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Introduction Today, data systems evolve quickly, demanding efficient monitoring and response. Real-time change detection is essential to keeping systems stable, preventing failures, and ensuring business continuity. Microsoft’s open-source tool, Drasi, addresses this need by effortlessly detecting, monitoring, and responding to data changes across platforms, including relational and graph databases.
We are announcing the General Availability of Provider Usage Analytics for Databricks Marketplace providers. This feature lets you analyze lead generation and product.
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
In 2019, Yelp’s Core Android team led an effort to boost navigation performance in Yelp’s Consumer app. We switched from building screens with multiple separate activities to using fragments inside a single activity. In this blog post, we’ll cover our solution, how we approached the migration and share learnings from along the way as well as performance wins.
When scaling data science and ML workloads, organizations frequently encounter challenges in building large, robust production ML pipelines. Common issues include redundant efforts between development and production teams, as well as inconsistencies between the features used in training and those in the serving stack, which can lead to decreased performance.
When scaling data science and ML workloads, organizations frequently encounter challenges in building large, robust production ML pipelines. Common issues include redundant efforts between development and production teams, as well as inconsistencies between the features used in training and those in the serving stack, which can lead to decreased performance.
Flying home into Detroit this past week working on this blog post on a plane and saw for the first time, the newly connected deck of the Gordie Howe International bridge spanning the Detroit River and connecting the U.S. and Canada. The image stuck out because, in one sense, a feature store is a bridge between the clean, consistent datasets and the machine learning models that rely upon this data.
Monte Carlo, the data observability leader, today announced industry-first features that help identify Databricks query code changes and Gitlab pull requests that result in data quality incidents. To provide business insights and power critical applications, engineers extract data from a variety of sources and then aggregate and transform it into the form required for consumption.
In an era where digital trust has become the cornerstone of meaningful relationships, Precisely is excited to announce the launch of our new Trust Center – a dedicated hub designed to reinforce our commitment to transparency, security, responsible use of AI and data privacy. Here’s what you should know about what this means for our customers. The Pillars of Trust: Transparency & Open Communication Our Trust Center is built on the foundation of transparency.
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
Boston-based WHOOP is on a mission to help its members understand their bodies and unlock their potential through a performance wearable, accompanying app, and 24/7 health data. Data isn’t just critical to optimizing physical potential – it’s also the lifeblood of WHOOP. Director of Business Analytics, Matt Luizzi and his team leverages this data firsthand.
Fog computing, therefore, is a distributed computing paradigm that aims at pushing the computations closer to where the data is generated in order to improve the response time for real-time decisions in scenarios such as IoT. It is different from conventional models of computing, such as cloud computing, which entails sending data to a server for processing instead of the it model, where operations can be accomplished locally with more efficiency and security.
How tech-driven workforce planning brings better-balanced outcomes for everyone Picnic’s supply chain teams work with in-house recruited Runners (electric vehicle drivers) and Shoppers (order pickers). Investing in local talent has been key to building a sustainable, thriving workforce. This approach brings stronger engagement, better alignment with our culture, and a better customer experience.
ReactJS is a famous JavaScript Library created by Facebook that mostly supports user interface solutions, especially for single-page applications (SPAs). It was designed as a way to bring efficient and straightforward solutions that were better than what others had proposed when it was released so long ago. There are several advantages of React, as it has been adopted by developers and companies because of its simplicity and flexibility.
Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri
This is an interesting one indeed, it’s one that teases and puzzles the brain to no end. Has the Data Warehouse finally died, has that unruly upstart the Lake House finally taken its place atop the seething mass of data we call home? Can we say that after all these decades the Data Warehouse Toolkit […] The post The Death of the Data Warehouse, replaced by the Lake House.
Data integration and data processing are among the most significant and critical tasks of the modern data-driven enterprises. Given the number of tools that exist for use, it becomes important for a business to select a right platform for data management, processing and analysis. The two most renowned solutions which can be implemented are Azure data factory vs Databricks.
Backend development is the backbone of any application. While the front end is what users see and interact with, the backend is where the magic happens—processing requests, storing data, and ensuring everything runs smoothly behind the scenes. If you’re looking to embark on a career in backend development or want to refine your skills, this comprehensive guide will walk you through the essential steps to mastering backend development.
Traditional software development needs highly skilled IT pros. They must know a lot about coding. Therefore, it’s slow and resource-intensive, involves highly skilled labor, and increases operational costs. A solution to these challenges will be a “game changer” in low code development. It will democratize software creation. The global low code platform market revenue is expected to grow at a CAGR of 26.1% from 2018 to 2024.
With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to: Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to Write DAGs that adapt to your data at runtime and set up alerts and notifications Scale you
Organizations hire professionals to boost enterprise security with the increasingly growing threat of cyberattacks. The average number of cyber attacks an organization faces every week in Q2 2024 reached 1,636, a significant 30% increase from last year’s numbers over the same quarter. Cybersecurity is a constantly evolving field and, at the very least, requires a professional with many varying skills and certifications in various areas.
Cybersecurity has emerged as a vital consideration for organizations from every sector in this digital information age. The huge demand for professionals with this specific skill means safeguarding sensitive information from cyber threats, which seems to grow by the day. Out of all the certifications in this field of study, Certified Information Systems Security Professional (CISSP) stands out as the most highly regarded.
Nowadays, in the world of web testing, two titans stand out: Cypress and Selenium. Developers and QA engineers often encounter the decision of selecting between these robust tools. Let the dissection of their benefits, drawbacks, and comparison of the two begin below to assist you in making the best decision for your future project. What is Cypress?
Introduction Desired capabilities involve setting browser properties for Selenium automated testing with environment parameters such as browser type, version, and platform. This blog will explain desired capabilities in Selenium, their role for QA professionals, and how they can be effectively employed with Selenium and Appium testing, with examples.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
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