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By now, most data leaders know that developing useful AI applications takes more than RAG pipelines and fine-tuned models it takes accurate, reliable, AI-ready data that you can trust in real-time. To borrow a well-worn idiom, when you put garbage data into your AI model, you get garbage results out of it. Of course, some level of data quality issues is an inevitabilityso, how bad is “bad” when it comes to data feeding your AI and ML models?
Annual Report: The State of Apache Airflow® 2025 DataOps on Apache Airflow® is powering the future of business – this report reviews responses from 5,000+ data practitioners to reveal how and what’s coming next. Get the report → Editor’s Note: Data Council 2025, Apr 22-24, Oakland, CA Data Council has always been one of my favorite events to connect with and learn from the data engineering community.
Apache Iceberg is a modern table format designed to overcome the limitations of traditional Hive tables, offering improved performance, consistency, and scalability. In this article, we will explore the evolution of Iceberg, its key features like ACID transactions, partition evolution, and time travel, and how it integrates with modern data lakes. Well also dive into […] The post How to Use Apache Iceberg Tables?
Many data engineers and analysts start their journey with Postgres. Postgres is powerful, reliable, and flexible enough to handle both transactional and basic analytical workloads. It’s the Swiss Army knife of databases, and for many applications, it’s more than sufficient. But data volumes grow, analytical demands become more complex, and Postgres stops being enough.
With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to: Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to Write DAGs that adapt to your data at runtime and set up alerts and notifications Scale you
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AI adoption is accelerating, but most enterprises are still stuck with outdated data management. The organizations that win in 2025 wont be the ones with the biggest AI modelstheyll be the ones with real-time, AI-ready data infrastructures that enable continuous learning, adaptive decision-making, and assist regulatory compliance at scale. Whats changing?
AI adoption is accelerating, but most enterprises are still stuck with outdated data management. The organizations that win in 2025 wont be the ones with the biggest AI modelstheyll be the ones with real-time, AI-ready data infrastructures that enable continuous learning, adaptive decision-making, and assist regulatory compliance at scale. Whats changing?
In todays data-driven world, organizations depend on high-quality data to drive accurate analytics and machine learning models. But poor data quality gaps, inconsistencies and errors can undermine even the most sophisticated data and AI initiatives. According to a new report by MIT Technology Review Insights , done in partnership with Snowflake, more than half of those surveyed indicated that data quality is a top priority.
The enterprise AI landscape is expanding all the time. With that expansion comes new challenges and new learning opportunities when it comes to GenAI development. Every day, the engineering team at Monte Carlo works with hundreds of customers across industries who are building AI in production today by monitoring the structured data and RAG pipelines that power their applications, from chatbots and cloud spend optimization to self-service analytics enablement and structuring unstructured data a
In today’s digital age, cybersecurity companies in India play a crucial role in safeguarding our personal data and critical systems. Because technology is getting into every part of our lives, strong cybersecurity measures are needed to keep data, personal information, and important systems safe from cyber risks that are getting smarter all the time.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
Earlier this week, we announced new agent development capabilities on Databricks. After speaking with hundreds of customers, we've noticed two common challenges to advancing beyond.
The enterprise AI landscape is expanding all the time. With that expansion comes new challenges and new learning opportunities when it comes to GenAI development. Every day, the engineering team at Monte Carlo works with hundreds of customers across industries who are building AI in production today by monitoring the structured data and RAG pipelines that power their applications, from chatbots and cloud spend optimization to self-service analytics enablement and structuring unstructured data a
Introduction Developers have a lot of tools and technologies at their disposal that are meant to make work faster and easier. Since its release in 2021, GitHub Copilot has been a star. It does more than just speed things up. It shines when it comes to making complicated code easier to understand and making switching between computer languages easier.
In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!
Natural Language Processing (NLP) is the key to all the recent advancements in Generative AI. Like many other industries, NLP has also revolutionized the life sciences and healthcare. The application of NLP in the medical domain ranges from drug discovery and efficient diagnosis to patient care and automating administrative tasks. To learn more about how […] The post Natural Language Processing in Healthcare appeared first on WeCloudData.
In todays dynamic retail environment, staying connected to customer sentiments is more crucial than ever. With shoppers sharing their experiences across countless platforms, retailers are.
Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
Compared to large language models (LLMs), which are limited in size, speed, and ease of customization, small language models (SLMs) would be a more economical, efficient, and space-saving AI technology for users with limited resources. With fewer parameters (usually less than 10 billion), SLMs are assumed to have lower computational and energy costs.
Learn how to delete topics in Apache Kafka safely and efficiently. Explore step-by-step instructions, best practices, and important considerations for managing Kafka topics.
Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
Deep Convolutional Generative Adversarial Networks (DCGANs) – a subclass of Generative Adversarial Networks (GANs) – have utilized convolutional neural networks (CNNs) to synthesize good-quality images. The architecture was established by Radford et al. in 2015, significantly improving the original GANs from their earlier forms as it innovates these architectural changes that lead to stabilizing the training process and also further the quality of generated images.
These models are free to use, can be fine-tuned, and offer enhanced privacy and security since they can run directly on your machine, and match the performance of proprietary solutions like o3-min and Gemini 2.0.
Knowing how to write effective SQL queries is an essential skill for many data-oriented roles. On one end of the spectrum, writing complex SQL queries can feel like a feat even if it might feel like its eating at your soul during the process. All of the above? Courtesy of Reddit. On the opposite side of the SQL spectrum is a strategy thats potentially even more impressive and useful than long-winded, complex SQL strings: SQL query optimization.
Apache Airflow® is the open-source standard to manage workflows as code. It is a versatile tool used in companies across the world from agile startups to tech giants to flagship enterprises across all industries. Due to its widespread adoption, Airflow knowledge is paramount to success in the field of data engineering.
Learn how Confluent and Databricks detect and prevent toxic in-game chat while allowing competitive trash talk, preserving player experience while keeping gaming communities safe.
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Artificial Intelligence (AI) research is rapidly advancing, with DeepSeek AI emerging as one of the most promising models in the field. The new DeepSeek AI study paper goes into great detail about the system’s architecture, how it is trained, how it is optimized, and how it can be used in the real world. This blog will break down the research paper’s key aspects, helping you understand how DeepSeek AI works and why it stands out in the AI landscape.
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Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali
As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.
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