Data Project Empowerment


Data Projects are at the foundation of delivering trusted, conformed, and complete information to an organization. However, managing corporate data  is a slow process which business people often feel reluctant to engage in because of its inability to adapt to changing business requirements. The sluggishness is largely a result of the data transformation complexity residing in ETL/ELT tools or in SQL code. Studio is designed to address this complexity by composing data transformation code onto existing ETL/ELT platforms which can be deployed more straightforward business requirements definitions. The output from Studio delivers clean consistent ETL/ELT code which follows appropriate naming conventions and encapsulates best practice data mappings out of the box.

Sample Use Cases

Data Warehousing


Developing the data conformity for a data warehouse requires extensive data transformation code. Developing this code is a task that can be froth with disjointed coding efforts as it requires a team effort to execute. Studio enables data analyst to deploy data transformation assets from the definitions they write. The generation of these assets is also accompanied by automated documentation and data lineage.

Data Vault


Studio is agnostic to modeling approaches. If you are seeking to deploy DataVault 2.0, Kimball, Inmon, Anchor, or any other flavor, Studio has you covered. However, unlike other solutions, Studio does not tightly couple itself to your deployment. Thus you can deploy your Data Vault with your choice of execution engines including, SQL, PySpark, Talend, DataStage, Informatica and others.

On-boarding Data


Partner data is a constant stream of new sources and needs. Studio simplifies the onboarding of data by automating the generation of data transformation assets. 

This also means that you can begin to consider 3rd party sources of data to ingest into existing data warehouses and other important systems to your organization.

Forked Conversion


The BladeBridge Converter is built on the same code foundation as Studio. What this means is that Studio can interact with the conversion process. For example, you may want to conduct your conversion as a vanilla lift and shift but have a portion of the code that you want to fork into newly redeveloped transformation assets. Studio gives you this flexibility out of the box.

Big Data Projects


Studio's ability to deploy native SQL and PySpark makes it a powerful tool for managing large data footprints which can run on distributed data frameworks. The user interface provides useful tools for data analysts to deploy formulas and value mappings without having to know complex data transformation code in PySpark or SQL.

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