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.

How Xandr, AT&T's Adtech Company, Prevents Revenue Loss with Autonomous Business Monitoring

Anodot CEO and Co-Founder David Drai joined Amazon Web Services and Xandr to discuss the shift to machine learning-based anomaly detection in business monitoring. Xandr Chief Technology Officer Ben John shared how their advertising marketplace is using Anodot platform to cut detection from “up to a week to less than a day”. You can watch the webinar at the link above or read on for the highlights of that talk.

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 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.

Snowflake Workloads Explained: Data Applications

Snowflake’s platform powers applications with virtually unlimited performance, concurrency, and scale. Launch new features faster with simplified data pipelines and improved engineering efficiency. Delivered as a service, Snowflake handles the infrastructure complexity, so you can focus on innovating with the data applications you build.