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Prioritizing requirements and selecting a complete Data Reconciliation and Observability solution that reduces the need for bespoke integration are crucial steps for data decision-makers in the effective implementation of Data reconciliation. On top of it higher adoption of Modern Data Analytics Cloud platforms such as Snowflake, Azure, Datbricks, Redshift, Google [...]
In today’s digital age, data is more than just numbers—it’s the lifeblood of innovation and growth. Organizations are navigating an ever-expanding ocean of information, with streams pouring in from on-premise systems, cloud applications, and hybrid environments. As businesses increasingly rely on this data to drive decisions and operations, the need [...]
Automating Data Reconciliation, Data Observability, and Data Quality Check After Each Data Load. Over the last several years with the rise of cloud data warehouses and lakes such as Snowflake, Redshift, and Databricks, data load processes have become increasingly distributed and complex. Organizations are investing more capital in ingesting data [...]
How to automate data reconciliation between data from 100’s of Data Sources(either on-prem or cloud) with data ingested into Cloud Analytics platform such as Snowflake or Redshift or Google Bigquery or Datalake? Business Use Case Data in many forms. We can love it or hate it, but we can’t [...]
Loading a lot of data to Google BigQuery. That is great. But do you reconcile data after every load to make sure data is in good quality? Business Case A large retail company has multiple ERPs and systems. Everyday, analytics teams load large volumes of data from multiple systems [...]