The Pragmatic Engineer
APRIL 21, 2024
See a longer version of this article here: Scaling ChatGPT: Five Real-World Engineering Challenges. Sometimes the best explanations of how a technology solution works come from the software engineers who built it. To explain how ChatGPT (and other large language models) operate, I turned to the ChatGPT engineering team. "How does ChatGPT work, under the hood?
Start Data Engineering
APRIL 22, 2024
1. Introduction 2. Docker concepts 2.1. Define the OS and its configurations with an image 2.2. Use the image to run containers 2.2.1. Communicate between containers and local OS 2.2.2. Start containers with docker CLI or compose 3. Conclusion 1. Introduction Docker can be overwhelming to start with. Most data projects use Docker to set up the data infra locally (and often in production).
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Data Engineering Podcast
APRIL 21, 2024
Summary Generative AI has rapidly transformed everything in the technology sector. When Andrew Lee started work on Shortwave he was focused on making email more productive. When AI started gaining adoption he realized that he had even more potential for a transformative experience. In this episode he shares the technical challenges that he and his team have overcome in integrating AI into their product, as well as the benefits and features that it provides to their customers.
Confessions of a Data Guy
APRIL 28, 2024
A few years ago I wasn’t sure, who was going to win, Golang seemed to be popular, and still is for that matter. When I first wrote a little Golang (~2+ years ago) I was just trying to see what the hype was all about. The funny thing is, at the time, and today, it […] The post Why did Golang lose to Rust for Data Engineering? appeared first on Confessions of a Data Guy.
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In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate
KDnuggets
APRIL 25, 2024
Interested in switching to data engineering? Here’s a list of Python libraries you’ll find super helpful.
Seattle Data Guy
APRIL 25, 2024
As data increased in volume, velocity, and variety, so, in turn, did the need for tools that could help process and manage those larger data sets coming at us at ever faster speeds. As a result, frameworks such as Apache Spark and Apache Flink became popular due to their abilities to handle big data processing… Read more The post Apache Spark Vs Apache Flink – How To Choose The Right Solution appeared first on Seattle Data Guy.
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Start Data Engineering
APRIL 22, 2024
1. Introduction 2. Ensure the code’s logic is working as expected with tests 2.1. Test types for data pipelines 2.2. pytest: A powerful Python library for testing 2.2.1. Set context, run code, check results & clean up 2.2.2. Tests are identified by their name 2.2.3. Use fixture to create fake data for testing 2.2.4. Define items to be shared among tests with conftest.
Data Engineering Podcast
APRIL 7, 2024
Summary Maintaining a single source of truth for your data is the biggest challenge in data engineering. Different roles and tasks in the business need their own ways to access and analyze the data in the organization. In order to enable this use case, while maintaining a single point of access, the semantic layer has evolved as a technological solution to the problem.
Confessions of a Data Guy
APRIL 19, 2024
Being Data Analytics is a meat grinder, it’s the worst job ever. Horrible it is. It will crush you. The post Data Analytics Suck! Worst Job Ever! appeared first on Confessions of a Data Guy.
KDnuggets
APRIL 15, 2024
Want to learn math for data science? Check out these three courses to learn linear algebra, calculus, statistics, and more.
Speaker: Tamara Fingerlin, Developer Advocate
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.
Snowflake
APRIL 24, 2024
Building top-tier enterprise-grade intelligence using LLMs has traditionally been prohibitively expensive and resource-hungry, and often costs tens to hundreds of millions of dollars. As researchers, we have grappled with the constraints of efficiently training and inferencing LLMs for years. Members of the Snowflake AI Research team pioneered systems such as ZeRO and DeepSpeed , PagedAttention / vLLM , and LLM360 which significantly reduced the cost of LLM training and inference, and open sourc
databricks
APRIL 18, 2024
We are excited to partner with Meta to release the latest state-of-the-art large language model, Meta Llama 3 , on Databricks. With Llama.
ArcGIS
APRIL 10, 2024
Starting with ArcGIS Pro 3.2, you can export all symbols in the map as style items and save them to a style in a single process.
Data Engineering Podcast
APRIL 28, 2024
Summary Generative AI promises to accelerate the productivity of human collaborators. Currently the primary way of working with these tools is through a conversational prompt, which is often cumbersome and unwieldy. In order to simplify the integration of AI capabilities into developer workflows Tsavo Knott helped create Pieces, a powerful collection of tools that complements the tools that developers already use.
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.
Confessions of a Data Guy
APRIL 19, 2024
Back in March, I did a writeup and experiment called DuckDB vs Polars, Thunderdom, 16GB on 4GB machine challenge. The idea was to see if the two tools could process “larger than memory” datasets with lazy execution. Polars worked fine, DuckDB failed in spectacular fashion. I also noted how many people had opened issues in […] The post DuckDB Out Of Memory – Has it been fixed?
KDnuggets
APRIL 3, 2024
Here’s how to stand out from the competition, impress employers, and get a job in data analytics.
Snowflake
APRIL 11, 2024
Data is the lifeblood of modern businesses, but unlocking its true insights often requires complex SQL queries. These queries can be time-consuming to write and challenging to maintain. At Snowflake, we believe in making the power of data accessible to all. That’s why we prioritize simplicity, governance and quality in everything we build – including our AI-powered tools.
databricks
APRIL 23, 2024
We're thrilled to announce the General Availability (GA) of Databricks Asset Bundles (DABs). With DABs you can easily bundle resources like jobs.
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
ArcGIS
APRIL 12, 2024
How to configure scale-appropriate contour lines and their labels.
Data Engineering Podcast
APRIL 14, 2024
Summary Databases come in a variety of formats for different use cases. The default association with the term "database" is relational engines, but non-relational engines are also used quite widely. In this episode Oren Eini, CEO and creator of RavenDB, explores the nuances of relational vs. non-relational engines, and the strategies for designing a non-relational database.
Confessions of a Data Guy
APRIL 30, 2024
The post Reaction to Data Engineering Survey for 2024 appeared first on Confessions of a Data Guy.
KDnuggets
APRIL 16, 2024
Bring the latest AI implementation to Pandas to improve your data workflow.
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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.
Snowflake
APRIL 1, 2024
Snowflake and Salesforce are happy to share that bidirectional data sharing between Snowflake, the Data Cloud company and Salesforce Data Cloud is now generally available. In September, we proudly announced that organizations could begin leveraging Salesforce data directly in Snowflake via zero-ETL data sharing to unify their customer and business data, accelerate decision-making and help streamline business processes.
databricks
APRIL 9, 2024
At Databricks, we’re committed to building the most efficient and performant training tools for large-scale AI models. With the recent release of DBRX.
ArcGIS
APRIL 8, 2024
Starting with ArcGIS Pro 3.2, you can copy layer properties from one feature layer and paste them to another.
Seattle Data Guy
APRIL 28, 2024
If you’ve worked in data long enough, then you’ve likely come across the term change data capture. Often called CDC, change data capture involves tracking and recording changes in a database as they happen, and then transmitting these changes to designated targets. This can be crucial because some pipelines, in particular batch pipelines, don’t capture… Read more The post Terms You Should Know If You’re Planning To Use Change Data Capture appeared first on Seattle D
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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?
Waitingforcode
APRIL 24, 2024
As a data engineer you're certainly familiar with data skew. Yes, this bad phenomena where one task takes considerably more input than the others and often causes unexpected latency or failures. Turns out, stream processing also has its skew but more related to time.
KDnuggets
APRIL 1, 2024
Start your AI journey today with these courses from Google.
Snowflake
APRIL 4, 2024
Data transformation is the process of converting data from one format to another, the “T” in ELT, or extract, load, transform, which enables organizations to get their data analytics-ready and derive insights and value from it. As companies collect more data, from disparate sources and in disparate formats, building and managing transformations has become exponentially more complex and time-consuming.
databricks
APRIL 30, 2024
We are proud to announce that Forrester has recognized Databricks as a Leader with the highest scores in both current offering and strategy.
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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
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