October, 2023

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Data Warehouse vs. Data Lake vs. Data Lakehouse: Know the differences

Medium Data Engineering

In the ever-evolving world of data management, three key concepts have gained prominence: Data Warehouse, Data Lake, and the relatively… Continue reading on Medium »

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Drag, Drop, Analyze: The Rise of No-Code Data Science

KDnuggets

No-code or low-code functionalities in data science have gained significant traction in recent years. These solutions are well-proven and matured, and they make data science more accessible to a wider range of people.

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Building a Streaming Data Pipeline with Redshift Serverless and Kinesis

Towards Data Science

An End-To-End Tutorial for Beginners Continue reading on Towards Data Science »

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So, You Want to be a Data Scientist or Machine Learning Developer? Here’s What You Need to Learn!

Medium Data Engineering

Data science, machine learning, artificial intelligence engineering, math Continue reading on Python in Plain English »

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. They're often developing using prompting, Retrieval Augmented Generation (RAG), and fine-tuning (up to and including Reinforcement Learning with Human Feedback (RLHF)), typically in that order. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are le

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Handling a Regional Outage: Comparing the Response From AWS, Azure and GCP

The Pragmatic Engineer

👋 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 three out of seven topics from today’s subscriber-only issue Three Cloud Providers, Three Outages: Three Different Responses.

AWS 239

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Introduction of Microsoft Fabric

Analytics Vidhya

In today’s rapidly evolving digital landscape, seamless data, applications, and device integration are more pressing than ever. Enter Microsoft Fabric, a cutting-edge solution designed to revolutionize how we interact with technology. This article will explore the key features and benefits, identify the ideal users for this solution, and guide you on when and how to […] The post Introduction of Microsoft Fabric appeared first on Analytics Vidhya.

Data 263
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How to use the BranchPythonOperator

Marc Lamberti

Are you looking for a way to choose one task or another? Do you want to execute a task based on a condition? Do you have multiple tasks, but only one should be executed if a criterion is valid? You’ve come to the right place! The BranchPythonOperator does precisely what you are looking for. It’s common to have DAGs with different execution flows, and you want to follow only one, depending on a value or a condition.

Python 246
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The State of WebAssembly 2023 by Colin Eberhardt

Scott Logic

The State of WebAssembly 2023 survey has closed, the results are in … and they are fascinating! If you want the TL;DR; here are the highlights: Rust and JavaScript usage is continuing to increase, but some more notable changes are happening a little further down - with both Swift and Zig seeing a significant increase in adoption. When it comes to which languages developers ‘desire’, with Zig, Kotlin and C# we see that desirability exceeds current usage WebAssembly is still most often used for we

Coding 145
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Snowflake To Acquire Ponder, Boosting Python Capabilities In the Data Cloud

Snowflake

Python’s popularity has more than doubled in the past decade¹ and it is quickly becoming the preferred language for development across machine learning, application development, pipelines, and more. One of our goals at Snowflake is to ensure we continue to deliver a best-in-class platform for Python developers. Snowflake customers are already harnessing the power of Python through Snowpark , a set of runtimes and libraries that securely deploy and process non-SQL code directly in Snowflake.

Python 141
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The Definitive Entity Resolution Buyer’s Guide

Are you thinking of adding enhanced data matching and relationship detection to your product or service? Do you need to know more about what to look for when assessing your options? The Senzing Entity Resolution Buyer’s Guide gives you step-by-step details about everything you should consider when evaluating entity resolution technologies. You’ll learn about use cases, technology and deployment options, top ten evaluation criteria and more.

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Going from Developer to CEO: Chronosphere

The Pragmatic Engineer

👋 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 three out of eight topics from today’s deepdive into tech scaleup Chronosphere. To get full issues twice a week, subscribe here.

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AMM Performance Testing Report

Ripple Engineering

Overview In the rippled 1.12.0 release, the AMM amendment stands out as a significant feature in both size and scope. Since September 2022, the RippleX performance team has collaborated closely with the engineering team responsible for the AMM feature implementation. This report presents a thorough overview of our testing approach, findings, and key takeaways.

AWS 144
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How LinkedIn Is Using Embeddings to Up Its Match Game for Job Seekers

LinkedIn Engineering

Think of how many times a day you use some type of search functionality across your devices and applications to discover information, find a contact, or a new job opportunity. The truth is we all depend on the ability to search for things online, and finding the right match to the information, organization, or to a job that maps to your skills and interests makes all the difference in our experiences and the knowledge we can gain.

IT 134
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Airflow Sensors: What you need to know

Marc Lamberti

Airflow Sensors are one of the most common tasks in data pipelines. Why? Because a Sensor waits for a condition to be true to complete. Do you need to wait for a file? Check if an SQL entry exists? Delay the execution of a DAG? That’s the few possibilities of the Airflow Sensors. If you want to make complex and robust data pipelines, you have to understand how Sensors work genuinely.

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LLM Inference Performance Engineering: Best Practices

databricks

In this blog post, the MosaicML engineering team shares best practices for how to capitalize on popular open source large language models (LLMs).

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5 Free Books to Master Machine Learning

KDnuggets

Machine Learning is one of the most exciting fields in computer science today. In this article, we will take a look at the five best yet free books to learn machine learning in 2023.

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How DoorDash Standardized and Improved Microservices Caching

DoorDash Engineering

As DoorDash’s microservices architecture has grown, so too has the volume of interservice traffic. Each team manages their own data and exposes access through gRPC services, an open-source remote procedure call framework used to build scalable APIs. Most business logic is I/O-bound because of calls to downstream services. Caching has long been a go-to strategy to improve performance and reduce costs.

Coding 121
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Automating dead code cleanup

Engineering at Meta

Meta’s Systematic Code and Asset Removal Framework (SCARF) has a subsystem for identifying and removing dead code. SCARF combines static and dynamic analysis of programs to detect dead code from both a business and programming language perspective. SCARF automatically creates change requests that delete the dead code identified from the program analysis, minimizing developer costs.

Coding 119
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Revolutionizing Real-Time Streaming Processing: 4 Trillion Events Daily at LinkedIn

LinkedIn Engineering

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers. This robust framework empowers near real-time data processing for critical services and platforms, ranging from machine learning and notifications to anti-abuse AI modeling.

Process 122
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High resolution data updates to Living Atlas World Elevation Layers and Tools (October 2023)

ArcGIS

In October 2023, elevation layers have been updated with high-res datasets of France, New Zealand, USA, Italy along with global bathymetry.

Datasets 135
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Training LLMs at Scale with AMD MI250 GPUs

databricks

Introduction Four months ago, we shared how AMD had emerged as a capable platform for generative AI and demonstrated how to easily and.

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7 Steps to Mastering Large Language Models (LLMs)

KDnuggets

Large Language Models (LLMs) have unlocked a new era in natural language processing. So why not learn more about them? Go from learning what large language models are to building and deploying LLM apps in 7 easy steps with this guide.

Building 124
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Announcing Apache Flink 1.18

Confluent

Read updates and improvements in Apache Flink 1.18, including dynamic fine-grained rescaling via REST API, Java 17 support, and faster rescaling & batch performance improvements.

Java 117
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Top 30+ Computer Science Project Topics of 2023 [Source Code]

Knowledge Hut

Choosing the best computer science project topic is critical to the success of any computer science student or employee. After all, the more engaging and interesting topic, the more likely it is that students or employees will be able to stay motivated and focused throughout the duration of the project. However, with so many options out there, it can be tough to decide which one is right for you.

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More Effectively Control and Limit Your Spend With Budgets

Snowflake

At Snowflake, we’re committed to helping customers effectively manage and optimize spend. To this effect, we’re excited to launch the public preview of Budgets on AWS today, which enables customers to set spending limits and receive notifications for Snowflake credit usage for either their entire Snowflake account or for a custom group of resources within an account.

AWS 115
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Prepare your data for the National Spatial Reference System modernization of 2022 in the U.S.

ArcGIS

The new U.S. datums of 2022 will soon be released. This article covers what is coming and how you should prepare your data.

Data 141
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Announcing MLflow 2.8 LLM-as-a-judge metrics and Best Practices for LLM Evaluation of RAG Applications, Part 2

databricks

Today we're excited to announce MLflow 2.8 supports our LLM-as-a-judge metrics which can help save time and costs while providing an approximation of.

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5 Free Books to Master Data Science

KDnuggets

Want to break into data science? Check this list of free books for learning Python, statistics, linear algebra, machine learning and deep learning.

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How Meta is creating custom silicon for AI

Engineering at Meta

With the recent launches of MTIA v1 , Meta’s first-generation AI inference accelerator, and Llama 2 , the next generation of Meta’s publicly available large language model, it’s clear that Meta is focused on advancing AI for a more connected world. Fueling the success of these products are world-class infrastructure teams, including Meta’s custom AI silicon team, led by Olivia Wu, a leader in the silicon industry for 30 years.

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Build Modern Innovative Solutions on Cloudera Data Platform Using the Power of Generative AI with Amazon Bedrock

Cloudera

Enterprises see embracing AI as a strategic imperative that will enable them to stay relevant in increasingly competitive markets. However, it remains difficult to quickly build these capabilities given the challenges with finding readily available talent and resources to get started rapidly on the AI journey. Cloudera recently signed a strategic collaboration agreement with Amazon Web Services (AWS), reinforcing our relationship and commitment to accelerating and scaling cloud native data manag

AWS 106
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Master Data Management: Common Misconceptions You Should Know

Precisely

When most people think of master data management, they first think of customers and products. This is logical, as the core mission of any company is to develop products and services, find the right customers, and consistently deliver excellence. But master data encompasses so much more than data about customers and products. It includes information about suppliers, employees, and target prospects.

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ArcGIS Utility Network: Out-of-the-Box

ArcGIS

Learn how the ArcGIS Utility Network is ready to use without spending a significant amount of time configuring or customizing.

Utilities 135
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Introducing Predictive Optimization: Faster Queries, Cheaper Storage, No Sweat

databricks

Predictive Optimization intelligently optimizes your Lakehouse table data layouts for peak performance and cost-efficiency - without you needing to lift a finger.

Data 113