Systems | Development | Analytics | API | Testing

March 2021

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.

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.

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.

Why DataOps is Critical for Your Business

Data is often compared to oil – it powers today’s organizations, just like the fossil fuel powered companies of the past. Just like oil, the data that companies collect needs to be refined, structured, and easily analyzed in order for it to really provide value in the form of gaining actionable insights. Every organization today is in the process of harnessing the power of their data using advanced analytics, which is likely running on a modern data stack.

Developing Data Literacy and Standardized Business Metrics at Tailored Brands

In this episode of CDO Battlescars, Sandeep Uttamchandani, Unravel Data’s CDO, speaks with Meenal Iyer, Sr. Director of Enterprise Analytics and Data at Tailored Brands. They discuss battlescars in two areas, data and metrics: Growing Data Literacy and Developing a Data-Driven Culture and Standardization of Business Metrics.

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.

Major Fortune 100 Brands Choose the Unravel Data Platform

It’s hard to believe that Unravel Data was founded eight years ago — though the first few years were dedicated to defining and building our initial product. Since this time, the company has raised several rounds of funding, released several versions of our flagship DataOps Platform, and is being used by some of the world’s leading brands to improve the efficiency and reliability of their data pipelines.