Tue.Dec 19, 2023

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Order is king for the performance

Waitingforcode

Even though nowadays data processing frameworks and data stores have smart query planners, they don't take our responsibility to correctly design the job logic.

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How Meta built the infrastructure for Threads

Engineering at Meta

On July 5, 2023, Meta launched Threads, the newest product in our family of apps, to an unprecedented success that saw it garner over 100 million sign ups in its first five days. A small, nimble team of engineers built Threads over the course of only five months of technical work. While the app’s production launch had been under consideration for some time, the business finally made the decision and informed the infrastructure teams to prepare for its launch with only two days’ advance notice.

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Practical Magic: Improving Productivity and Happiness for Software Development Teams

LinkedIn Engineering

Co-authors: Max Kanat-Alexander and Grant Jenks Today we are open-sourcing the LinkedIn Developer Productivity & Happiness Framework (DPH Framework) - a collection of documents that describe the systems, processes, metrics, and feedback systems we use to understand our developers and their needs internally at LinkedIn. Now more than ever, developers are navigating so much change and new opportunity in this new era of Generative AI, so ensuring teams have the systems, processes, metrics and f

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5 Cheap Books to Master Data Science

KDnuggets

There are many data-learning materials locked up behind expensive books. These cheap books would bolster your skills without blowing up your savings.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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AI debugging at Meta with HawkEye

Engineering at Meta

HawkEye is the powerful toolkit used internally at Meta for monitoring, observability, and debuggability of the end-to-end machine learning (ML) workflow that powers ML-based products. HawkEye supports recommendation and ranking models across several products at Meta. Over the past two years, it has facilitated order of magnitude improvements in the time spent debugging production issues.

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AI-Automated Cybersecurity: What to Automate?

KDnuggets

Soon AI will become embedded into daily business processes, including cybersecurity controls. The author explains how to assess which processes make sense to automate.

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Deployment of Exabyte-Backed Big Data Components

LinkedIn Engineering

Co-authors: Arjun Mohnot , Jenchang Ho , Anthony Quigley , Xing Lin , Anil Alluri , Michael Kuchenbecker LinkedIn operates one of the world’s largest Apache Hadoop big data clusters. These clusters are the backbone for storing and processing extensive data volumes, empowering us to deliver essential features and services to members, such as personalized recommendations, enhanced search functionality, and valuable insights.

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Databricks Data Intelligence Platform for Retail comes to NRF 2024

databricks

Request a meeting with Databricks executives/thought leaders at NRF! Each January, thousands of leaders from retailers around the globe gather at Javits Center.

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Make this AI-inspired topo landscape please

ArcGIS

Here's how to fake an isometric 3D topo terrain in 2D! And stuff.

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Optimizing the Value of AI Solutions for the Public Sector

Cloudera

Without a doubt, 2023 has shaped up to be generative AI’s breakout year. Less than 12 months after the introduction of generative AI large language models such as ChatGPT and PaLM, image generators like Dall-E, Midjourney, and Stable Diffusion, and code generation tools like OpenAI Codex and GitHub CoPilot, organizations across every industry, including government, are beginning to leverage generative AI regularly to increase creativity and productivity.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Build AI Apps with Amazon PartyRock and Amazon Bedrock

Workfall

Reading Time: 16 minutes Introducing Amazon PartyRock, an innovative platform that redefines the landscape of app exploration and creation. For Part 1 of this blog, refer here. In this transformative hands-on implementation, we will guide you through the PartyRock playground, an exciting journey that encompasses navigating its free features, signing in to unlock personalized experiences, experimenting with suggested apps, exploring a myriad of pre-built applications, and culminating in the creat

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Tips for training data preparation for object detection models

ArcGIS

We will dive into our best practices for preparing and using training samples for object detection models.

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LiveRamp Customers Build ‘Foundation of Identity’ With Snowflake Native Apps

Snowflake

The best marketing is truly data-driven, creating powerful product promotions and offers through an understanding of customer needs and preferences. But for many organizations, building this understanding is more akin to solving an ever-growing jigsaw puzzle (with no easy edge pieces!) than reading data insights from a beautiful dashboard. Every customer store interaction, online transaction, form fill, event participation, chatbot response, text request, like, review, complaint, and click creat

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Running Airflow DAG Only If Another DAG Is Successful

Towards Data Science

Using Airflow sensors to control the execution of DAGs on a different schedule Continue reading on Towards Data Science »

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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Toronto’s Data Science Renaissance: A Tale of Two Markets

WeCloudData

The Recap We continue with the unfolding saga of the data science jobs landscape, this time for the month of November. In my previous blog, I continued to compare Toronto’s data science jobs market against the rest of North America, and after a strong September, it didn’t look especially good for Toronto. It looked as […] The post Toronto’s Data Science Renaissance: A Tale of Two Markets appeared first on WeCloudData.

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ETL for Snowflake: Why You Need It and How to Get Started

Ascend.io

If you’re working with Snowflake or just starting to explore its capabilities, you might be wondering: Do I really need ETL for Snowflake? Is it possible to rely solely on Snowflake’s own features, or is there a strong case for bringing ETL into the mix? If so, where do I get started? In this article, we’re diving into these questions to clear up any confusion.

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Digitizing Customer Experience in the Travel Industry

Confluent

Legacy data systems often power travel experiences, such as on cruise lines, but modern customers want real-time experiences online. Here's how to think about data integration with data streaming for travelers.

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Conscientious Computing - Podcasts: What we are listening to right now! by Charlotte Hayes

Scott Logic

Many of us love a good podcast so I reached out to our project team to see what they were listening to in the tech and sustainability space. Here are their recommendations: Environment Variables If I were to pick one podcast to start with, then this would be the one. Published by the Green Software Foundation, each episode aims to bring listeners the latest news regarding how to reduce the emissions of software and how the industry is dealing with its own environmental impact.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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15 Essential Java Full Stack Developer Skills in 2024

Knowledge Hut

Java, as the language of digital technology, is one of the most popular and robust of all software programming languages. It is ideal for cross-platform applications because it is a compiled language with object code that can work across more than one machine or processor. All programming is done using coding languages. Java, like Python or JavaScript, is a coding language that is highly in demand.

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2023 in a nutshell —ride along!

Picnic Engineering

With operations in full swing to pull us through the busiest time of the year, the code slush we apply in some of our teams allow us to take a step back and reflect on another exciting year in the crazy little groceries roller coaster we call Picnic. In this blog, we’d like to give you a glimpse into some of the major developments in Picnic Tech in 2023.

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React Architecture Pattern: Implementation + Best Practices

Knowledge Hut

React comes with so many features that help you develop fantastic User Interfaces. One cool thing with React is that it doesn't force you to use a predefined architectural pattern like other JavaScript frameworks do. That is to say, React allows you to determine the structure of your application by yourself. An architectural pattern in front-end development is the blueprint of the User Interface.

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How to integrate with dbt

dbt Developer Hub

Overview ​ Over the course of my three years running the Partner Engineering team at dbt Labs, the most common question I've been asked is, How do we integrate with dbt? Because those conversations often start out at the same place, I decided to create this guide so I’m no longer the blocker to fundamental information. This also allows us to skip the intro and get to the fun conversations so much faster, like what a joint solution for our customers would look like.

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.

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A Blueprint for a Real-World Recommendation System

Rockset

Overview In this guide, we will: Understand the Blueprint of any modern recommendation system Dive into a detailed analysis of each stage within the blueprint Discuss infrastructure challenges associated with each stage Cover special cases within the stages of the recommendation system blueprint Get introduced to some storage considerations for recommendation systems And finally, end with what the future holds for the recommendation systems Introduction In a recent insightful talk at Index confe

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