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In recent years, Health Information Exchange (HIE) capabilities have helped mobilize patient data allowing clinicians and healthcare managers to provide near real time diagnosis closing the gap on member care.

How do we gain buy-in with enterprise Data Governance and data quality programs and processes when your organization is exercising caution due to past failures? Data Governance has become a critical discipline and important area of focus for organizations to realize operational efficiency and to support business growth.

Many of our customers have grown primarily through mergers and acquisitions to achieve accelerated growth. As a result, the organization quickly faces the prospects of multiple applications and systems that deliver similar functions and store the same data.

By implementing Snowflake’s best practices, it becomes possible to better understand and articulate your data warehouse’s overall structure and layout.

The Snowflake Data Platform is designed for scale, efficiency, and ease of use. It supports an unlimited number of Virtual Data Warehouse clusters that offer shared access for optimal performance.

With the enormous revenue potential tied to digitization, data management is becoming even more critical, reaching an all-time high in demand for enterprise data management initiatives.

Cloud-based technology like Snowflake provide financial services organizations with a much needed competitive advantage.

Success with Snowflake will lead to building a data foundation that future initiatives can build on to further advance and grow the organization’s data and analytics capabilities.

There are two main data movement processes for the Snowflake data warehouse technology platform. Extract, Transform, and Load (ETL) vs. Extract, Load, and Transform (ELT).

Snowflake’s core architecture is built on a multi-tier cloud data platform that scales independently. Snowflake’s multi-cluster shared data architecture consolidates data warehouses, data marts, and data lakes into a single source of truth that enables any data workload on any cloud with a simple, powerful, and flexible platform.

Leveraging the shared datasets feature from Power BI allows your company’s analysts to work from a single source of truth.