
A client using Databricks faced high infrastructure costs, fragmented data, and poor readiness for advanced analytics. We executed a phased migration to Snowflake as a centralized, cost-effective SSOT. The solution included Snowpipe Streaming from DynamoDB, Oracle CDC via DMS, AWS Step Functions, and DBT-driven transformations.
The result: up to 70% savings in Snowflake usage, improved data governance, and a scalable platform ready for machine learning. Business units now benefit from reliable access and faster insights across the board.
With no developer assigned for nearly a year, a client’s Tableau reports became outdated and unusable. Our team audited and reconnected all big data systems, fixed credential issues, and republished broken reports.
Within days, critical dashboards were restored and performance stabilized. The company quickly regained full access to insights, with a clean and reliable BI environment moving forward.
Think of Business Intelligence as the layer that delivers clean, structured, and often real-time insights to decision-makers through dashboards, reports, and alerts. It's the "what is happening" view of your business perspective.
Data analytics, on the other hand, digs deeper. It explores why something is happening and what might happen next. It includes techniques like predictive analytics modeling, statistical analysis, or machine learning models. At inVerita, we often implement both: business intelligence & analytics services as part of a full data strategy, BI to enable quick wins and visibility, analytics to power long-term innovation and transformation.