Articles & Resources

Explore our articles and resources on data and analytics.

Snowflake

Snowflake’s Best Practices for Data Warehouse Development

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

Top 5 performance best practices with Snowflake

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.
Snowflake

Top 5 Benefits to Centralized Data

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.
Snowflake

Snowflake Advantages

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.
Snowflake

Five ways Financial Services Can Benefit from a Cloud Data Platform like Snowflake

Cloud computing and its capabilities have become an essential part of supporting financial services organizations, as many are launching digital transformation initiatives.
Snowflake

Snowflake ELT vs. ETL

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

How Snowflake Delivers A Single Data Experience Across Multiple Clouds And Regions

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.
Snowflake

How can the Snowflake Cloud Data Platform transform your organization? Part 2

One platform to build your data apps.
Snowflake

Data Science Powers the Data-Driven Organization of the Future

Data Scientists and a traditional scientist have a lot in common.