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 […] The post Leveraging AI & Automation in Data Engineering: 4 Essential Frameworks appeared first on Ascend.io ..read more

Metadata is the information that provides context and meaning to data, ensuring it’s easily discoverable, organized, and actionable. It enhances data quality, governance, and automation, transforming raw data into valuable insights. Imagine a library with millions of books but no catalog system to organize them. Chaos, right? This is what managing data without metadata feels like. Often described as “data about data,” it is the unsung hero in data management that ensures our vast amounts of information are not only stored but easily discoverable, organized, and actionable. Effective metada ..read more

DataOps, short for Data Operations, integrates data engineering, data quality, and management with agile and DevOps practices. This methodology emphasizes automation, collaboration, and continuous improvement, ensuring faster, more reliable data workflows. With data workflows growing in scale and complexity, data teams often struggle to keep up with the increasing volume, variety, and velocity of data. This is where DataOps comes in—a methodology designed to streamline and automate data workflows, ensuring faster and more reliable data delivery. By adopting this approach, organizations can ..read more

Snowflake Summit 2024 has set the stage for exciting changes in the data landscape. As a data enthusiast and a leader in data engineering, I’m eager to share my reflections on these innovations and their implications for Ascend. Here are my top five takeaways from our week at Moscone Center.  #1 - AI and Machine Learning Continue to Be The New Frontier For me, the most exciting development from the Snowflake Summit 2024 was the enhanced focus on AI and machine learning. The buzz around AI and ML was palpable last week, woven into nearly every keynote and session.  Snowflake’s pa ..read more

Strategic partnership to deliver significant enhancements in efficiency, security, and modernization with advanced AI technology solutions & services SAN FRANCISCO, CA, May 7, 2024 – Wizeline, a leading AI-powered software engineering company, and Ascend.io, a pioneer in data pipeline automation, today announced a partnership that redefines the landscape of data management and utilization across several dynamic sectors, including media, retail, technology, finance, healthcare, and consumer goods.  By combining their respective expertise, Wizeline and Ascend.io will deliver seve ..read more

At Ascend, we believe it’s time to rethink data engineering from the ground up. As the world of data continues to evolve at a breakneck pace, we are thrilled to announce the next revolutionary step in our journey – Project Inception. Ascend has always been at the forefront of innovation, and with Project Inception, we’re setting a new standard. This initiative is more than just an upgrade; it’s a reimagining of what a Data Automation Platform can be: dynamic, extensible, and highly intelligent.  A unified platform that combines a powerful metadata core, an extensible plugin architect ..read more

The rise of generative AI is changing more than just technology; it’s reshaping our professional landscapes — and yes, data engineering is directly experiencing the impact. How does AI recalibrate the workload and priorities of data teams? Does it serve merely as an enhancement to the skills of data professionals, or does it redefine their roles entirely? How can data engineers harness the power of AI? And crucially, what does the future hold for data engineering in an AI-driven world? While data engineering and Artificial Intelligence (AI) may seem like distinct fields at first glance, thei ..read more

You are a data professional. This means that you are fully aware of the recent developments in AI and Large Language Models (LLMs). You’ve identified several complex challenges within your business that AI seems tailor-made to tackle. Exciting, isn’t it Yet, embarking on the AI adoption journey introduces a series of challenges, with one of the most significant being the readiness of your data platform. Is it equipped to support the sophisticated demands of AI initiatives? In this article, we outline the essential prerequisites for an AI data platform. What capabilities should your data plat ..read more

A common hurdle that many data engineering teams face is how to choose the right data replication strategy. Despite the availability of tools that offer a plug-and-play experience, the lack of a deep understanding of these strategies can lead to inefficient data management, potentially derailing your plans to create slowly changing dimensions in your data warehouse. This article breaks down the complexities of data replication strategies in a way that’s easy to understand. By the end of this article, you’ll be equipped with the know-how to choose a strategy that not only makes sense but also ..read more

The rapidly evolving AI landscape presents a multitude of opportunities for organizations. As AI’s capabilities expand, businesses are leveraging these advancements for cost reductions, revenue growth, market expansion, and product innovation (here are some real-world examples).   The McKinsey Global Survey on AI in 2023 highlights this evolution, revealing that despite the nascent stage of generative AI, its use is already widespread, with a third of respondents saying their organizations are utilizing generative AI in at least one function. Source: McKinsey Global Survey on AI ..read more