Data Mastering and Governance
Data Readiness towards your workload migration
Your challenge, our solution
Transforming and maintaining a data-focused culture requires a disciplined approach to data acquisition, ingestion, curation, and governance.
truData Solutions partnerships, experience, and focus provide the roadmap and strategy that suits your business – from best-in-breed collections of tools like Snowflake on AWS or Azure platforms to platform-specific implementations of Azure Synapse, AWS, and SAP.
Building a Golden Record provides a central reference towards your overall enterprise data strategy
What questions are we answering?
How can I enable our project teams with the best quality source data for their development and conversion process?
It’s a proven best practice to provide the conversion process the best source data whenever possible, as opposed to cleansing and applying enrichments rules during the cutover itself.
How can I improve the quality and percentage of data loaded during our testing cycles prior to go-live?
Source data cleansing and building a complete master data reference can begin prior to your system migration initiative and be completed independently. This mitigates the risk of poor master data during integration testing and user acceptance.
truData partners with clients to build a ‘Golden Record’ source towards the data conversion process, taking an early look at the available master data and creating a solid reference for the load process throughout the project life cycle and go-live.
We work with clients to assess the quality of their master data in source systems and begin addressing data quality issues very early (even independently) of your journey.
truData helps consolidate master data into a single reference model reducing redundant data conversion developments, based on unique data sources. This improves the quality of master data in the new system.
truData’s approach creates a common Master or Reference Data Repository providing a central reference towards your overall enterprise data strategy
Improved and more consistent testing during your system implementation
Higher quality data loads into system at go-live
More efficient data loads that do not depend on extensive routines in the ETL process
Cloud Database (Azure Synapse, Databricks, Redshift, etc.), Databricks