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Unleashing the next level of organizational decision-making with the cloud data warehouse

The ability for cloud data warehouses to provide a single platform that enables organizations to analyze data at any scale is a market changing capability. Sure, much has been made of the ability of applying Artificial Intelligence (AI) to this data to gain insight into new areas, ultimately to increase an organization’s competitiveness. There is however a greater level of impact that this architecture can have that can be independent of AI and ultimately inclusive of AI.

Unravel Launches Performance Management and Cloud Migration Assessment Solution for Google Cloud Dataproc

We are very excited to announce that Unravel is now available for Google Cloud Dataproc. If you are already on GCP Dataproc or on a journey to migrate on-premises data workloads to GCP Dataproc then Unravel is now available immediately to accelerate and de-risk your Dataproc migration and ensure performance SLAs and cost targets are achieved.

Unravel and Azure Databricks: Monitor, Troubleshoot and Optimize Apache Spark in the Cloud

We are super excited to announce our support for Azure Databricks! We continue to build out the capabilities of the Unravel Data Operations platform and specifically support for the Microsoft Azure data and AI ecosystem teams. The business and technical imperative to strategically and tactically architect the journey to cloud for your organization has never been stronger.

Accelerate and Reduce Costs of Migrating Data Workloads to the Cloud

Today, Unravel announced a new cloud migration assessment offer to accelerate the migration of data workloads to Microsoft Azure, Amazon AWS, or Google Cloud Platform. Our latest offer fills a significant gap in the cloud journey, equips enterprises with the tools to deliver on their cloud strategy, and provides the best possible transition with insights and guidance before, during, and after migration. Full details on the assessment and business value are detailed below in our announcement below.

How to bulk load Snowflake tables using Talend Cloud Platform

Talend Cloud is an Integration platform as a service (iPaaS) offering by Talend. It is a fully managed cloud option which has the capabilities of data integration, data stewardship, data preparation, API designer and Tester and Pipeline designer. These tools can be used for lightweight ETL and detecting the schema on the fly. One of the unique features of Talend Cloud is it provides both on premise and cloud execution environments.

Microsoft Azure & Talend : 3 Real-World Architectures

We know that data is a key driver of success in today data-driven world. In fact, according to Forrester, data and insight-driven businesses are growing at an average of more than 30% annually. However, becoming a data driven organization is not easy. Companies often struggle with speed in accessing and analyzing their data, as well with ensuring delivery of trustworthy data that is free of critical errors.

Katalon and Sauce Labs: A Better Cloud-based Automation Solution

We are excited to announce a partnership establishment with Sauce Labs – a cloud-hosted, web, and mobile application automated testing platform company. This collaboration aims at delivering better automated cloud execution, allowing software development businesses to release high-quality products faster. “One of the challenges that software development teams often face is not having a user-friendly test automation tool, or insufficiency in testing environments.

Meeting SLAs for Data Pipelines on Amazon EMR With Unravel

A household name in global media analytics – let’s call them MTI – is using Unravel to support their data operations (DataOps) on Amazon EMR to establish and protect their internal service level agreements (SLAs) and get the most out of their Spark applications and pipelines. Amazon EMR was an easy choice for MTI as the platform to run all their analytics. To start with, getting up and running is simple. There is nothing to install, no configuration required etc.

How We Moved from Heroku to Google Kubernetes Engine

In my last post I laid out our reasoning for moving from Heroku to Google Kubernetes Engine (GKE) and other GCP services. Now I'll describe the actual migration process in detail. This isn't designed as a how-to guide for migrating from Heroku to GKE—Google has their own excellent tutorial for that—but rather a description of some of the challenges of migrating real-world production applications and how we overcame them.