Unterfeldstrasse 18, 8050 Zurich
+41 32 511 27 89

Features Details

Data Warehouse Automation
Automatically start a new environment within minutes ok
Automatically convert data models into working ELT code ok
Automatically convert data models into operational jobs ok
Built for Agile and Devops: develop, retest and deploy new features within a day ok
Extend jobs automatically if new elements are added to the data model ok
Enable automated testing ok
Self-generated Documentation of actual Solution ok
Deployment Server
On Premise ok
Private Cloud ok
SAAS ok
Desktop: Windows, Mac, Linux ok
Deployment Client
Runs on any platform running Chrome or Chromium ok
Windows all versions ok
Mac OS X all versions ok
Linux all distirubtions ok

Extract, Transform, Load (ETL / ELT)
Built in ELT Engine ok
Using the full power of the underlaying data base ok
Automatical parallelization of work loads ok
Any Data Transformation, Text parsing, Calculations based on common SQL (no new abilities needed) ok
Automatic generation of slowly changing dimensions ok
Metadata-Storage
Direct storage of metadata in database-objects ok
No need for separate Metadata Repository ok
Version Control
Every change is tracked and can be restored ok
A complete protocol is provided with timestamp and user information ok
Included Software
Modeling Tool ok
ETL / ELT Tool ok
SQL Editor ok
Data Profiling Tool ok
Interactive Documentation ok
Operations including Scheduler ok
Database in some editions ok

Generel Staging Features
Load Files, JDBC Databases and Rest Interface ok
Preview actual Source Data ok
Add hashes in transfer process ok
Delta and Full loads ok
Persistent staging ok
Snapshot all incoming rows ok
Non JDBC Sources
Load from CSV, TSV and other Delimiter separated Files ok
Load fixed width files ok
Load from MS Access and MS Excel Files ok
Load from REST Services (JSON, XML) ok
Load from Webpages ok
Load Cobol Copy Books with 3th party driver

JDBC Sources (extract)
Amazon Aurora ok
Amazon RDS ok
Amazon Redshift ok
Apache Derby ok
Apache Spark ok
IBM DB2 ok
EXASOL ok
eXist-db ok
Firebird ok
Google Cloud ok
Greenplum ok
H2 ok
HSQL DB ok
Informix ok
AmazonRDS ok
Ingres ok
InterBase ok
JavaDB ok
MariaDB ok
MaxDB ok
Microsoft SQL Server ok
MySQL ok
Netezza ok
Oracle ok
ParAccel ok
PostgreSQL / Postgres ok
PostgresPlus ok
SAP Hana ok
SAS ok
SQLite ok
Sybase ok
Sybase IQ ok
Teradata ok
VectorWise ok
Vertica ok
Windows Azure ok
… all other JDBC Data Sources ok

Modelling
Conceptuel Modelling ok
Logical Modelling integrated with Conceptual Modeling ok
Visually develop logical model (for business analysts without IT skill) ok
Automatic Technical Implementation from Logical Model ok
Data Vault Specific
Visually implement Hubs, Links and Satellites loads (matching ELT loads are created in real time) ok
Visually implement Hubs, Links and Satellites loads (matching ELT loads are created in real time) ok
Wizard to create Hub and Satellite including the loads by only selecting the Business Key ok
Automatic Creation and Evaluation of Tracking Satellites and Link Tracking Satellites ok

Technical Implementation
Load data with one click while modelling and get instant feed back ok
Tables, Indexes and Foreign Keys are created automatically ok
Automatic ELT Loads for SCD Type 0,1,2 ok
Fully historized loads are created ok
Loads are fully audible ok
Browsing
Browse through actual data model ok
Search model by hubs, subject areas or systems ok
Graphically indicate data sources in the model ok

Business Object
Automatically denormalize business objects (facts and dimensions) ok
Automatic grain checks ok
Visual consolidation of data ok
Visual harmonization of column names ok
Taking care of all necessary join operations without writing one line of code ok

Business Rules
Add any business rule you want ok
Full power of SQL ok
Editor with autocomplete support ok
Build multi layer rules ok
Access all core layer objects ok

Advanced Features
Preview output and make it immediatelly available to recipients like reporting tools ok
Prepare complex rules for materialization in the Business Vault ok
Add comments which are automatically transferred into the documentation ok
Define Error Rulesets to assure Data quality ok

Error Mart / Automated Testing
Automated views for missing relations and values ok
Create custom rules to be monitored ok
Based on single rows or sets ok

Access Layer
Automatically merge data from different sources ok
Define priority on row and column level ok
Reload free by providing a virtual layer ok

Data Lineage
Show “Where-Used” Data Lineage from Source to Target ok
Lineage and Impact Analysis ok
Browse and Filter your Data Lineage ok
Access Data Lineage with your favorite Reporting Tool or integrate views in your corporate Wiki ok

Data Profiling / Instant Insights
Prepared views to identify Business Key ok
Create Simple Charts ok
Analyze Data with Heatmaps and Treecharts ok
Access all DWH Layers to verify your data ok
Access the metrics vault to analyze the load performance ok

Operations
Monitor current state of created loads ok
Automatically created Jobs for Continuous Integration ok
Customize automatically created Jobs ok
Add individual jobs ok
Add custom loading schedules ok
Easily define job dependencies ok
Start jobs via Rest API with your Enterprise Scheduling Tool (Enterprise Edition) ok
Automatic parallelization of loading processes ok
Trigger SQL Jobs to push the data to files or target databases ok

Data Vault Modeling
Data Vault using Hash Key ok
Hubs ok
Links ok
Satellites (automatic and manual) ok
Tracking Satellites and Link-Satellites created automatically ok
Data Vault extended modeling
Automatic Business Vault Loads ok
Denormalization to Dimensional Model ok
Bridge Tables ok
Point in Time Tables (PIT) ok

Technical Elements
Hashes automatically added to ETL Flows ok
All loads parallelized automatically ok
Tracking Satellites loaded and evaluated automatically ok
Full SCD Type 2 History created automatically ok
Full SCD Type 0 and 1 views available out of the box ok

Built for Agile
Start small – grow big ok
Group changes by stories ok
Start model from different starting points and connect them later ok
Loose coupling by Data Vault Modeling ok
Data model supports partial roll outs ok
Data model limits retesting to a minimum ok
Support for automated testing ok

Continuous Integration and DevOps
Master jobs are created automatically ok
Master jobs extend if new elements are modeled ok
Test new elements automatically on a defined schedule (nightly builds or continuous integration) ok
Automated roll out package creation ok
Data model supports partial roll outs ok
Data model limits retesting to a minimum ok
Support for automated testing ok

Deployment and Multitenancy SMB Enterprise
Deploy new objects automatically ok ok
Deploy changed objects automatically ok ok
Return to previous versions of the model ok ok
Simplified Deployment process directly from one environment to the other ok ok
Enterprise Deployment process using GIT Workflow  ok
Deploy packages to different target environments / Multitenancy Support ok

Real Time Support SMB Enterprise
Use continous mini batches for single entities, complete systems or the full data model ok ok
Load data staged by other applications as they arrive ok
Offers an API to push single records into the model ok

Deployment and Multitenancy SMB Enterprise
Built in Database (based on Postgres) ok ok
Microsoft SQL Standard Edition 3.1 (April 2017) 3.1 (April 2017)
EXASOL 3.2
Microsoft SQL Enterprise Edition 3.1 (April 2017)
Oracle (12.2) 3.3