AnalyticsCreator Reviews

AnalyticsCreator

4.6 out of 5 stars
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Average Ratings 46 Ratings

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Description

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.

Description

AtScale streamlines and speeds up business intelligence processes, leading to quicker insights, improved decision-making, and enhanced returns on your cloud analytics investments. It removes the need for tedious data engineering tasks, such as gathering, maintaining, and preparing data for analysis. By centralizing business definitions, AtScale ensures that KPI reporting remains consistent across various BI tools. The platform not only accelerates the time it takes to gain insights from data but also optimizes the management of cloud computing expenses. Additionally, it allows organizations to utilize their existing data security protocols for analytics, regardless of where the data is stored. AtScale’s Insights workbooks and models enable users to conduct Cloud OLAP multidimensional analysis on datasets sourced from numerous providers without the requirement for data preparation or engineering. With user-friendly built-in dimensions and measures, businesses can swiftly extract valuable insights that inform their strategic decisions, enhancing their overall operational efficiency. This capability empowers teams to focus on analysis rather than data handling, leading to sustained growth and innovation.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Tableau Yes 
Azure Analysis Services Yes 
Azure Database for PostgreSQL Yes 
Azure DevOps Yes 
Azure SQL Database Yes 
Azure Service Fabric Yes 
Cloudera No 
DuckDB Yes 
Microsoft Dynamics 365 Business Central Yes 
Microsoft Fabric Yes 
Microsoft Power Query No 
PostgreSQL Yes 
Qlik Sense Yes 
SAP Business One Yes 
SAP ERP Yes 
SQL Yes 
SQL Server Yes 
SQL Server on Azure Virtual Machines Yes 
SSAS Yes 
SSIS Yes 

Integrations

Tableau Yes 
Azure Analysis Services No 
Azure Database for PostgreSQL No 
Azure DevOps No 
Azure SQL Database No 
Azure Service Fabric No 
Cloudera Yes 
DuckDB No 
Microsoft Dynamics 365 Business Central No 
Microsoft Fabric No 
Microsoft Power Query Yes 
PostgreSQL No 
Qlik Sense No 
SAP Business One No 
SAP ERP No 
SQL No 
SQL Server No 
SQL Server on Azure Virtual Machines No 
SSAS No 
SSIS No 

Pricing Details

Pricing 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 Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

AnalyticsCreator

Country

Germany

Website

www.analyticscreator.com

Vendor Details

Company Name

AtScale

Founded

2013

Country

United States

Website

www.atscale.com

Product Features

Data Engineering

AnalyticsCreator is an innovative, model-based data engineering tool designed specifically for teams utilizing Microsoft SQL Server, Azure, and Microsoft Fabric. Data engineers leverage source metadata along with smart wizards to construct both business and technical models, establish data transformations, define historisation rules, and outline processing dependencies. As the model evolves, the associated implementation code adapts accordingly, remaining accessible throughout the development process. The tool automatically produces native database structures, SSIS packages, Azure Data Factory components, as well as artifacts for Fabric pipelines, deployment packages, and Power BI semantic-model definitions, all derived from the managed project. With integrated testing capabilities and project versioning, AnalyticsCreator ensures that changes are well-regulated and deliveries are consistent and repeatable. The generated implementations seamlessly function within the client's Microsoft ecosystem, eliminating the need for an AnalyticsCreator production runtime.

Data Integration

AnalyticsCreator facilitates a metadata-driven approach to data integration tailored for Microsoft data warehouse and analytics ecosystems. The process begins with the importation of source-system metadata into a managed project environment, where developers establish relationships, mappings, ingestion protocols, transformations, historization, and processing dependencies. AnalyticsCreator then generates the necessary implementation logic, producing SQL processing scripts, SSIS packages, Azure Data Factory pipelines, and orchestration artifacts for Microsoft Fabric. In instances where source structures undergo modifications, metadata refresh and connected lineage aid engineers in pinpointing impacted areas, enabling them to update the model and regenerate the corresponding outputs efficiently. Data movement and processing occur through the designated target technologies, while AnalyticsCreator maintains the context for design, generation, and change management throughout the process.

Data Lake

AnalyticsCreator is designed to work seamlessly with Microsoft Fabric data architectures, utilizing OneLake as its core storage solution. Its main function is to create managed data warehouse models, define transformation logic, establish processing dependencies, and build analytical frameworks. It subsequently produces native artifacts for Microsoft Fabric Warehouse and Data Factory pipelines. The initiative keeps track of source metadata, relationships, transformations, and analytical definitions, allowing the warehouse design to adapt over time while maintaining its business and technical integrity. Microsoft Fabric offers OneLake for storage, along with services for warehouse execution and pipeline runtime. In contrast, AnalyticsCreator focuses on model-driven design and generation features, rather than serving as an independent data lake storage system or a Spark processing engine.

Data Lineage

AnalyticsCreator offers a comprehensive overview of data lineage and dependencies by utilizing metadata within the data warehouse and analytical frameworks of its projects. It maintains a connection between source structures, business definitions, mappings, transformations, relationships, and semantic-model definitions, enabling teams to trace the flow of data from its origins to analytical outputs clearly. Whenever there is an update to the source metadata, the impacted areas within the project lineage are marked for evaluation, facilitating change-impact assessments prior to any alterations in transformations, warehouse configurations, or downstream analytical models. The platform includes project versioning, automatically generated documentation, and documented test results, which serve as evidence for regulated changes. Unlike typical runtime monitoring, the lineage represents the documented project design and its established scope.

Database Change Impact Analysis Yes 
Filter Lineage Links Yes 
Implicit Connection Discovery Yes 
Lineage Object Filtering Yes 
Object Lineage Tracing Yes 
Point-in-Time Visibility Yes 
User/Client/Target Connection Visibility No 
Visual & Text Lineage View Yes 

Data Management

AnalyticsCreator is an innovative application designed for model-driven design and automation tailored for Microsoft data ecosystems. It seamlessly integrates business definitions, source metadata, logical and physical models, transformation rules, implementation code, dependencies, and documentation within a well-governed project framework. This interconnected approach empowers organizations to maintain a comprehensive understanding of their data architecture, assess the ramifications of changes, and lessen their dependency on individual developers or fragmented documentation. With features such as project versioning, metadata-driven lineage tracking, and integrated testing, AnalyticsCreator facilitates controlled development and ongoing maintenance. The platform produces native artifacts for data warehouses, pipelines, and analytics that are compatible with various Microsoft technologies, ensuring that the final solutions function autonomously within the designated environment. The primary emphasis of AnalyticsCreator lies in the governance and engineering of data analytics solutions, distinguishing itself from traditional operational master data management.

Customer Data Yes 
Data Analysis Yes 
Data Capture No 
Data Integration Yes 
Data Migration Yes 
Data Quality Control Yes 
Data Security Yes 
Information Governance Yes 
Master Data Management Yes 
Match & Merge No 

Data Modeling

AnalyticsCreator facilitates a model-first approach to creating business, logical, physical, and semantic data models tailored for Microsoft analytics ecosystems. With the assistance of smart wizards, it leverages source metadata and specific project needs to construct dimensional, normalized, hybrid, and layered data warehouse architectures. Teams can effectively model facts, dimensions, relationships, business keys, transformations, and historization protocols. In contrast to traditional modeling tools that merely create diagrams, AnalyticsCreator simultaneously generates the implementation code that corresponds to the model, ensuring visibility and clarity throughout the development process. This governed project framework intertwines business semantics with technical structures, transformation logic, lineage tracking, and documentation. Building on this robust foundation, AnalyticsCreator produces compatible artifacts for SQL Server, Azure, Microsoft Fabric, and Power BI. Start with the model. Then move to generation.

Data Warehouse

AnalyticsCreator facilitates a model-driven approach to developing and automating data warehouses specifically for Microsoft SQL Server, Azure SQL, and compatible Microsoft Fabric Warehouse platforms. Using smart wizards, the tool leverages source metadata and design choices to create customized warehouse models tailored for specific projects. Throughout the development process, core components such as business definitions, relationships, transformation logic, and implementation code remain interconnected. The platform produces native SQL structures, views, stored procedures, historisation, and snapshot logic, along with DACPAC deployment packages and suitable loading and orchestration artifacts. Additionally, built-in testing functionality allows for a comparison between actual processing outcomes and predefined expectations, ensuring thorough validation prior to deployment. The solutions generated can operate seamlessly within the chosen Microsoft environment without the necessity of an AnalyticsCreator production runtime.

Ad hoc Query Yes 
Analytics Yes 
Data Integration Yes 
Data Migration Yes 
Data Quality Control No 
ETL - Extract / Transfer / Load Yes 
In-Memory Processing No 
Match & Merge No 

ETL

AnalyticsCreator specializes in the design and automated creation of ETL and ELT workflows tailored for Microsoft data warehouse infrastructures, utilizing a metadata-driven approach. Developers are able to outline key components such as data ingestion, transformation, historical data management, persistence, and processing dependencies within a controlled project environment. As the model evolves, the generated SQL and processing logic are developed in tandem and can be easily reviewed. The platform produces compatible SQL Server Integration Services (SSIS) packages, Azure Data Factory pipelines, and artifacts for Microsoft Fabric, along with the necessary database processing code. Built-in testing capabilities allow for consistent validation against criteria set by developers, ensuring that inputs and expected outputs are met. The generated workloads run directly within the designated Microsoft environment, rather than relying on a proprietary runtime from AnalyticsCreator.

Data Analysis Yes 
Data Filtering Yes 
Data Quality Control No 
Job Scheduling No 
Match & Merge Yes 
Metadata Management Yes 
Non-Relational Transformations Yes 
Version Control Yes 

Metadata Management

AnalyticsCreator is responsible for managing the interconnected metadata essential for the creation, advancement, and optimization of Microsoft data analytics solutions. Within a governed project, it oversees source definitions, business concepts, models, relationships, transformation rules, implementation code, dependencies, and deployment configurations. This metadata facilitates model-driven development, automated documentation creation, lineage tracking, impact assessments of changes, project version management, and native implementation generation. The AnalyticsCreator Design Intelligence further enhances this methodology by granting authorized MCP-compatible AI agents access to the relevant saved-project context for analysis, explanation, and technical recommendations. The available context varies based on the project's scope and coverage, while any proposed modifications are subject to human oversight and organizational protocols.

Semantic Layer

AnalyticsCreator bridges the gap between the development of semantic models and the structured design of a governed data warehouse, enabling teams to uphold uniform analytical frameworks throughout Microsoft data ecosystems. In this unified project environment, elements such as facts, dimensions, relationships, metrics, and hierarchies are established alongside the relevant source metadata and transformation logic. The tool produces compatible semantic model artifacts for Power BI, including outputs in Power BI Project (PBIP) format utilizing native Tabular Model Definition Language (TMDL). These textual definitions can be easily reviewed, versioned, and integrated into established Git and CI/CD pipelines. While Power BI takes charge of visualizations, workspace settings, and analytical processing, AnalyticsCreator lays the groundwork for designing and generating the semantic model.

Product Features

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

Data Fabric

Data Access Management No 
Data Analytics No 
Data Collaboration No 
Data Lineage Tools No 
Data Networking / Connecting No 
Metadata Functionality No 
No Data Redundancy No 
Persistent Data Management No 

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

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