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).
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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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.
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.
Data Engineering Digest brings together the best content for data engineering professionals from the widest variety of industry thought leaders.
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
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!
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
The Pragmatic Engineer
APRIL 11, 2024
👋 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 four topics from today’s subscriber-only The Pulse issue. To get full issues twice a week, subscribe here.
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.
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.
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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.
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.
KDnuggets
APRIL 3, 2024
Here’s how to stand out from the competition, impress employers, and get a job in data analytics.
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?
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?
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.
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.
ArcGIS
APRIL 12, 2024
How to configure scale-appropriate contour lines and their labels.
KDnuggets
APRIL 16, 2024
Bring the latest AI implementation to Pandas to improve your data workflow.
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.
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.
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.
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.
Seattle Data Guy
APRIL 19, 2024
How data is structured, managed and processed will continue to grow in importance as the demand for AI and machine learning increase. It’s unavoidable that as businesses demand that their data teams implement AI, they will also realize that data engineers are a crucial piece of the data pipeline. That means, if you’re looking for… Read more The post 10 Great Videos To Help You Learn Data Engineering appeared first on Seattle Data Guy.
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.
ArcGIS
APRIL 8, 2024
Starting with ArcGIS Pro 3.2, you can copy layer properties from one feature layer and paste them to another.
KDnuggets
APRIL 1, 2024
Start your AI journey today with these courses from Google.
Christophe Blefari
APRIL 19, 2024
easy ( credits ) Hey, new Friday, new Data News. This week, I feel like the selection is smaller than usual, so enjoy the links. I'm a bit late with the Recommendations emails, I'm sorry about that I got a few new leads as a freelancer I had to take in priority changing a bit my schedule. But don't worry it gonna be out soon. AI News 🤖 When do models get the same hype as 2007 iPhone release?
Waitingforcode
APRIL 18, 2024
Streaming jobs are supposed to run continuously but it applies to the data processing logic. After all, sometimes you may need to release a new job package with upgraded dependencies or improved business logic. What happens then?
Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage
When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.
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