Data Engineering Weekly

FEBRUARY 2, 2025

The article advocates for a "shift left" approach to data processing, improving data accessibility, quality, and efficiency for operational and analytical use cases. link] Get Your Guide: From Snowflake to Databricks: Our cost-effective journey to a unified data warehouse.

Data Engineering 57

Data Engineering Data Engineer Engineering Data Lake 57

Monte Carlo

JANUARY 16, 2024

Factor in the advertising strategies, media production, partner programming, audience analytics…and you’re looking at an ocean of data that would fill even the deepest trench (we’d like a television show about that too, please!). So how does Fox’s data strategy support these complex data workflows?

Government 52

Government High Quality Data Data Governance Entertainment 52

Monte Carlo

APRIL 24, 2023

While we won’t get into the minutia of every consideration for every level of the data stack, it’s important to recall these five considerations as they’ll nonetheless steer the direction of our conversation. It required a complete data workflow and an orchestration team that’s frankly not feasible for most organizations.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Data Engineering Podcast

MAY 18, 2024

Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. Unfortunately this often turns into an exercise in frustration for everyone involved due to complex workflows and hard-to-understand dashboards.

Building 278

Building Data Lake High Quality Data Business Intelligence 278

RandomTrees

MAY 6, 2025

Modern data engineering can help with this. It creates the systems and processes needed to gather, clean, transfer, and prepare data for AI models. Without it, AI technologies wouldn’t have access to high-quality data. It incorporates far more than basic data handling techniques.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Cleanse 52