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Latest Videos

How to get Observability for Apache Airflow

Observability of Apache Airflow presented by Ry Walker, Founder & CTO at Astronomer. Apache Airflow has become an important tool in the modern data stack. We will explore the current state of observability of Airflow, common pitfalls if you haven't planned for observability, and chart a course for where we can take it going forward.

DataOps Unleashed Things You May Not Know About Apache Kafka but Should

Things You May Not Know About Apache Kafka but Should presented by Patrick Druley, Senior Solution Engineer at Confluent. In this session, you will learn about some of the common misconceptions, best practices, and little-known facts about Apache Kafka. Event Streaming has changed the way businesses think about data movement and integration. If you are new to Kafka or having been creating topics and developing clients for years, there's something for everyone in this fun and informative session.

DataOps Unleashed Dataops Automation and Orchestration With Fivetran, Dbt, and the Modern Data Stack

Dataops Automation and Orchestration With Fivetran, Dbt, and the Modern Data Stack presented by Nick Acosta, Developer Advocate at Fivetran. Many organizations struggle with creating repeatable and standardized processes for their data pipeline. Fivetran reduces pipeline complexity by fully managing the extraction and loading of data from a source to a destination and orchestrating transformations in the warehouse.

Prepare Your Data - The Self-Service Data Roadmap, Session 2 of 4

In this webinar, Unravel CDO and VP Engineering Sandeep Uttamchandani describes the second step for any large, data-driven project: the Prep phase. Having found the data you need in the Discover phase, it's time to get your data ready. You must structure, clean, enrich, and validate static data, and ensure that "live," updated or streamed data events are continually ready for processing.

Going Beyond Observability for Spark Applications & Databricks Environments

Join Chris Santiago, Solutions Engineer Director at Unravel Data, as he takes you through Unravel’s approach to getting better and finer grain visibility with Spark applications and how to tune and optimize them for resource efficiency. An overview of out of the box tools like Ganglia and their overall lack of visibility on Databricks jobs How Unravel helps you gain finer grain visibility, observability, monitoring into Spark data pipelines How Unravel can recommend better configurations and tuning of Spark applications.

Discover Your Datasets - The Self-Service Data Roadmap, Session 1 of 4

In this session, Unravel CDO and VP Engineering Sandeep Uttamchandani describes the start of any large, data-driven project: the Discover phase. You must identify the insights you want to generate from the project, you must discover; that is, you must identify the current data assets you have, and the new data assets you will need, to generate the insights you want to produce. Sandeep expertly guides you through this process, and shows you how to invest the right amount of time and effort to get the job done.

Moving Big Data and Streaming Data Workloads to Google Cloud Platform

Cloud migration may be the biggest challenge, and the biggest opportunity, facing IT departments today - especially if you use big data and streaming data technologies, such as Cloudera, Hadoop, Spark, and Kafka. In this 55-minute webinar, Unravel Data product marketer Floyd Smith and Solutions Engineering Director Chris Santiago describe how to move workloads to Google Dataproc, BigQuery, and other destinations on GCP, fast and at the lowest possible cost.