
Supported
Deletion Management
Supported
Email Management
Not Supported
Policy Management
Not Supported
Process Management
Not Supported
Roles Management
Supported
Storage Management
Supported
Data Science Features
Access Control
Supported
Advanced Modeling
Supported
Audit Logs
Supported
Data Discovery
Supported
Data Ingestion
Supported
Data Preparation
Supported
Data Visualization
Supported
Model Deployment
Supported
Reports
Supported
Data Visualization Features
Analytics
Supported
Content Management
Not Supported
Dashboard Creation
Supported
Filtered Views
Supported
OLAP
Supported
Relational Display
Supported
Simulation Models
Supported
Visual Discovery
Supported
Machine Learning Features
Deep Learning
Supported
ML Algorithm Library
Supported
Model Training
Supported
Natural Language Processing (NLP)
Supported
Predictive Modeling
Supported
Statistical / Mathematical Tools
Supported
Templates
Supported
Visualization
Supported
|
|||||
Integrations
Azure Databricks
Supported
DuckDB
Supported
Google Cloud BigQuery
Supported
Microsoft Azure
Supported
SQL
Supported
Adobe Experience Platform
Not Supported
Astrato
Not Supported
Azure Service Fabric
Supported
Connecty AI
Not Supported
Decentriq
Not Supported
|
Integrations
Azure Databricks
Supported
DuckDB
Supported
Google Cloud BigQuery
Supported
Microsoft Azure
Supported
SQL
Supported
Adobe Experience Platform
Supported
Astrato
Supported
Azure Service Fabric
Not Supported
Connecty AI
Supported
Decentriq
Supported
|
|||||
|
|
