Data quality issues are present in all data warehouses. But how can you tell if the quality of your data is good? The answer: set data quality dimensions.
Learn to talk fluent data with this data glossary, covering data terminology, and specific terms related to analytics, DataOps, data development, and more.
Read on for perspectives on how Agile Data Engine helps business and IT departments improve their DataOps and take action to fix bottlenecks and issues.
Outlining Data Vault best practices - approaches for managing, structuring, and modeling data and data warehouses in complex, dynamic environments.
Choosing a data modeling approach requires understanding things from business needs to methodologies. Here we unpack data modeling stages & approaches.
Data modeling as important as ever when you move your data warehouse from on-prem into the cloud - it's a crucial component of resilient data ops.
In DataOps, terms get muddled by jargon - as does data when stored in a data lake, eventually devolving into to a data swamp. Here's a brief guide to help.
Cloud data warehouse transformation with Agile Data Engine helps airports improve passenger experience and maximise efficiency beyond just DataOps and EDW
Data modeling turns data structures, relationships, attributes, and rules into visual and understandable blueprints that describe how the organization uses its data.
DataOps Database Selection projects can be time-consuming and overwhelming. But with the right tools, like Agile Data Engine, you can design once and deploy anywhere, saving time and effort. Future-proof your data warehouse and streamline your cloud data journey.
