Mon.Nov 18, 2024

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From IC to Data Leader: Key Strategies for Managing and Growing Data Teams

Seattle Data Guy

There are plenty of statistics about the speed at which we are creating data in today’s modern world. On the flip side of all that data creation is a need to manage all of that data and thats where data teams come in. But leading these data teams is challenging and yet many new data… Read more The post From IC to Data Leader: Key Strategies for Managing and Growing Data Teams appeared first on Seattle Data Guy.

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Expert Insights for Your 2025 Data, Analytics, and AI Initiatives

Precisely

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. A long-term approach to your data strategy is key to success as business environments and technologies continue to evolve. The rapid pace of technological change has made data-driven initiatives more crucial than ever within modern business strategies.

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DuckDB … reading from s3 … with AWS Credentials and more.

Confessions of a Data Guy

In my never-ending quest to plumb the most boring depths of every single data tool on the market, I found myself annoyed when recently using DuckDB for a benchmark that was reading parquet files from s3. What was not clear, or easy, was trying to figure out how DuckDB would LIKE to read default AWS […] The post DuckDB … reading from s3 … with AWS Credentials and more. appeared first on Confessions of a Data Guy.

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Change Data Capture at Pinterest

Pinterest Engineering

Liang Mou; Staff Software Engineer, Logging Platform | Elizabeth (Vi) Nguyen; Software Engineer I, Logging Platform | In today’s data-driven world, businesses need to process and analyze data in real-time to make informed decisions. Change Data Capture (CDC) is a crucial technology that enables organizations to efficiently track and capture changes in their databases.

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A Guide to Debugging Apache Airflow® DAGs

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

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Expert Insights for Your 2025 Data, Analytics, and AI Initiatives

Precisely

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. A long-term approach to your data strategy is key to success as business environments and technologies continue to evolve. The rapid pace of technological change has made data-driven initiatives more crucial than ever within modern business strategies.

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A Guide to Data Analysis in Python with DuckDB

KDnuggets

Learn how to perform data analysis in Python using DuckDB.

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Develop the Right AI Skills for Job Security

KDnuggets

Don’t get left behind - start learning AI with 5-course tracks by DataCamp with 50% on Black Friday deal!

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Automating Unity Catalog Upgrade Workflows with UCX

databricks

As organizations increasingly leverage the Databricks Data Intelligence Platform for data and AI needs, upgrading to Unity Catalog is a key step in.

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Exploring Python’s Ellipsis (…) : More than Just Syntax Sugar

KDnuggets

Ever wondered what the three dots (.) in Python are used for? Discover how this powerful operator can simplify your code!

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From Data Warehousing to Data Intelligence: How Data Took Over

databricks

While GenAI is the focus today, most enterprises have been working for a decade or longer to make data intelligence a reality within.

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Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

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.

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The Importance of Reducing Your Digital Shadow as a Data Scientist

KDnuggets

This is the tool you need to protect yourself and your organization.

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Unlock Databricks cost transparency

Sync Computing

In the world of big data and cloud computing, managing costs effectively is a significant challenge. While Databricks provides powerful tools for data engineers and analysts, understanding the complete cost picture can be complex. Databricks customers receive two separate bills – one for their Databricks usage and another from their cloud provider where clusters were spun up to run Databricks workloads.

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Snowflake Will Automatically Disable Passwords Detected on the Dark Web

Snowflake

Security has been an integral part of Snowflake’s platform since the company was founded. Through the security capabilities of Snowflake Horizon Catalog , we empower security admins and CISO’s to better protect their environments. As part of our continued efforts to help customers secure their accounts, and in line with our pledge to align with CISA’s Secure By Design principles, we are announcing the general availability of Snowflake Leaked Password Protection (LPP).

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