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. See Github repo.

Data Engineering 72

Data Engineering Data Engineer Project Engineering 72

Workfall

JULY 4, 2023

Reading Time: 8 minutes In the world of data engineering, a mighty tool called DBT (Data Build Tool) comes to the rescue of modern data workflows. With DBT, they weave powerful SQL spells to create data models that capture the essence of their organization’s information. In DBT, transformations are like these artisans.

Data Warehouse 69

Data Warehouse SQL PostgreSQL Database 69

Data Engineering Podcast

NOVEMBER 6, 2022

Sonal Goyal created and open-sourced Zingg as a generalized tool for data mastering and entity resolution to reduce the effort involved in adopting those practices. In this episode she shares the story behind the project, the details of how it is implemented, and how you can use it for your own data projects.

MongoDB 130

MongoDB Scala MySQL Data Lake 130

Data Engineering Podcast

FEBRUARY 8, 2021

In this episode Zeeshan Qureshi and Michelle Ark share their experiences using DBT to manage the data warehouse for Shopify. This is a great conversation about the lessons learned from real world use of a specific technology and how well it lives up to its promises.

Data Warehouse 100

Data Warehouse Building BI SQL 100

Workfall

AUGUST 14, 2023

Two powerful tools that have emerged to simplify the management of data pipelines are DBT (Data Build Tool) and Airflow. Two powerful tools that have emerged to simplify the management of data pipelines are DBT (Data Build Tool) and Airflow. In this blog, we will cover: Understanding DBT and Airflow What is DBT?

Data Pipeline 62

Data Pipeline Raw Data Data Database 62

Monte Carlo

JULY 5, 2023

All too often, teams tasked with becoming “data-driven” get excited about new technologies (Snowflake! In our conversation, we learned about Mark and Mike’s “crawl, walk, run” approach to data quality and gained helpful tips and tricks for mastering data quality at scale. What does it mean to be truly “data-driven”? Databricks!)

High Quality Data 52

High Quality Data Data Software Engineer Software Engineering 52

AltexSoft

JANUARY 26, 2022

In addition to understanding data and how it is going to be used, an analytics engineer has to be pretty tech-savvy to apply software engineering best practices to the analytics. In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59