Leveraging AI & Automation in Data Engineering: 4 Essential Frameworks
Data engineering is evolving rapidly, driven by advancements in AI and automation. As teams face increasing demands, the need for efficient and effective solutions has never been greater. This article […]
Automating Data: Practical Steps and Real-World Examples
Explore the intricacies of automating data: from practical steps and common challenges to real-world success stories in diverse industries.
How to Use Snowpark in Two Steps
Explore Snowpark’s process from setup to advanced deployment. Discover how Ascend simplifies this detailed journey for data engineers.
Data Pipeline Architecture: Understanding What Works Best for You
Delve into data pipeline architecture types and get actionable guidance on choosing the best fit for your business.
Data Mesh Implementation: Your Blueprint for a Successful Launch
Kick-start your data mesh implementation with our hands-on guide. Stop overthinking, start acting, and harness the power of data mesh effectively.
Is Your Company Ready to Graduate from Data as a Product to Data Mesh?
Explore the transformative journey from data product to data mesh, its benefits, and assess your business’s readiness for this change.
Creating Value With a Data-Centric Culture: Essential Capabilities to Treat Data as a Product
Discover how to harness data as a strategic business asset through advanced technical capabilities and a data-centric culture.
Data Pipeline Optimization: How to Reduce Costs with Ascend
Data pipeline optimization helps cut costs, enhance efficiency, pinpoint hotspots, and drive data-driven success.
How to Ensure Data Integrity at Scale By Harnessing Data Pipelines
We developed a framework with a sequence of stages to implement data integrity quickly and measurably via data pipelines.
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.
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.
