Wed.Sep 04, 2024

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What are the Key Parts of Data Engineering?

Start Data Engineering

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.

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Read Meta’s 2024 Sustainability Report

Engineering at Meta

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.

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Enhanced Workflows UI reduces debugging time and boosts productivity

databricks

Data teams spend way too much time troubleshooting issues, applying patches, and restarting failed workloads. It's not uncommon for engineers to spend their.

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5 Must-Know R Packages for Data Analysis

KDnuggets

Here are five must-know R packages for data analysis in R.

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Apache Airflow® 101 Essential Tips for Beginners

Apache Airflow® is the open-source standard to manage workflows as code. It is a versatile tool used in companies across the world from agile startups to tech giants to flagship enterprises across all industries. Due to its widespread adoption, Airflow knowledge is paramount to success in the field of data engineering.

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Streaming Postgres data to Databricks Delta Lake in Unity Catalog

Confessions of a Data Guy

Over the many years I’ve been pounding my keyboard … Perl, PHP, Python, C#, Rust … whatever … I, like most programmers, built up a certain disdain for what is called Low Code / No Code solutions. In my rush to worship at the feet of the code we create, I failed, in the beginning, […] The post Streaming Postgres data to Databricks Delta Lake in Unity Catalog appeared first on Confessions of a Data Guy.

Python 100

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Introduction to Polars in 2 Minutes

Confessions of a Data Guy

Polars is the hot new Rust based Python Dataframe tool that is taking over the world and destryoing Pandas even as we speak. You want the quick and dirty introduction to Polars? Look no farther. The post Introduction to Polars in 2 Minutes appeared first on Confessions of a Data Guy.

Python 100
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Detecting AI-written code: lessons on the importance of data quality by Amy Laws

Scott Logic

Our team had previously built a tool to investigate code quality from PR data. Building on this work, we set about finding a method to detect AI-written code, so we could investigate any potential differences in code quality between human and AI-written code. During our time on this project, we learnt some important lessons, including just how hard it can be to detect AI-written code, and the importance of good-quality data when conducting research.

Coding 84
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Training Highly Scalable Deep Recommender Systems on Databricks (Part 1)

databricks

Recommender systems (RecSys) have become an integral part of modern digital experiences, powering personalized content suggestions across various platforms. These sophisticated systems and.

Systems 72
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Comprehensive Guide to Modern Data Warehouse in 2024

Hevo

A data warehouse is a centralized system that stores, integrates, and analyzes large volumes of structured data from various sources. It is predicted that more than 200 zettabytes of data will be stored in the global cloud by 2025.

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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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Let Flink Cook: Mastering Real-Time Retrieval-Augmented Generation (RAG) with Flink

Confluent

How to use Flink AI model inference with familiar SQL syntax to work directly with LLMs and vector databases for your generative AI use cases.

SQL 69
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How to Implement Complex Filters on DataFrame Columns with Pandas

KDnuggets

Learn how to acquire data you need with Pandas filter syntax.

Data 67
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Precisely Women in Technology: Meet Mahima

Precisely

According to the Women in Tech Network , women make up about 35 percent of the tech workforce. While this number has grown over the years, it still indicates that technology is a male-dominated industry. Precisely is committed to creating a supportive environment for women to build their careers so that this number can continue growing. As a result, the Precisely Women in Technology (PWIT) network was developed.

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Harnessing Continuous Data Streams: Unlocking the Potential of Online Machine Learning

Striim

The world is generating an astonishing amount of data every second of every day. It reached 64.2 zettabytes in 2020, and is projected to mushroom to over 180 zettabytes by 2025, according to Statista. Modern problems require modern solutions — which is why businesses across industries are moving away from batch processing and towards real-time data streams, or streaming data.

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Apache Airflow® Crash Course: From 0 to Running your Pipeline in the Cloud

With over 30 million monthly downloads, Apache Airflow is the tool of choice for programmatically authoring, scheduling, and monitoring data pipelines. Airflow enables you to define workflows as Python code, allowing for dynamic and scalable pipelines suitable to any use case from ETL/ELT to running ML/AI operations in production. This introductory tutorial provides a crash course for writing and deploying your first Airflow pipeline.

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Your Guide to Building the Perfect Data Quality Dashboard

Monte Carlo

Picture this: You’re leading a meeting, ready to present the latest sales figures. But, as you start sharing the numbers, someone points out a glaring inconsistency. Suddenly, the room is filled with doubt—about the data, the insights, and, let’s face it, even your judgment. A data quality dashboard is your safety net in these situations. It’s more than a tool—it’s a real-time report card on the health of your data.

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What is ThoughtSpot? Everything You Need to Know

phData: Data Engineering

This article was co-written by Lynda Chao & Tess Newkold With the growing interest in AI-powered analytics, ThoughtSpot stands out as a leader among legacy BI solutions known for its self-service search-driven analytics capabilities. ThoughtSpot offers AI-powered and lightning-fast analytics, a user-friendly semantic engine that is easy to learn, and the ability to empower users across any organization to quickly search and answer data questions.

BI 52
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Application Development vs. Web Development: A Simple Guide

Edureka

Deciding which path to follow between Application Development vs Web Development is a decision that should not be taken lightly. They are both relevant and promising. In both areas, there are numerous opportunities. This guide will help to introduce each one, to state what it is that they do, the skills required, and how they may differ in terms someone with little or no background in sociology can understand.

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Top dbt Alternatives and Competitors –  Ranked by G2

Hevo

In this fast-changing world of data analytics, choosing the right tool for data transformation is one of the keys. Grown in this sector, dbt, or what is popularly known as the data build tool, is a significant solution for SQL-based data transformations, keeping workflows properly and well-documented by data teams inside data warehouses.

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Optimizing The Modern Developer Experience with Coder

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.

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Data Lake vs Data Warehouse: How to choose?

Hevo

Currently, data management is a continually developing field that requires careful consideration when deciding which solution should be implemented to store, process, and analyze data effectively. There are two forms that are frequently selected: data warehouse vs data lake.

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Alteryx vs Matillion: A Side-by-Side Detailed Comparison

Hevo

Data is the new currency in today’s world, helping industries make decisions and innovations. To use data to its full potential, organizations require powerful tools to manage, transform, and analyze vast amounts of it. Various tools are available, among which Alteryx and Matillion stand out as two of the leading ETL solutions.