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👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and startups through the lens of engineering managers and senior engineers. In this article, we cover one out of three topics from last week’s subscriber-only The Pulse issue. Today, full subscribers got access to a comprehensive Senior-and-above tech compensation research.
Mountains I hope this e-mail finds you well, wherever you are. I'd like to thank you for the excellent comments you sent me last week after the publication of the first version of the Recommendations. This is just the beginning! This week I've added a subscribe button in the Recommendations page in order for you to opt-in for the weekly recommendation email—every Tuesday.
Summary A core differentiator of Dagster in the ecosystem of data orchestration is their focus on software defined assets as a means of building declarative workflows. With their launch of Dagster+ as the redesigned commercial companion to the open source project they are investing in that capability with a suite of new features. In this episode Pete Hunt, CEO of Dagster labs, outlines these new capabilities, how they reduce the burden on data teams, and the increased collaboration that they ena
Learn everything about data science by exploring our curated collection of free courses from top universities, covering essential topics from math and programming to machine learning, and mastering the nine steps to become a job-ready data scientist.
With over 30 million monthly downloads, Apache Airflow is the tool of choice for programmatically authoring, scheduling, and monitoring data pipelines. Airflow enables you to define workflows as Python code, allowing for dynamic and scalable pipelines suitable to any use case from ETL/ELT to running ML/AI operations in production. This introductory tutorial provides a crash course for writing and deploying your first Airflow pipeline.
You probably think this is another internet clickbait title uh? Just trying to get you to clickty clickty and sell you some Google Ads. Two problems. I don’t have Google Ads, and I know a small percentage of people will actually listen to this advice. Whatever. There is a reason some developers struggle to move […] The post The Best Piece of Software Engineering Advice appeared first on Confessions of a Data Guy.
👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and startups through the lens of engineering managers and senior engineers. In this article, we cover one out of five topics from today’s subscriber-only article What Changed in 50 Years of Computing.
👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and startups through the lens of engineering managers and senior engineers. In this article, we cover one out of five topics from today’s subscriber-only article What Changed in 50 Years of Computing.
Mistral ( credits ) Hello all, this is the Data News, this week edition might be smaller than usual in term of comments as I'm working on a Data News related project that takes me a bit of time, which will probably lead to a series of articles. Before I forget I've appeared on The Joe Reis Show , we chatted with Joe about data engineering teaching, why it is hard and about generative AI that will change education for ever.
Summary Artificial intelligence technologies promise to revolutionize business and produce new sources of value. In order to make those promises a reality there is a substantial amount of strategy and investment required. Colleen Tartow has worked across all stages of the data lifecycle, and in this episode she shares her hard-earned wisdom about how to conduct an AI program for your organization.
Marking a major investment in Meta’s AI future, we are announcing two 24k GPU clusters. We are sharing details on the hardware, network, storage, design, performance, and software that help us extract high throughput and reliability for various AI workloads. We use this cluster design for Llama 3 training. We are strongly committed to open compute and open source.
In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!
Databricks’ mission is to deliver data intelligence to every enterprise by allowing organizations to understand and use their unique data to build their.
Seamlessly integrate Apache Kafka data into your lakehouse as Apache Iceberg tables, bridging the operational and analytical divide, with Tableflow. Read more in our blog post.
Summary A significant portion of data workflows involve storing and processing information in database engines. Validating that the information is stored and processed correctly can be complex and time-consuming, especially when the source and destination speak different dialects of SQL. In this episode Gleb Mezhanskiy, founder and CEO of Datafold, discusses the different error conditions and solutions that you need to know about to ensure the accuracy of your data.
Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
Threads has entered the fediverse! As part of our beta experience, now available in a few countries, Threads users aged 18+ with public profiles can now choose to share their Threads posts to other ActivityPub-compliant servers. People on those servers can now follow federated Threads profiles and see, like, reply to, and repost posts from the fediverse.
Streaming Delta tables is slightly different from streaming native streaming sources, such as Apache Kafka topics. One of the significant differences is schema enforcement. It leads to the job failure in case of schema changes of the streamed table.
Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
Friday routine ( credits ) It's Friday and it's Data News. I don't go into too much detail about the magic of Data News, but every Friday is the same. At first, I'm: oh s**t, here we go again and 10 minutes later I'm lost in reading the content and picking too many articles to fit into a thousand word edition. Usually all the process takes me a whole Friday.
Summary Data lakehouse architectures are gaining popularity due to the flexibility and cost effectiveness that they offer. The link that bridges the gap between data lake and warehouse capabilities is the catalog. The primary purpose of the catalog is to inform the query engine of what data exists and where, but the Nessie project aims to go beyond that simple utility.
Want to start your data science journey from home, for free, and work at your own pace? Have a dive into this data science roadmap using the YouTube series.
To comply with a new EU law, the Digital Markets Act (DMA), which comes into force on March 7th, we’ve made major changes to WhatsApp and Messenger to enable interoperability with third-party messaging services. We’re sharing how we enabled third-party interoperability (interop) while maintaining end-to-end encryption (E2EE) and other privacy guarantees in our services as far as possible.
Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali
As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.
By Steve Sobel - Global Industry Leader; Communications, Media & Entertainment Today Databricks and Adobe are excited to announce a strategic partnership focused.
Apache Spark leverages the observer design pattern for the framework-to-code communication. One of the consumers' implementations is StreamingQueryListener.
Recently an Architecture at Databricks recommended people use Notebooks for Production workloads. Very bad and horrible idea. Very expensive compute for most people (All Purpose Clusters) and it leads to horrible development practices. It set off a firestorm on Linkedin when I commented people SHOULD NOT follow this advice. Read here and here The post Never Put Databricks Notebooks in Production appeared first on Confessions of a Data Guy.
Summary Working with data is a complicated process, with numerous chances for something to go wrong. Identifying and accounting for those errors is a critical piece of building trust in the organization that your data is accurate and up to date. While there are numerous products available to provide that visibility, they all have different technologies and workflows that they focus on.
Speaker: Nikhil Joshi, Founder & President of Snic Solutions
Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.
We all need recommendations ( credits ) When I started writing this newsletter nearly three years ago, I never imagined that the words I write on my keyboard would take such an important place in my life. All the interactions I have with you, whether online or offline, are always amazing and give me wings. Today I want to introduce a new feature in the Data News galaxy.
Sharing a belief that open source solutions will foster innovation and transparency in generative AI development, Databricks has announced a partnership and participation.
That's the question. The lack of the processing time trigger means more a reactive micro-batch triggering but it cannot be considered as the single true best practice. Let's see why.
Whether you’re creating complex dashboards or fine-tuning large language models, your data must be extracted, transformed, and loaded. ETL and ELT pipelines form the foundation of any data product, and Airflow is the open-source data orchestrator specifically designed for moving and transforming data in ETL and ELT pipelines. This eBook covers: An overview of ETL vs.
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