What is ETL? – (Extract, Transform, Load)
Explore the ETL process, its importance, the transformation to ELT, and the tools needed to consolidate and analyze data effectively.
Getting to the Heart of ETL with Data Transformation
In this episode, Sean and I chat with one of Ascend’s Field Data Engineers, Shayaan Saiyed, about one thing data engineers can’t function without—data transformations.
Data Transformation Explained
How do you structure and make data accessible for stakeholders to drive insights? The answer is data transformation. Discover more!
Three Mistakes Data Engineering Managers Make That Slow Down Development (And How to Speed It Back Up)
Leading data teams is challenging. Few technological domains have undergone such rapid change over the past few years. Yet the vast majority of data teams, 96% to be exact, are at or over capacity.
Data Ingestion: What You Need to Know
Explore the essentials of data ingestion, its types, challenges, and its critical role in effective data analysis and informed decision-making.
Common Change Data Capture Usage Patterns
Dive deep into common Change Data Capture (CDC) techniques to efficiently track and understand database changes and their impacts.
Practices for Data Warehousing with Ascend—Automate the Data Warehouse as a Projection
In this second post in the series “Practices for Data Warehousing with Ascend”, we’ll explore the concept of automating the management of a data warehouse through the projection of source data.
Practices for Data Warehousing with Ascend—Early Query, Fast Iteration, Collaboration
Welcome to the first in a series of posts regarding patterns and practices we’ve learned while working with customers using Ascend within the core of their data platform/stack to help them build and manage data warehouses.
Keeping Up with Data Engineering: A Resource Guide for Data Engineers
As the demand for data engineers increases, data teams must be prepared with the right tools and resources to ensure the role maintains a productive and effective workflow
2020: The Year of the Citizen Data Engineer
Data scientists and data engineers play the primary role in accelerating a company’s data sophistication, providing both the technology and domain expertise from a sea of zeros and ones into valuable data products. As we reflect on 2019 and look forward to the year and decade ahead, we will examine the evolving nature of these roles and teams.
Four Anti-patterns in Balancing Data Teams
Let’s look at how managers of data teams can set the stage for a path that fuels speed and business results, by sorting out different aspects of what needs to get accomplished, and tagging four common mistakes as killer anti-patterns.
Whitepaper | An Assessment of Pipeline Orchestration Approaches
In this whitepaper, we compare and contrast both approaches to pipeline orchestration and the impact to data engineering.
