CI/CD for Data Teams: A Roadmap to Reliable Data Pipelines
Continuous Integration and Continuous Delivery (CI/CD) has transformed software development by enabling faster, safer deployments – and data teams are now realizing these same benefits must extend to data pipelines and analytics code. But applying CI/CD in a data context comes with unique challenges. In this guide, we’ll explore general CI/CD principles and dive into […]
Data Engineering Trends in 2025: Your Roadmap to Smarter Data Teams
Data teams are under more pressure than ever before, with demands skyrocketing and technology outpacing teams’ ability to adapt. Understanding how your team stacks up against these challenges is crucial—it could mean the difference between leading the charge and falling behind. Over the past five years, Ascend.io has conducted the industry-wide Pulse Survey to capture […]
2025 DataAware Pulse Survey
Download the 2025 Dataware Pulse Survey for insights on data engineering trends, best practices, and priorities of data teams.
Modernizing Your Data Management Strategy for the AI Era
6 Ways To Prepare Your Data Team for 2025
As we approach 2025, data teams find themselves at a pivotal juncture. The rapid evolution of technology and the increasing demand for data-driven insights have placed immense pressure on these teams. According to recent research, 95% of data teams are operating at or over capacity, highlighting the urgent need for strategic preparation. This isn’t just […]
How To Future-Proof Your Data Pipelines
Why Future-Proofing Your Data Pipelines Matters Data has become the backbone of decision-making in businesses across the globe. The ability to harness and analyze data effectively can make or break a company’s competitive edge. But when data processes fail to match the increased demand for insights, organizations face bottlenecks and missed opportunities. Future-proofing involves designing […]
Complete Guide to Data Transformation: Basics to Advanced
What is Data Transformation? Data transformation is the process of converting raw data into a usable format to generate insights. It involves cleaning, normalizing, validating, and enriching data, ensuring that it is consistent and ready for analysis. Data transformation is key for data-driven decision-making, allowing organizations to derive meaningful insights from varied data sources. If […]
AI’s Impact on Data Engineering Careers
Data engineering is the backbone of any data-driven organization, responsible for building and maintaining the infrastructure that supports data collection, storage, and analysis. Traditionally, data engineers have focused on the technical aspects of data management, ensuring data pipelines run smoothly and efficiently. However, the landscape is changing rapidly, and data engineers are finding themselves at […]
Data Flows: Designing Strategies for Seamless Integration
How to Design a Data Flow in 6 Steps: 1. Engage Key Stakeholders2. Identify Data Sources3. Define Data Requirements4. Implement Data Flow Diagrams (DFDs)5. Build & Optimize Data Pipelines6. Incorporate Feedback Loops Data flows are the unsung heroes of the digital age, overseeing the seamless movement of information across systems and platforms. But what are […]
Deploying AI to Enhance Data Quality and Reliability
AI-driven data quality workflows deploy machine learning to automate data cleansing, detect anomalies, and validate data. Integrating AI into data workflows ensures reliable data and enables smarter business decisions. Data quality is the backbone of successful data engineering projects. Poor data quality can lead to costly errors, misinformed decisions, and ultimately, a significant economic impact. In […]
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 (based on the webinar below) explores how data engineering teams can leverage AI and automation to enhance productivity and tackle current challenges. We will explore […]
Metadata: What Is It and Why it Matters
Learn effective metadata management practices to streamline your data engineering workflows, enhance data quality, & optimize your pipelines.
