How to Build a Data Pipeline in 6 Steps
Explore how to build a data pipeline in 6 steps, from design to deployment, and learn a new framework to simplify the process.
ETL for Snowflake: Why You Need It and How to Get Started
Dive into ETL for Snowflake: Discover if you need it, when it’s essential, and tips on picking the perfect ETL tool for your data strategy.
Data Orchestration: Defining, Understanding, and Applying
Uncover data orchestration’s impact on workflow efficiency and reevaluate the necessity of an orchestration layer in your data strategy
Five Data Pipeline Best Practices to Follow in 2024
Although every company has unique data challenges, there are several near-universal data pipeline best practices that can guide every data leader in building a solid foundation with their team.
What Is Data Pipeline Orchestration and Why You Need It
Explore data pipeline orchestration, its strategic role in data management, and how it differs from general data orchestration.
ELT Explained: What You Need to Know
Explore the essentials of ELT: uncover its core principles, trace its evolution, and understand its role in today’s dynamic data landscape.
Ep 24 – 2023 Data Engineering Trends
Join Sean and Paul as they unpack the trends from Ascend’s annual DataAware Pulse Survey. Learn why executives and individual contributors disagree on strategy so often… and why many in the data team want to drive automation but struggle to achieve it. All that and a full recap of the 2023 Big Data London event in this episode!
The State of Data Engineering in 2023: Does Your Data Program Stack Up?
Explore 2023 DataAware Pulse findings: Key insights to refine your data team’s strategies and boost competitiveness.
2023 DataAware Pulse Survey
Download the 2023 Dataware Pulse Survey for insights on data engineering trends, best practices, and priorities of data teams.
Ep 23 – The Three Eras Of Data Engineering
Sean and Paul talk the three eras of data engineering teams move through as they get more mature with data processing. We unpack the kinds of metadata required at each stage, and how realistic it is to build a system that processes data in incremental packets instead of full reductions.
Zero ETL: What’s Behind the Hype?
Discover why Zero ETL might not live up to the hype. Exploring its rise, benefits, and deeper implications in the data landscape.
Moving Past ETL and ELT: Understanding the EtLT Approach
Explore the evolution from ETL and ELT to the dynamic EtLT approach, highlighting the shift towards continuous data refinement in modern data operations.
