Analytics

Ten Steps to Cloud Migration

In cloud migration, also known as “move to cloud,” you move existing data processing tasks to a cloud platform, such as Amazon Webservices (AWS), Microsoft Azure, or Google Cloud Platform, to private clouds, and-or to hybrid cloud solutions. See our blog post, What is Cloud Migration, for an introduction. Figure 1: Steps in cloud migration.

Using Artificial Intelligence to Interact with the Stock Market | Snowflake Inc.

Michael O'Rourke, SVP of Machine Intelligence at NASDAQ, discusses how NASDAQ integrates artificial intelligence and machine learning models to identify trends, provide data solutions, & detect Stock Market abuse. Rise of the Data Cloud is brought to you by Snowflake.

Analytics Experience Explained

One of the really big trends that we're seeing in the analytics space, is the move towards talking about the analytics experience. Analytics experience is about supporting or triggering decisions and transactions. This is a shift from what I would describe as the passive use of analytics, where people were expected to use dashboards and reports that didn't add a lot of value to their transactions or decision making. The difference sounds subtle, but it's really quite profound.

Snowflake for Marketing Analytics

Identify deeper insights with 360° customer views, create relevant messaging and offers, and produce much higher marketing ROI. Snowflake’s platform virtually eliminates data silos to create a single repository for a single copy of your data. As a result, marketing teams extract deep insights and deliver timely, relevant and consistent customer messaging and offers.

Snowflake Workloads Explained: Data Engineering

Snowflake streamlines data engineering, while delivering performance and reliability. Learn how with Snowflake, data engineers can spend little to no time managing infrastructure, avoiding such tasks as capacity planning and concurrency handling. Instead, they can focus on more value-add activities towards delivering your data.