1. Development Automation WhereScape RED
Data Warehouse
Development Automation
WhereScape RED
How data warehouse automation reduces the manual effort, time and cost of building and maintaining a data warehouse.

2. Data Warehouse Automation
Automate the “donkey work”
Keep developers solving the hard problems not the boring ones
A lot of manual / boring work in building the data warehouse
Not processing performance – addresses Developer performance

3. Data Warehouse Automation
Model Automation
Rules based approach to design
Input: source model
Output: target model
Development Automation
Meta data driven development
Code generation
Table / Indexes
Documentation
2 Levels of automation – addressed by WS Software

4. Demonstration 3D Showing: Reverse engineer Profile Test data Derive
Not :
Documentation
3D-RED Integration
Video on the website (

5. WhereScape RED A data warehouse automation IDE Results :
develop, refine, document, promote, operate, support and enhance
Results :
Saves time & money
Enables agile development
Iterations
Collaboration
Reduces risk
High quality development
Promotes in-house development
Lower TCO – manages complete lifecycle
Addresses the full lifecycle of the data warehouse

6. DW development Automation
Built in management framework
Fast development speed
Metadata
Metadata driven tool – drives generation of DDL, code, Operations, documentation and deployment.
Leverage skills
Consistency
Best Practices
Documentation
Scheduler
Low cost of change

7. An Agile platform Automation enables agile projects
Build deployable data marts (or parts) rapidly and get in front of users - Automation
data and requirements exploration
prototype and iterate
workshops
Design Approach – requires iterations:
Data driven design
Model driven design
Automation enables agile projects

8. Agile Processing Architecture
Sales
Data xforms Business xforms
Financials
A-TV-DS
LDD
JMS
Some parts of the data warehouse processing architecture are more agile than others.
Assets
Static
Agile
Sources Foundation Data Marts

9. Demonstration RED Showing: Build a data mart from scratch
Documentation
Workflow
OLAP Cubes
Not :
Complexity
Multi-step operations
Data volumes
(there’s just not enough time)
Video on the website (

10. Questions ?