Start Data Engineering
SEPTEMBER 18, 2024
1. Introduction 2. Setup 3. Parts of data engineering 3.1. Requirements 3.1.1. Understand input datasets available 3.1.2. Define what the output dataset will look like 3.1.3. Define SLAs so stakeholders know what to expect 3.1.4. Define checks to ensure the output dataset is usable 3.2. Identify what tool to use to process data 3.3. Data flow architecture 3.
The Pragmatic Engineer
SEPTEMBER 19, 2024
This is a follow-up to the article Paying down tech debt , written by industry veteran Lou Franco. Lou has been in the software business for over 30 years as an engineer, EM, and executive. He’s also worked at four startups and the companies that later acquired them; most recently Atlassian as a Principal Engineer on the Trello iOS app. Later this year, he’s publishing a book on tech debt.
Jesse Anderson
SEPTEMBER 18, 2024
Survey Changes Over Time Between 2020 and 2024 (see 2020, 2023, and 2024 for each year’s information), I’ve been conducting a data teams survey. I wanted to dedicate an entire post to examining the change in data teams over time. Total Value Creation The most important question I ask each year concerns data team value creation. I break the question into two parts: “How successful would the business say your projects are?
KDnuggets
SEPTEMBER 12, 2024
Develop unique yet standing-out data science projects to improve your data portfolio.
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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.
Analytics Vidhya
SEPTEMBER 12, 2024
Introduction Imagine yourself as a data professional tasked with creating an efficient data pipeline to streamline processes and generate real-time information. Sounds challenging, right? That’s where Mage AI comes in to ensure that the lenders operating online gain a competitive edge. Picture this: thus, unlike many other extensions that require deep setup and constant coding, […] The post Setup Mage AI with Postgres to Build and Manage Your Data Pipeline appeared first on Analytics Vidhy
Confluent
SEPTEMBER 9, 2024
Confluent has acquired WarpStream, an innovative Kafka-compatible streaming solution. Read the full statement by Jay Kreps, co-founder and CEO of Confluent.
Data Engineering Digest brings together the best content for data engineering professionals from the widest variety of industry thought leaders.
Start Data Engineering
SEPTEMBER 23, 2024
1. Introduction 2. Steps to decide on a data project to build 2.1. Objective 2.2. Research 2.2.1. Job description 2.2.2. Potential referral/hiring manager research 2.2.3. Company research 2.3. Data 2.3.1. Dataset Search 2.3.2. Generate fake data 2.4. Outcome 2.4.1. Visualization 2.5. Presentation 3. Conclusion 4. Read these 1.
Seattle Data Guy
SEPTEMBER 20, 2024
We are still in the early days of data and the value it can add to companies. You’ll read plenty of statistics about how much value data can drive and how far behind companies that aren’t using data are. And as a data consultant, I have helped companies find that value in their data. It… Read more The post How To Modernize Your Data Strategy And Infrastructure For 2025 appeared first on Seattle Data Guy.
KDnuggets
SEPTEMBER 26, 2024
Are you an aspiring data scientist or early in your data science career? If so, you know that you should use your programming, statistics, and machine learning skills—coupled with domain expertise—to use data to answer business questions. To succeed as a data scientist, therefore, becoming proficient in coding is essential. Especially for handling and analyzing.
ArcGIS
SEPTEMBER 18, 2024
Learn the difference between ArcGIS Data Interoperability and FME technology and how they relate to one another.
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!
Engineering at Meta
SEPTEMBER 10, 2024
We’re sharing more about the role that reinforcement learning plays in helping us optimize our data centers’ environmental controls. Our reinforcement learning-based approach has helped us reduce energy consumption and water usage across various weather conditions. Meta is revamping its new data center design to optimize for artificial intelligence and the same methodology will be applicable for future data center optimizations as well.
databricks
SEPTEMBER 19, 2024
Mosaic AI Model Training now supports fine-tuning up to 131K context length for Llama 3.1 models. More efficient training at long sequence lengths is made possible by several optimizations highlighted in this post.
Start Data Engineering
SEPTEMBER 4, 2024
1. Introduction 2. Key parts of data systems: 2.1. Requirements 2.2. Data flow design 2.3. Orchestrator and scheduler 2.4. Data processing design 2.5. Code organization 2.6. Data storage design 2.7. Monitoring & Alerting 2.9. Infrastructure 3. Conclusion 1. Introduction If you are trying to break into (or land a new) data engineering job, you will inevitably encounter a slew of data engineering tools.
Seattle Data Guy
SEPTEMBER 3, 2024
One of the holy grails that many data teams seem to chase is real-time data analytics. After all, if you can have real-time analytics, you can make better decisions faster. However, there often is a conflation between real-time data analytics and stream processing. These are two different concepts that are crucial to understanding how to… Read more The post Real-time Analytics Vs Stream Processing – What Is The Difference?
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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.
KDnuggets
SEPTEMBER 2, 2024
Interested in data engineering? Check out this round-up of built-in Python modules that'll come in handy for data engineering tasks.
Precisely
SEPTEMBER 23, 2024
Are mainframes still relevant today? You bet! The following ten statistics paint a picture that shows mainframes are still going strong, with no signs of slowing. 1. The Mainframe Turns 60: A Milestone in Computing History. 60 years can really fly by! On April 7, 2024 , the Mainframe turned 60. At this milestone, we should all reflect on what the mainframe has done to the computing industry.
Engineering at Meta
SEPTEMBER 17, 2024
This episode of the Meta Tech Podcast is all about Bento , Meta’s internal distribution of Jupyter Notebooks, an open-source web-based computing platform. Bento allows our engineers to mix code, text, and multimedia in a single document and serves a wide range of use cases at Meta from prototyping to complex machine learning workflows. Pascal Hartig ( @passy ) is joined by Steve, whose team has built several features on top of Jupyter, including scheduled notebooks , sharing with colleagues, and
databricks
SEPTEMBER 25, 2024
We are excited to partner with Meta to launch the latest models in the Llama 3 series on the Databricks Data Intelligence Platform.
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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?
ArcGIS
SEPTEMBER 24, 2024
Interested in 3D GIS but not sure where to start? Learn the proper method to transform pre-existing 2D footprint polygons into a 3D buildings.
Confessions of a Data Guy
SEPTEMBER 24, 2024
I recently wrote on my Substack (Data Engineering Central) about how I used the new OpenAI o1 model to do some basic Data Engineering tasks surrounding PostgreSQL. It did ok. I’ve also been using CoPilot and ChatGPT for over a year now to assist me with my daily code that I have to write for […] The post AI (LLMs) and Software Engineering (Writing Code) appeared first on Confessions of a Data Guy.
KDnuggets
SEPTEMBER 12, 2024
The GitHub repository includes up-to-date learning resources, research papers, guides, popular tools, tutorials, projects, and datasets.
Confluent
SEPTEMBER 24, 2024
Learn how your data goes from a producing client all the way to disk on a broker—along the way traversing buffers, threads, queues and more.
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.
Engineering at Meta
SEPTEMBER 4, 2024
We are working in partnership with others to scale inclusive solutions that support the transition to a zero-carbon economy and help create a healthier planet for all.
databricks
SEPTEMBER 5, 2024
An improved answer-correctness judge in Agent Evaluation Agent Evaluation enables Databricks customers to define, measure, and understand how to improve the quality of.
ArcGIS
SEPTEMBER 25, 2024
To publish different views of the same source data, alter map layer settings before you publish each web feature layer.
Confessions of a Data Guy
SEPTEMBER 19, 2024
It is a Brave New World out there these days. The new tools and features come out faster than your mom on Sunday morning getting you ready for church. The same goes for the context and advice being produced on a myriad of platforms, the ole’ Like and Subscribe, and all that bit. It does […] The post Data Modeling in the Brave New Lakehouse World appeared first on Confessions of a 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.
KDnuggets
SEPTEMBER 11, 2024
Kickstart your data analyst career with all these free courses.
Netflix Tech
SEPTEMBER 18, 2024
Vidhya Arvind , Rajasekhar Ummadisetty , Joey Lynch , Vinay Chella Introduction At Netflix our ability to deliver seamless, high-quality, streaming experiences to millions of users hinges on robust, global backend infrastructure. Central to this infrastructure is our use of multiple online distributed databases such as Apache Cassandra , a NoSQL database known for its high availability and scalability.
Christophe Blefari
SEPTEMBER 13, 2024
Back to work ( credits ) Hey you, can you believe it's already September? This year has been flying. It feels like I just blinked, and here we are. In August, I've been focusing mainly on my next big journey—if you follow me on LinkedIn, you might have caught a sneak peek! I'll be making a full announcement next week. I want to take the time to explain my thought process and ideas behind it.
databricks
SEPTEMBER 23, 2024
We are excited to announce that Databricks now supports Amazon EC2 G6 instances powered by NVIDIA L4 Tensor Core GPUs. This addition marks.
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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