Systems | Development | Analytics | API | Testing

FedRAMP High Authorization on AWS GovCloud (US-West and US-East) Expands Snowflake's Commitment to Serving the Public Sector

It’s a milestone moment for Snowflake to have achieved FedRAMP High authorization on the AWS GovCloud (US-West and US-East Regions) . This authorization, from the Federal Risk and Authorization Management Program (FedRAMP), is one of the most rigorous security endorsements a cloud service provider (CSP) can achieve.

Harnessing the Data Cloud to Empower Our Own Marketing Team: Building a Digital Ads Ecosystem on Snowflake

You need metrics to do your job well as a marketer but getting clear, meaningful metrics is a huge challenge. While digital advertisers and paid media professionals are on the hook to build ample sales pipeline and maximize return on ad spend (ROAS), they’re also expected to deliver personalized advertising content while navigating evolving privacy requirements and adhering to consumer expectations—all while extracting insights from siloed ad platforms.

15 Examples of Data Pipelines Built with Amazon Redshift

At Integrate.io, we work with companies that build data pipelines. Some start cloud-native on platforms like Amazon Redshift, while others migrate from on-premise or hybrid solutions. What they all have in common is the one question they ask us at the very beginning: And so that’s why we decided to compile and publish a list of publicly available blog posts about how companies build their data pipelines.

Using ClearML and MONAI for Deep Learning in Healthcare

This tutorial shows how to use ClearML to manage MONAI experiments. Originating from a project co-founded by NVIDIA, MONAI stands for Medical Open Network for AI. It is a domain-specific open-source PyTorch-based framework for deep learning in healthcare imaging. This blog shares how to use the ClearML handlers in conjunction with the MONAI Toolkit. To view our code example, visit our GitHub page.

Understanding the Limitations of AI: How to Tackle Them? | Raju Kandaswamy #shorts #ai

In this video, Raju explores certain segments where AI faces challenges, shedding light on instances that circulated on social media. There's a revelation about AI's struggle with single-shot answers, a phenomenon that once garnered much attention and even bragging rights.

Why Is Unique, Dynamic and Run-Time Test Data Important? | Vishal Parmar #testdata #softwaretesting

In this insightful session, Vishal Parmar sheds light on the critical significance of dynamic, unique, run-time, and compliant test data in the testing landscape. Explore the key takeaways, including the essential role of unique and dynamic test data, ensuring it aligns with prerequisites and localization requirements. Vishal emphasizes the importance of comprehensive data compliance, covering the removal of data during execution.

How Your API Strategy Is Fundamental to Any Data Mesh Strategy

The data mesh approach has gained popularity over the last couple of years as organizations look for reliable ways to break down data silos. At first, data lakes looked like a good way to improve data management and make information more discoverable. Unfortunately, data lakes — and data warehouses — don’t always conform to business needs. They’re often slow and even unresponsive to queries. Potentially even worse, they can still lead to data silos.

What is Confluent?

Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations.