Sat.May 14, 2022 - Fri.May 20, 2022

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The 6 Python Machine Learning Tools Every Data Scientist Should Know About

KDnuggets

Let's look at six must-have tools every data scientist should use.

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Setting up a local development environment for python data projects using Docker

Start Data Engineering

1. Introduction 2. Set up 3. Reproducibility 3.1. Docker 3.2. Docker Compose 4. Developer ergonomics 4.1. Formatting and testing 4.2. Makefile 5. Conclusion 6. Further reading 7. References 1. Introduction Data systems usually involve multiple systems, which makes local development challenging.

Project 147
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What’s New in Apache Kafka 3.2.0

Confluent

I’m proud to announce the release of Apache Kafka 3.2.0 on behalf of the Apache Kafka® community. The 3.2.0 release contains many new features and improvements. This blog will highlight […].

Kafka 139
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Azure Data Factory: Stored Procedure Activity

Azure Data Engineering

When it comes to transforming structured data, (e.g., applying business logic, standardization etc.) stored in a database, SQL is the most convenient and fit-to-purpose option. Stored procedures provide a way to store the transformation logic as a set of SQL statements that can be re-executed as pre-compiled code. The Stored Procedure Activity in Data Factory provides and simple and convenient way to execute Stored Procedures.

SQL 130
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A Guide to Debugging Apache Airflow® DAGs

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

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The Complete Collection of Data Science Books – Part 1

KDnuggets

Read the best books on Programming, Statistics, Data Engineering, Web Scraping, Data Analytics, Business Intelligence, Data Applications, Data Management, Big Data, and Cloud Architecture.

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Designing And Deploying IoT Analytics For Industrial Applications At Vopak

Data Engineering Podcast

Summary Industrial applications are one of the primary adopters of Internet of Things (IoT) technologies, with business critical operations being informed by data collected across a fleet of sensors. Vopak is a business that manages storage and distribution of a variety of liquids that are critical to the modern world, and they have recently launched a new platform to gain more utility from their industrial sensors.

Designing 100

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New Strategies Needed to Manage Acute Part Shortages

Teradata

Faced with persistent supply chain disruption automotive companies need a new approach to planning. Find out more.

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Popular Machine Learning Algorithms

KDnuggets

This guide will help aspiring data scientists and machine learning engineers gain better knowledge and experience. I will list different types of machine learning algorithms, which can be used with both Python and R.

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Insights And Advice On Building A Data Lake Platform From Someone Who Learned The Hard Way

Data Engineering Podcast

Summary Designing a data platform is a complex and iterative undertaking which requires accounting for many conflicting needs. Designing a platform that relies on a data lake as its central architectural tenet adds additional layers of difficulty. Srivatsan Sridharan has had the opportunity to design, build, and run data lake platforms for both Yelp and Robinhood, with many valuable lessons learned from each experience.

Data Lake 100
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#ClouderaLife Spotlight: Margot Tien, Software Engineer

Cloudera

From fashion to data flow, in this #ClouderaLife Spotlight Margot talks about her career transition from fashion design to cloud computing and her co-founding of Cloudera’s Asian American and Pacific Islander community Employee Resource Group amid the racial tensions of 2021. . It started with feeling stuck and ended with a brand-new career (BTW, lots of hard work in the middle).

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Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

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.

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The Results Are in From The First Ever Data in Motion Report

Confluent

There’s an increasing need for businesses to act intelligently and in real time to win in today’s digital-first world. To achieve this, forward-thinking companies are modernizing their data infrastructure with […].

Data 75
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Natural Language Processing Key Terms, Explained

KDnuggets

This post provides a concise overview of 18 natural language processing terms, intended as an entry point for the beginner looking for some orientation on the topic.

Process 157
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Optimizing dbt Models with Redshift Configurations

dbt Developer Hub

If you're reading this article, it looks like you're wondering how you can better optimize your Redshift queries - and you're probably wondering how you can do that in conjunction with dbt. In order to properly optimize, we need to understand why we might be seeing issues with our performance and how we can fix these with dbt sort and dist configurations.

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What Does a Data Engineer do? A 2023 Guide with Tops Skills

Emeritus

With businesses increasingly relying on data for their day-to-day operations, the role of a data engineer has emerged as one of the most sought-after professions in the industry. But what does a data engineer do exactly? And why is it in demand? According to McKinsey, by 2025, smart workflows and seamless interactions between humans and… The post What Does a Data Engineer do?

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

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.

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Stream Processing vs. Batch Processing: What to Know

Confluent

With more data being produced in real time by many systems and devices than ever before, it is critical to be able to process it in real time and get […].

Process 59
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Finding the Best IDE Software

KDnuggets

What should you be looking for in an IDE? Find out here.

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Data Engineering Annotated Monthly – April 2022

Big Data Tools

Long time no see! Sorry about the silence, but luckily we’re back. Hi, I’m Pasha Finkelshteyn , and I’ll be your guide through this month’s news. I’ll offer my impressions of recent developments in the data engineering space and highlight new ideas from the wider community. If you think I missed something worthwhile, catch me on Twitter and suggest a topic, link, or anything else you want to see.

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What Does a Data Engineer Do and How Can You Become One?

Emeritus

Data is so ubiquitous and valuable that it is touted as the new currency. From data analytics to data engineering, everything is data-centric. As Carly Fiorina, the former Chief Executive Officer of Hewlett Packard, said, “The goal is to turn data into information, and information into insight.” Data allows leaders to make informed decisions that… The post What Does a Data Engineer Do and How Can You Become One?

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How to Modernize Manufacturing Without Losing Control

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

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SQL and Complex Queries Are Needed for Real-Time Analytics

Rockset

This is the fourth post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! Posts published so far in the series: Why Mutability Is Essential for Real-Time Data Analytics Handling Out-of-Order Data in Real-Time Analytics Applications Handling Bursty Traffic in Real-Time Analytics Applications SQL and Complex Queries

SQL 52
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How to Manage Your Complex IT Landscape with AIOps

KDnuggets

Complete guide and blog post series on IT Operations Management with AIOps. Using AI and Machine Learning to manage IT complexity to deliver world class IT service while keeping the lights on.

IT 123
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Data Engineering Annotated Monthly – April 2022

Big Data Tools

Long time no see! Sorry about the silence, but luckily we’re back. Hi, I’m Pasha Finkelshteyn , and I’ll be your guide through this month’s news. I’ll offer my impressions of recent developments in the data engineering space and highlight new ideas from the wider community. If you think I missed something worthwhile, catch me on Twitter and suggest a topic, link, or anything else you want to see.

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Scala 3: General Type Projections

Rock the JVM

Scala's general type projections are considered unsound and were removed in Scala 3: discover what this means and how it affects your code

Scala 52
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The Ultimate Guide to Apache Airflow DAGS

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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The Ultimate Guide To Data Lineage

Monte Carlo

Data lineage isn’t new, but automation has finally made it accessible and scalable—to a certain extent. In the old days (way back in the mid-2010s), lineage happened through a lot of manual work. This involved identifying data assets, tracking them to their ingestion sources, documenting those sources, mapping the path of data as it moved through various pipelines and stages of transformation, and pinpointing where the data was served up in dashboards and reports.

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5 Ways to Double Your Income with Data Science

KDnuggets

Here’s how you can use your data skills to generate side income from home.

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Stakeholder-friendly model names: Model naming conventions that give context

dbt Developer Hub

Analytics engineers (AEs) are constantly navigating through the names of the models in their project, so naming is important for maintainability in your project in the way you access it and work within it. By default, dbt will use your model file name as the view or table name in the database. But this means the name has a life outside of dbt and supports the many end users who will potentially never know about dbt and where this data came from, but still access the database objects in the datab

BI 52
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Operationalizing Machine Learning from PoC to Production

KDnuggets

Most companies haven’t seen ROI from machine learning since the benefit is only realized when the models are in production. Here’s how to make sure your ML project works.

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Apache Airflow® Best Practices: DAG Writing

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!

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Reinforcement Learning for Newbies

KDnuggets

A simple guide to reinforcement learning for a complete beginner. The blog includes definitions with examples, real-life applications, key concepts, and various types of learning resources.

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A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability

KDnuggets

We give a taxonomy of the trustworthy GNNs in privacy, robustness, fairness, and explainability. For each aspect, we categorize existing works into various categories, give general frameworks in each category, and more.

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Should The Data Warehouse Be Immutable?

KDnuggets

Is the data warehouse broken? Is the "immutable data warehouse" the right path for your data team? Learn more here.

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6 Soft Skills for Data Scientists Working Remotely

KDnuggets

As a data scientist, you might have a great portfolio of technical skills, but if you can’t communicate effectively, you won’t be able to convey your ideas clearly during virtual meetings.

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m