Confluent

FEBRUARY 26, 2025

GenAI depends on the data it is fed, thus streaming data has become a necessity, whether you are optimizing real-time supply chains, delivery routes, or customer interactions.

Project 52

Project Data IT 52

Simon Späti

FEBRUARY 26, 2025

Geospatial data is everywhere in modern analytics. Consider this scenario: you’re a data analyst at a growing restaurant chain, and your CEO asks, “Where should we open our next location?” This seemingly simple question requires analyzing competitor locations, population density, traffic patterns, and demographicsall spatial data. Traditionally, answering this question would require expensive GIS (Geographic Information Systems) software or complex database setups.

Database 130

Database Data Engineering Data Engineer Accessibility 130

Precisely

FEBRUARY 26, 2025

Key Takeaways: New AI-powered innovations in the Precisely Data Integrity Suite help you boost efficiency, maximize the ROI of data investments, and make confident, data-driven decisions. These enhancements improve data accessibility, enable business-friendly governance, and automate manual processes. The Suite ensures that your business remains data-driven and competitive in a rapidly evolving landscape.

Data Integration 64

Data Integration Data Management Management Data Governance 64

Monte Carlo

FEBRUARY 26, 2025

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?

Banking 52

Banking Datasets Data Machine Learning 52

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In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate

Data Pipeline

Waitingforcode

FEBRUARY 26, 2025

Is there an easier way to address the insertInto position-based data writing in Apache Spark SQL? Totally, if you use a column-based method such as saveAsTable with append mode.

SQL 130

SQL Data 130

KDnuggets

FEBRUARY 26, 2025

Tired of the job portal grind? Dont just applymake them come to you! Check out 7 powerful strategies to land top-paying tech jobs in 2025.

125

125

KDnuggets

FEBRUARY 26, 2025

Build, test, and deploy a complete application in minutes — just by chatting with OpenHands.

Building 120

Building 120

databricks

FEBRUARY 26, 2025

Building an end-to-end AI or ML platform often requires multiple technological layers for storage, analytics, business intelligence (BI) tools, and ML models in order to.

Machine Learning 86

Machine Learning BI Business Intelligence Technology 86

KDnuggets

FEBRUARY 26, 2025

Learn the best ways to use LLM in your data projects.

Project 100

Project Data Science Data 100

ArcGIS

FEBRUARY 26, 2025

Here is an outright hack to give a line a gradient along its path rather than across it. Maybe it will come in handy?

IT 86

IT 86

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

Data

Striim

FEBRUARY 26, 2025

As businesses increasingly rely on SaaS solutions like Stripe for payment processing, Striim’s integration makes it easier to move, analyze, and leverage payment data in real time. This connector helps streamline data workflows, allowing customers to consolidate their payment data and gain valuable insights faster than ever before. What Does the Stripe Reader Do?

Data Consolidation 40

Data Consolidation Data Workflow Data Pipeline Data 40

databricks

FEBRUARY 26, 2025

Summary Databricks will be at GDC this year, demonstrating how game teams can de-risk their development and better know and grow their player base like.

Data 66

Data Entertainment Media 66

Striim

FEBRUARY 26, 2025

Customer engagement is crucial for businesses to thrive, and platforms like Intercom have made it easier than ever to connect with users through messaging tools for sales, marketing, and customer care. Striim 5.0s new Intercom Reader makes it even easier by enabling seamless real-time data integration from the Intercom platform into your analytics systems.

Data Integration 40

Data Integration Data Collection Data Security Cloud 40

Snowflake

FEBRUARY 26, 2025

According to McKinsey , generative AI will drive four key shifts in enterprise technology, including the rise of autonomous AI data agents that automate workflows and surface insights in real-time. These agents will transform work patterns, optimize IT architectures, and reshape organizational structures to enhance decision-making and reduce operational costs.

Cloud 56

Cloud Business Analyst AWS Architecture 56

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

Systems

Striim

FEBRUARY 26, 2025

Striims suite of connectors for Salesforce applications helps organizations streamline this process by enabling seamless, real-time data movement between Salesforce and other systems. Whether you’re working with Salesforce CRM, Pardot, or Salesforce Marketing Cloud, Striim simplifies the data integration experience. What Does It Do? Striim provides both read and write connectors for Salesforce applications, enabling real-time data movement across multiple Salesforce environments.

BI 40

BI Cloud Data Pipeline Data Integration 40

Wayne Yaddow

FEBRUARY 26, 2025

AI is transforming how senior data engineers and data scientists validate data transformations and conversions. Photo by Markus Spiske on Unsplash Introduction Senior data engineers and data scientists are increasingly incorporating artificial intelligence (AI) and machine learning (ML) into data validation procedures to increase the quality, efficiency, and scalability of data transformations and conversions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Snowflake

FEBRUARY 26, 2025

McKinsey AI41AIIT Snowflake Genesis Computing Snowflake GenesisAIGenbotGenbotEG SuiteJiraTeamsSlack GenesisMatt GlickmanJustin Langseth2SnowflakeGenesisSnowflakeGenesisSnowflake Snowflake AIAIGenesisSnowflakeSnowflakeGenesis Snowflake BUILD 2024 GenesisSnowflakeSnowparkAWSMicrosoft AzureGenbot AISnowflakeAIAIGenesisMattJustinGenesisAI

Building 52

Building 52

Data Council

FEBRUARY 26, 2025

Data Council is looking for Data Engineers, Data Scientists, Data Analysts, and students with similar proven interest to join the Data Council Bay event as volunteers. In exchange, volunteers will be provided free and full access to the three-day event.

Data 52

Data Data Engineering Data Engineer Accessibility 52

Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives

Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri

Manufacturing

Tweag

FEBRUARY 26, 2025

Retrieval-augmented generation (RAG) is about providing large language models with extra context to help them produce more informative responses. Like any machine learning application, your RAG app needs to be monitored and evaluated to ensure that it continues to respond accurately to user queries. Fortunately, the RAG ecosystem has developed to the point where you can evaluate your system in just a handful of lines of code.

Datasets 70

Datasets Database Systems AWS 70

Data Engineering Weekly

FEBRUARY 26, 2025

Lakehouse architecture represents a major evolution in data engineering. It combines data lakes' flexibility with data warehouses' structured reliability, providing a unified platform for diverse data workloads ranging from traditional business intelligence to advanced analytics and machine learning. Roy Hassan , a product leader at Upsolver, now Qlik , offers a comprehensive reality check on Lakehouse implementations, shedding light on their maturity, challenges, and future directions.

Architecture 52

Architecture Amazon Web Services Data Lake AWS 52