It’s all about getting more work done. Today.
I believe in getting projects done in small iterations – step by step – minimizing your risk and guaranteeing growth for you and your stakeholders.
- You must be able to predict what the business needs from your data warehouse solution at least 6 months in advance.
- You have to accept that modifying a data warehouse project is a long, tiring, and expensive process.
- You must base business decisions on assumptions rather than facts. From our experience, this creates an obsolete solution stakeholders will hate.
The advantages of a business solution built on a Data Warehouse Automation platform:
- Delivers results and success to stakeholders from day 1.
- Is easy to maintain and modify as your business evolves.
- Provides real-time figures that are accurate – every time.
Do you need new current figures for a board or executive meeting? They are easy to come by with Data Warehouse Automation. Analysis and reporting becomes a process of continuous refinement to fit your ever-changing business. Take a minute to watch our video – you might just recognize yourself in it.
Data Warehouse Automation (DWA)?
There is really not that much to it. Data Warehouse Automation – or simply “DWA” – gives you the advantages of data warehousing and adds a range of automation features that, in the words of The Data Warehouse Institute’s Dave Wells, makes it better, faster and cheaper.
Just like automation has helped manufacturers increase productivity, achieve better and more consistent quality and reduce the manual effort, DWA improves data warehousing.
A high performance and flexible data warehouse is important because the data warehouse is the heart of modern enterprise business intelligence solutions. Users will quickly realize the benefits of implementing a data warehouse with Data Warehouse Automation: Less waiting, better reports, faster implementation of their requests and much more.
The benefits of a Data Warehouse are many:
- Single common data model
- Governed data discovery
- Integrate data from multiple source systems
- Congregate data from multiple sources
- Improve data quality
- Maintain data history
- Optimized data model for query and analysis
- Independent security model
Definition: A data warehouse is a copy of transaction data specifically structured for query and analysis.
Data Warehouse Automation
With DWA, you get the benefits of a data warehouse plus:
- Source data exploration
- Warehouse data models
- ETL generation
- Test automation
- Metadata management
- Managed deployment
- Change impact analysis
- Easier maintainence and modification
Definition: Data Warehouse Automation uses technology to gain efficiencies and improve effectiveness in data warehousing processes.
You Are not Alone
We have been doing what is now known as Data Warehouse Automation in more than 10 years and have helped hundreds of companies. They got faster, better and cheaper data warehouse solutions to power their business intelligence needs and give them an edge on the marketplace.
You can read some of our customers stories here. We dare say: If you choose TimeXtender, you are in good company.