BI Ready

BI Ready®
Data Warehouse Automation

BIReady Overview

BIReady is the first model driven product that is reshaping the data warehouse market, due to its speed of development and its hybrid approach to automatically generating all the data warehouse, data mart and ETL Code

Used by data warehouse professionals, data architects, data modellers and developers for business users.

Organizations of all sizes can use BIReady to quickly and easily design the data warehouse from a CA ERwin data source model and generate robust code to populate it.

Traditional data warehouse projects spend 80% of the project getting the data into a workable format for reporting., By contrast BIReady solves this problem by generating a targeted data warehouse design and code to populate it in minutesĀ 

BIReady handles the lifecycle of a Data Warehouse, from mapping to source systems, generation of ETL, designing and generating and loading the normalized Data Warehouse and star-schema Data Marts, maintenance of history and surrogate keys, change-data capture and logging.

These processes are scalable, stable and automated. Using BIReady, your Data Warehouse is taken care of, surfacing the data you need, and supporting your favourite BI reporting tools.


                          Before BI Ready                     After BI Ready

The Technology

Traditional Data Warehouses are brittle, hand-coded, complex and expensive. BIReady doesn't get rid of the complexity; it automates it. The technology is Model-driven. This gives you the power to turn your meta-data into the very thing it describes. This puts your Model-driven Data Warehouse fully under your control. Changes to the model are implemented automatically. Now you can grow and adapt your Data Warehouse at the speed of your business. Design, generate, adapt without limits.

Why has Data Warehouse Automation become so important?

Processes that have evolved to become standardized and repeatable can be made generic and automated. The frontiers on BI tools were pushed back when reporting tools became generic - from that moment, you no longer had to build the equivalent of Cognos, Business Objects or the Microsoft BI Stack by hand.

In the same way, the underlying Data Warehouse and star-schema Data Marts followed the same route. With BIReady the Data Warehouse architecture that feeds your BI tools is now automated, enforcing best-practices, simplifying the processes, and driving down cost and development time. Its the smart way forward if your organization is serious about data.

Where does Data Warehouse Automation add value to your organization?

Automation solves several problems with traditional Data Warehouse development, both technical and commercial.

  • Building a new Data Warehouse

    It is widely recognized that Data Warehouses are expensive to build by hand. BIReady implements the entire solution straight from your Business Information Model, and does so with a few clicks. You can import your model from your favorite CASE/Modelling tool such as ERWin, reverse-engineer an existing database, or build the model directly in BIReady.

    BIReady generates and executes all the necessary ETL while giving you total control over the process - to tweak and adapt the code for any organization-specific customizations. Data Marts can be designed and adapted using BIReady's wizard interface. Loading can be scheduled and customized with ease. BIReady also supports a wide range of Database platforms.
  • Changes to an existing Data Warehouse

    As if building a Data Warehouse by hand wasn't expensive enough, even more of a shock to most organizations is the cost of change. Since the Data Warehouse technology stack requires tight coupling of the various dependent components between the source systems and the final reports, change requests come with a high price tag.

    Adapting an existing report in order to add a new dimension for drill-down has implications for Data Mart redesign, additional scope for the normalized Data Warehouse that feeds it, the ETL back to the source systems, the handling of history and data warehouse keys and logging. Additional Change-data Capture code has to be implemented. Each of these changes must be managed carefully through analysis, implementation, testing and transition to the production reporting environment.

    Additional complexity is introduced when new developers make changes to an existing Data Warehouse. Different coding styles, and variations in adherence to best-practices impact on maintainability.