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Cloud

405% 3-year ROI Procuring Snowflake Through AWS Marketplace: New Forrester TEI Study

Snowflake is delighted to share the findings of a new Forrester Consulting Total Economic Impact™ (TEI) study that examines the potential return on investment for organizations that procure Snowflake through Amazon Web Services (AWS) Marketplace and then use Snowflake as a core part of your application’s architecture. We commissioned the study in partnership with AWS.

Enter the Next Level: Migrating to Cloud Native Platform

Organizations are moving from centralized data centers to distributed cloud native platforms. Due to the complexity of such a migration, an organization would be running a hybrid multi-platform environment which spans from the old to the new world. It starts at the edge of a system, using functionality provided by an API gateway or platform.

Snowflake Demo: Cross-Cloud Replication & Failover and Failback

Snowflake's cross-cloud replication & failover/failback support ensures high availability and quick recovery of data — no matter where or through which cloud provider your business operates. This demo video will walk you through how you would replicate a database across three clouds for business continuity purposes (from AWS US West in Oregon to Azure East US in Virginia to GCP Europe West in the Netherlands).

Data Lake Export Public Preview Is Now Available on Snowflake

Public preview of the data lake export feature is now available. Snowflake announced a private preview of data lake export at the Snowflake virtual summit in June 2020. Data lake export is one of the key features of the data lake workload in the Snowflake Data Cloud. The feature makes Snowflake data accessible to the external data lake, and it enables customers to take advantage of Snowflake’s reliable and performant processing capabilities.

Democratizing Machine Learning Capabilities With Qlik Sense and Amazon SageMaker

The ability to discover insights from past events, transactions and interactions is how many customers currently utilize Qlik. Qlik’s unique approach to Business Intelligence (BI) using an in-memory engine and intuitive interface has democratized BI for typical business users, who usually have little to no technical savvy. But, for many years, organizations have only been able to analyze metrics or KPIs of “what has happened” (i.e., descriptive analytics).

Democratizing Machine Learning Capabilities With Qlik Sense and Amazon SageMaker

The ability to discover insights from past events, transactions and interactions is how many customers currently utilize Qlik. Qlik’s unique approach to Business Intelligence (BI) using an in-memory engine and intuitive interface has democratized BI for typical business users, who usually have little to no technical savvy. But, for many years, organizations have only been able to analyze metrics or KPIs of “what has happened” (i.e., descriptive analytics).

Cloud Data Management Guide: Solutions & Best Practices

Your data can quickly get out of control when you’re working with multiple cloud storage services and applications throughout your organization. Complex cloud ecosystems can make it difficult to know what data you have, how it’s being managed, whether it’s safe, and how to use it effectively. Cloud data management platforms can stop this frustrating scenario in its tracks.

Moving Big Data and Streaming Data Workloads to AWS

Cloud migration may be the biggest challenge, and the biggest opportunity, facing IT departments today - especially if you use big data and streaming data technologies, such as Cloudera, Hadoop, Spark, and Kafka. In this 55-minute webinar, Unravel Data product marketer Floyd Smith and Solutions Engineering Director Chris Santiago describe how to move workloads to AWS EMR, Databricks, and other destinations on AWS, fast and at the lowest possible cost.

The Modern Data Eco System - How teams collaborate to unleash their data

With data becoming the main asset of a business, one of the biggest challenges is how to successfully leverage data to gain a business advantage. In the modern Data Eco System people with different skills set need to collaborate and work together to achieve their data objectives. How does a modern analytics team with data scientists, business analysts and data engineers work together? How are technologies such as Machine Learning, Big data and Cloud come together in a productive way.