Snowflake

APRIL 17, 2024

This traditional SQL-centric approach often challenged data engineers working in a Python environment, requiring context-switching and limiting the full potential of Python’s rich libraries and frameworks. This allows your applications to handle large data sets and complex workflows efficiently.

Data Pipeline 107

Data Pipeline Python Data Engineering Data Engineer 107

Knowledge Hut

JANUARY 18, 2024

Speaking of job vacancies, the two careers have high demands till date and in upcoming years are Data Scientist and a Software Engineer. Per the BLS, the expected growth rate of job vacancies for data scientists and software engineers is around 22% by 2030. What is Data Science? What is Software Engineering?

Software Engineer 97

Software Engineer Software Engineering Data Science Engineering 97

Seattle Data Guy

MAY 20, 2023

Starting new data engineering projects can be challenging. Data engineers can get stuck on finding the right data for their data engineering project or picking the right tools.

Data Engineering 147

Data Engineering Data Engineer Project Engineering 147

Analytics Vidhya

MARCH 8, 2023

The Biggest Data Science Blogathon is now live! Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon. Knowledge is power. Sharing knowledge is the key to unlocking that power.”―

Data Science 245

Data Science Data Cloud Computing Deep Learning 245

Data Engineering Weekly

MAY 5, 2024

[link] Uber: From Predictive to Generative – How Michelangelo Accelerates Uber’s AI Journey Constantly adopting and implementing tech advancement with an existing system indicates efficient engineering. Uber wrote an in-depth article about the evolution of its centralized ML platform, Michelangelo.

Data Engineering 67

Data Engineering Data Engineer Engineering Google Cloud 67

Netflix Tech

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community!

Data Engineering 103

Data Engineering Data Engineer Engineering Metadata 103

Simon Späti

MARCH 9, 2021

This post focuses on practical data pipelines with examples from web-scraping real-estates, uploading them to S3 with MinIO, Spark and Delta Lake, adding some Data Science magic with Jupyter Notebooks, ingesting into Data Warehouse Apache Druid, visualising dashboards with Superset and managing everything with Dagster.

Data Engineering 189

Data Engineering Data Engineer Engineering Project 189

Data Engineering Weekly

MARCH 17, 2024

It also introduces emerging standards like the Open Data Contract Standard and Data Product Descriptor Specification. As you know, I’m fascinated by data products and the potential to change the data engineering practice. Can we measure the cost of data incidents?

Data Engineering 70

Data Engineering Data Engineer Engineering Data Governance 70

Towards Data Science

FEBRUARY 10, 2024

Advanced techniques to process and load data efficiently Continue reading on Towards Data Science »

Data Engineering 93

Data Engineering Data Engineer Engineering Data Science 93

Data Engineering Weekly

DECEMBER 3, 2023

link] Microsoft: Generative AI for Beginners Understanding Gen-AI becomes a mandatory skill for application developers and data engineers. link] Netflix: Incremental Processing using Netflix Maestro and Apache Iceberg Netflix writes about its incremental processing design with its orchestration engine Maestro on top of Iceberg.

Data Engineering 70

Data Engineering Data Engineer Engineering Bytes 70

Confessions of a Data Guy

DECEMBER 29, 2022

Data engineering is a vital field within the realm of data science that focuses on the practical aspects of collecting, storing, and processing large amounts of data. appeared first on Confessions of a Data Guy. Here it is.

Data Engineering 130

Data Engineering Data Engineer Engineering IT 130

Towards Data Science

FEBRUARY 24, 2023

The Chaos Data-Engineering Manifesto Another lesson we can learn from software engineers: break stuff to make it more reliable. As a result, the 2020 election was the first I can remember where the on-call engineers weren’t on the edge of their seats, white-knuckling their keyboards…At least not for system reliability reasons.

Data Engineering 97

Data Engineering Data Engineer Engineering Software Engineer 97

KDnuggets

JULY 13, 2022

Linear Algebra for Data Science; 10 Modern Data Engineering Tools; Python String Processing Cheatsheet; Simple Salary Guide for Tech Experts 2022; 16 Essential DVC Commands for Data Science.

Data Science 107

Data Science Data Engineering Data Engineer Engineering 107

Team Data Science

DECEMBER 17, 2020

Organizations in several industries such as banking, healthcare, and automobiles are now acknowledging the value of data science in their mode of operation. Thus, an ideal and efficacious data science team are therefore expected to manage numerous volume of tasks.

Data Engineering 130

Data Engineering Data Engineer Engineering Cloud Computing 130

Towards Data Science

AUGUST 31, 2023

Optimizing queries, improving runtimes, and geospatial data science applications Photo by Tamas Tuzes-Katai on Unsplash Intro: why is a spatial index useful? In doing geospatial data science work, it is very important to think about optimizing the code you are writing. Let’s get started! ? What’s a spatial index?

Data Engineering 75

Data Engineering Data Engineer Engineering Data Science 75

Towards Data Science

AUGUST 19, 2023

How I made the transition to an analytics engineer Photo by Campaign Creators on Unsplash A few years ago, I was at a point where I was feeling unfulfilled in my career. I had been working in data engineering for three years and the initial excitement of starting in the world of tech had faded.

Data Engineering 83

Data Engineering Data Engineer Engineering SQL 83

Data Engineering Weekly

FEBRUARY 4, 2024

Joe Reis: Definition of Data Modeling & What Data Modeling Is not Joe raised a very fundamental question in data engineering. What is Data Modeling, and what is not? He rightly points out that many data engineers will name any of the modeling techniques as data modeling.

Data Engineering 62

Data Engineering Data Engineer Engineering PostgreSQL 62

Towards Data Science

MARCH 17, 2024

Outlining strategies and solution architectures to incrementally load data from various data sources. Continue reading on Towards Data Science »

Data Engineering 73

Data Engineering Data Engineer Engineering Data Science 73

Analytics Vidhya

FEBRUARY 28, 2023

Introduction Data science has taken over all economic sectors in recent times. To achieve maximum efficiency, every company strives to use various data at every stage of its operations.

Data Science 285

Data Science Data Preparation Big Data Data 285

Towards Data Science

NOVEMBER 12, 2023

Readers Digest to Learn Data Engineering Gradually Continue reading on Towards Data Science »

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

Silectis

FEBRUARY 17, 2021

In this blog post, we’ll walk you through how data science and data engineering are complementary disciplines. We’ll also delineate a third category: data analysis. We’ll explore how both data engineering and data science should be marshaled to make better decisions.

Data Science 52

Data Science Data Engineering Data Engineer Engineering 52

Data Science Blog: Data Engineering

DECEMBER 23, 2022

Warum Data Engineering der Data Science in Bedeutung und Berufschancen längst die Show stiehlt, dabei selbst ebenso einem stetigen Wandel unterliegt. Was ein Data Engineer wirklich können muss Der Data Scientist als sexiest Job des 21. Data Engineer, der gefragteste Job des 21sten Jahrhunderts?

Data Engineering 52

Data Engineering Data Engineer Engineering Business Intelligence 52

KDnuggets

FEBRUARY 28, 2024

Begin your data professional journey from the basics of statistics to building a production-grade AI application.

Machine Learning 157

Machine Learning Data Science Data Engineering Data Engineer 157

Simon Späti

MARCH 9, 2021

This post focuses on practical data pipelines with examples from web-scraping real-estates, uploading them to S3 with MinIO, Spark and Delta Lake, adding some Data Science magic with Jupyter Notebooks, ingesting into Data Warehouse Apache Druid, visualising dashboards with Superset and managing everything with Dagster.

Data Engineering 130

Data Engineering Data Engineer Engineering Project 130

Towards Data Science

JANUARY 6, 2024

Knowledge and skills for successful data leadership Continue reading on Towards Data Science »

Data Engineering 97

Data Engineering Data Engineer Engineering Data Science 97

Knowledge Hut

JUNE 26, 2023

Welcome to the world of data engineering, where the power of big data unfolds. If you're aspiring to be a data engineer and seeking to showcase your skills or gain hands-on experience, you've landed in the right spot. What are Data Engineering Projects?

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Data Engineering Data Engineer Coding Project 98

Towards Data Science

MARCH 23, 2024

Data pipelines that would turn you into a decorated data professional Continue reading on Towards Data Science »

Data Engineering 94

Data Engineering Data Engineer Project Engineering 94

Towards Data Science

NOVEMBER 11, 2023

Java Juggernaut: The key to data engineering mastery Continue reading on Towards Data Science »

Java 52

Java Data Engineering Data Engineer Engineering 52

Data Engineering Podcast

JANUARY 30, 2022

Summary Pandas is a powerful tool for cleaning, transforming, manipulating, or enriching data, among many other potential uses. As a result it has become a standard tool for data engineers for a wide range of applications. What are the main tasks that you have seen Pandas used for in a data engineering context?

Data Engineering 100

Data Engineering Data Engineer Engineering Data Pipeline 100

Towards Data Science

NOVEMBER 17, 2023

A go-to guide for data engineers wading through the backfilling maze Continue reading on Towards Data Science »

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

Knowledge Hut

MARCH 15, 2024

At the same time, it has opened up a wealth of opportunities for data engineers. With businesses harnessing the power of Azure’s services, the need for skilled data engineers has topped the charts. Speaking from experience, the data engineers in this role are right in the thick of it all.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Towards Data Science

DECEMBER 1, 2023

Pet Project for Data/Analytics Engineers: Explore Modern Data Stack Tools — dbt Core, Snowflake, Fivetran, GitHub Actions. This hands-on experience will allow you to develop an end-to-end data lifecycle, from extracting data from your Google Calendar to presenting it in a Snowflake analytics dashboard.

Data Engineering 73

Data Engineering Data Engineer Project Engineering 73

KDnuggets

DECEMBER 9, 2022

As more people are entering the field of Data Science and more companies are hiring for data-centric roles, what type of jobs are currently in highest demand?

Data Engineering 160

Data Engineering Data Engineer Engineering Data Science 160

Knowledge Hut

MAY 9, 2024

Data Science, with its interdisciplinary approach, combines statistics, computer science, and domain knowledge and has opened up a world of exciting and lucrative career opportunities for professionals with the right skills and expertise. The market is flooding with the highest paying data science jobs.

Data Science 52

Data Science Data Mining Data Architect Programming Language 52

KDnuggets

JANUARY 17, 2022

In this article, I will describe three of the most promising career options within the data industry? — data analytics, data science, and data engineering.

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Data Engineering Data Engineer Engineering Data 131

Towards Data Science

DECEMBER 11, 2023

Streaming data pipelines and real-time analytics Continue reading on Towards Data Science »

Data Engineering 77

Data Engineering Data Engineer Engineering Data Pipeline 77

RandomTrees

FEBRUARY 2, 2024

GPT-based data engineering accelerators make the working of data more accessible. These accelerators use GPT models to do data tasks faster, fix any issues, and save a lot of time. GPT models change data in simple language and also provide summaries and explanations. One can rely on this information.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52