Confluent

SEPTEMBER 24, 2020

Operating critical Apache Kafka® event streaming applications in production requires sound automation and engineering practices. Streaming applications are often at the center of your transaction processing and data systems, requiring […].

Kafka 143

Kafka Engineering Systems Process 143

Teradata

SEPTEMBER 21, 2020

Get tips on how to cast a more critical eye on the seemingly endless amount of data-driven conclusions presented to us. Learn more.

Data 106

Data 106

Data Engineering Podcast

SEPTEMBER 21, 2020

Summary Data engineering is a constantly growing and evolving discipline. There are always new tools, systems, and design patterns to learn, which leads to a great deal of confusion for newcomers. Daniel Molnar has dedicated his time to helping data professionals get back to basics through presentations at conferences and meetups, and with his most recent endeavor of building the Pipeline Data Engineering Academy.

Data Engineering 100

Data Engineering Data Engineer Engineering AWS 100

Cloudera

SEPTEMBER 23, 2020

In this blogpost, we are going to take a look at some of the OpDB related security features of a CDP Private Cloud Base deployment. We are going to talk about auditing, different security levels, security features of Data Catalog, and Client Considerations. You can find part 1 of this series, here. . Auditing. Comprehensive auditing is provided to enable enterprises to effectively and efficiently meet their compliance requirements by auditing access and other types of operations across OpDB (thr

Database 84

Database Data Lake Metadata Java 84

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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

Confluent

SEPTEMBER 25, 2020

Twitter, one of the most popular social media platforms today, is well known for its ever-changing environment—user behaviors evolve quickly; trends are dynamic and versatile; and special and emergent events […].

Machine Learning 95

Machine Learning Kafka Building Media 95

Teradata

SEPTEMBER 23, 2020

A modern analytics architecture means something different to everyone. What does it mean for your organization? Find out more.

Analytics Architecture 106

Analytics Architecture Architecture IT 106

Cloudera

SEPTEMBER 21, 2020

As organizations look to optimize the speed and cost of their cloud journey in today’s rapidly evolving economy, Cloudera is delighted to announce the availability of Cloudera Data Platform (CDP) Public Cloud in AWS Marketplace. Now customers can easily, confidently and cost-effectively discover, procure and deploy the world’s first Enterprise Data Cloud, powered by AWS, for faster time-to-insight from their advanced analytics and machine learning services.

AWS 83

AWS Cloud Amazon Web Services Data Warehouse 83

Confluent

SEPTEMBER 23, 2020

The promise of cloud computing is simplicity, speed, and cost savings. But what about workloads that can’t move to the cloud? Are they stuck using expensive legacy tooling and practices? […].

Kafka 59

Kafka Cloud Computing Cloud Google Cloud 59

Rock the JVM

SEPTEMBER 24, 2020

Explore the Game-Changing New Types in Scala 3: What We're Eagerly Anticipating

Scala 52

Scala 52

Afterpay Tech

SEPTEMBER 24, 2020

Photo by Pietro Jeng on Unsplash By Letian Wang Context At Afterpay, we are generating lots of data from customer transactions, website views and consumer referrals every day. Being able to derive insights from this data, and to use those insights to  improve our consumer experience and provide value to our merchants and consumers, is a critical competitive differentiator for Afterpay.

Data Science 52

Data Science Building Data Lake Machine Learning 52

Speaker: Tamara Fingerlin, Developer Advocate

Data

Cloudera

SEPTEMBER 24, 2020

Aren’t two superheroes better than one? Some of the most powerful results come from combining complementary superpowers, and the “dynamic duo” of Apache Hive LLAP and Apache Impala, both included in Cloudera Data Warehouse , is further evidence of this. Both Impala and Hive can operate at an unprecedented and massive scale, with many petabytes of data.

Data Warehouse 71

Data Warehouse SQL Engineering Metadata 71

Grouparoo

SEPTEMBER 22, 2020

I have been working on the Salesforce integration. That experience will be its own story. In the process, though, I found something tricky that I might be uniquely experiencing given the combinatorics of the modern Node/Javascript/Typescript world. Grouparoo connects with sources, processes the data from them, and sends that data to destinations. When data comes from a source, we call it an import.

Coding 52

Coding Process Engineering IT 52

Teradata

SEPTEMBER 22, 2020

Learn about the early adopters for both Customer Journey Analytics and Real-Time Marketing who overcame initial hurdles and realized superior business outcomes.

IT 52

IT 52

Preset

SEPTEMBER 22, 2020

Build a beautiful Slack dashboard using open source tools Meltano and Superset. Part 1 of 3.

Building 40

Building Data 40

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

Cloudera

SEPTEMBER 24, 2020

A conversation with civil rights activist and author Dr. Mary Frances Berry about the importance of data in diversity and inclusions initiatives. . COVID-19 has forced businesses to change in ways we didn’t know was possible, and at a speed many had never imagined. The summer of 2020 made something else very clear; while we’ve been agile on digital transformation in business, we have failed to tap data to help us confront deep-seated social justice issues.

Data 68

Data Technology Project IT 68

Teradata

SEPTEMBER 20, 2020

What will it take for energy retailers to transition to world-class segment leaders? The answer is millions of modest improvements, implemented by business users themselves.

Retail 52

Retail IT 52